European guidelines for quality assurance in breast cancer screening and diagnosis : fourth edition, supplements.
Date: 2013-10-16
Institutions: Directorate-General for Health and Consumers
Subjects: cancer, disease prevention, health policy, medical diagnosis, public health, report, woman

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Financial  support  was  provided  by  the  European  Union Public  Health  Programme  (Project  no. 
2006322,  European  Cooperation  on  Development  and  Implementation  of  Cancer  Screening  and  Pre-
vention Guidelines [ECCG]).

The views expressed in this document are those of the authors and do not necessarily reflect the offi-
cial position of the European Commission. Neither the European Commission nor any other organiza-
tion, nor any person acting alone or on behalf of others can be held responsible for any use that may 
be made of the information in this document.

Special  thanks  are  due  to  the  IARC  staff  in  the  Quality  Assurance,  Screening  and  Communication 
Groups who provided technical and editorial assistance.

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Luxembourg: Office for Official Publications of the European Union, 2013

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European  guidelines  for  quality  assurance  in  breast
cancer screening and diagnosis                   FourthEdition

Supplements                       

Editors
N. Perry
M. Broeders
C. de Wolf
S. Törnberg
R. Holland
L. von Karsa

EEDDIITTOORRSS  

N. Perry 
The London Breast Institute 
Princess Grace Hospital 
42 Nottingham Place 
London W1U 5NY / United Kingdom 

M. Broeders 
National Expert and Training Centre for Breast Cancer Screening 
EUREF Office 
P.O. Box 6873 
6503 GJ Nijmegen / The Netherlands 

C. de Wolf 
Swiss Cancer Screening Federation 
Effingerstrasse 40 
Postfach 8219 
CH-3001 Bern / Switzerland 

S. Törnberg 
Department of Cancer Screening 
Regional Cancer Centre 
Karolinska University Hospital 
S-17176 Stockholm / Sweden 

R. Holland 
National Expert and Training Centre for Breast Cancer Screening 
EUREF Office 
P.O. Box 6873 
6503 GJ Nijmegen / The Netherlands 

L. von Karsa 
Quality Assurance Group 
Section of Early Detection and Prevention 
International Agency for Research on Cancer 
150 cours Albert Thomas 
F-69372 Lyon Cedex 08 / France 

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European guidelines for quality assurance in breast cancer screening and diagnosis  Fourth edition  Supplements 

 
 
 
 
 
Address for correspondence 
Dr Lawrence von Karsa 
Quality Assurance Group 
International Agency for Research on Cancer 
150 cours Albert Thomas 
F-69372 Lyon cedex 08 
France

European guidelines for quality assurance in breast cancer screening and diagnosis  Fourth edition  Supplements 

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Authors, contributors and editors1

Isabel Amendoeira, Serviço de Anatomia Patológica H.S. João and IPATIMUP 
Porto, Portugal 

Ahti Anttila, Finnish Cancer Registry 
Helsinki, Finland 

Jean-Pierre Bellocq, University Hospital Strasbourg 
Strasbourg, France 

Simonetta Bianchi, University of Florence 
Florence, Italy 

Magdalena Bielska-Lasota, National Institute of Public Health – NIH 
Warsaw, Poland 

Werner Boecker, University of Münster 
Münster, Germany 

Bettina Borisch, University of Geneva 
Geneva, Switzerland 

Hilde Bosmans2, University Hospitals Leuven 
Leuven, Belgium 

Mireille Broeders, National Expert and Training Centre for Breast Cancer Screening 
Nijmegen, The Netherlands 

Birgitte Bruun Rasmussen, Herlev Hospital 
Herlev, Denmark 

1  Authors, contributors and editors serve in their individual capacities as experts and not as representatives of their 
government or any organization with which they are affiliated. Affiliations are provided for identification purposes 
only. Each expert was asked to disclose pertinent research, employment, and financial interests. Current financial 
interests and research and employment interests during the past 4 years or anticipated in the future are identified 
here. 
Minor pertinent interests are not listed and include stock valued at no more than US$ 10 000 overall, grants that 
provide  no  more  than  5%  of  the  research  budget  of  the  expert’s  organization  and  that  do  not  support  the 
expert’s  research  or  position,  and  consulting  or  speaking  on  matters  not  before  a  court  or  government  agency 
that does not exceed 2% of total professional time or compensation. All grants that support the expert’s research 
or  position  and  all  consulting  or  speaking  on  behalf  of  an  interested  party  on  matters  before  a  court  or 
government agency are listed as significant pertinent interests. 

2  H.  Bosmans  and  the  University  of  Leuven  where  she  works  hold  shares  in qaelum,  a  company  established  in 
October 2011 after her work on the digital mammography supplement was complete. The company provides soft-
ware for quality control in diagnostic radiology and screening. She serves as president of the board and with her 
spouse has a 16% interest in the company. The value of their shares is estimated at less than 135 000 €. 

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Grace Callagy, National University of Ireland 
Galway, Ireland 

Ewa Chmielik, Maria Sklodowska-Curie Memorial Cancer Center 
Gliwice, Poland 

Alicia Cordoba, Hospital de Navarra 
Pamplona, Spain 

Gábor Cserni, University of Szeged, Szeged, Hungary & 
Bács-Kiskun County Teaching Hospital, Kecskemét, Hungary  

David R. Dance, Royal Surrey County Hospital 
Guildford, United Kingdom 

Peter B. Dean3, International Agency for Research on Cancer, Lyon, France &  
University of Turku, Turku, Finland  

Chris de Wolf4, Swiss Cancer Screening Federation 
Bern, Switzerland 

Thomas Decker, Dietrich Bonhoeffer Medical Center 
Neubrandenburg, Germany 

James DeGaetano, Mater dei Hospital 
Valletta, Malta 

Maria Drijkoningen, University Hospitals Leuven 
Leuven, Belgium 

Ian Ellis, University of Nottingham 
Nottingham, United Kingdom 

Daniel Faverly, CMP pathology laboratory and CCR Community Reference Center for cancer 
screening, Brussels, Belgium 

Maria Pia Foschini, University of Bologna 
Bologna, Italy 

3  P. B. Dean is employed part-time as a breast cancer screening radiologist for the Finnish national programme. 
4  C. de Wolf is a self-employed consultant to a non-profit organization working in the public interest (Swiss Cancer 
Screening Federation) and to various public entities in Switzerland (breast screening programmes in the cantons 
of  Bern,  Fribourg  and  Thurgau)  that  are  engaged  in  the  development,  implementation  and  evaluation  of 
population-based breast screening programmes. All income derived from these sources is paid to him through the 
Agency  for  Development  and  Evaluation  of  Health  Policy,  a  company  registered  in  Geneva,  Switzerland  with  a 
value of 20 000 CHF, of which he is the sole proprietor and employee. 

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Snjezana Frkovic-Grazio, University Medical Center Ljubljana 
Ljubljana, Slovenia 

Dorthe A. Grabau5, Skaane University Hospital 
Lund, Sweden 

Patrice Heid, Association ARCADES 
Marseille, France 

Paivi Heikkila, University of Helsinki and HUSLAB 
Helsinki, Finland 

Roland Holland, National Expert and Training Centre for Breast Cancer Screening 
Nijmegen, The Netherlands 

Efrosini Iacovou, Nicosia General Hospital 
Nicosia, Cyprus 

Jurgen Jacobs, Qaelum 
Leuven, Belgium 

Jocelyne Jacquemier, Association ARCADES 
Marseille, France 

Handan Kaya, Marmara University School of Medicine 
Istanbul, Turkey 

Janina Kulka, Semmelweis University 
Budapest, Hungary 

Manuela Lacerda, Instituto Português de Oncologia 
Coimbra, Portugal 

Barbara Lazzari, Azienda USL 3 
Pistoia, Italy 

Hans Lelivelt, National Expert and Training Centre For Breast Cancer Screening 
Nijmegen, The Netherlands 

Inta Liepniece-Karele, Riga Eastern Clinical University Hospital 
Riga, Latvia 

5  D. Grabau currently collaborates part-time with researchers at the University of Lund on studies of HER2 in breast 
cancer  patients  that  have  been  partially  financed  by  Roche.  The  total  funding  provided  by  Roche  to  Lund 
University for this research was less than 50 000 € and ended in 2010. 

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Elsebeth Lynge6, University of Copenhagen 
Copenhagen, Denmark 

Nicholas Marshall, University Hospital Leuven 
Leuven, Belgium 

Jose-Maria Martinez-Penuela, Hospital de Navarra 
Pamplona, Spain 

Nicholas Perry7, The London Breast Institute 
London, United Kingdom 

Maja Primic Zakelj, Institute of Oncology 
Ljubljana, Slovenia 

Cecily Quinn, St. Vincent's University Hospital 
Dublin, Ireland 

Fritz Rank, Copenhagen University Hospital 
Copenhagen, Denmark  

Peter Regitnig, Medical University of Graz 
Graz, Austria 

Angelika Reiner, Danube Hospital 
Vienna, Austria 

Anna Sapino, University of Torino 
Torino, Italy 

Stephan Schopphoven, Referenzzentrum Mammographie Südwest 
Marburg, Germany 

Nereo Segnan8, CPO Piemonte and City of Health and Science of Turin 
Turin, Italy 

Eero Suonio, International Agency for Research on Cancer 
Lyon, France 

6  E.  Lynge  is  undertaking  a  comparative  study  of  new-generation  HPV  tests,  involving  collaboration  with  Roche 
Diagnostics  A/S,  Genomica  S.A.U.,  Qiagen  Gaithersburg  Ltd.,  and  GenProbe  Inc.,  and  has  served  as  an  unpaid 
advisor GenProbe and Norchip. 

7  N.  Perry  is  employed  part-time  as  director  of  the  London  Breast  Institute  at  the  Princess  Grace  Hospital,  in 

London, UK, a privately owned and operated health care facility. 

8   N. Segnan has received consultancy fees of less than 1 500 € from Roche Diagnostics Ltd for his participation at 

an Advisory Board Meeting on CRC screening. 

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Martin Thijssen, National Expert and Training Centre For Breast Cancer Screening 
Nijmegen, The Netherlands 

Sven Törnberg, Karolinska University Hospital 
Stockholm, Sweden 

Tibor Tot, Central Hospital 
Falun, Sweden 

Johannes J.M. van Delden, Utrecht University 
Utrecht, The Netherlands 

Paul J. Van Diest, University Medical Center 
Utrecht, The Netherlands 

Ruben Van Engen, National Expert and Training Centre For Breast Cancer Screening 
Nijmegen, The Netherlands 

Chantal Van Ongeval, University Hospital Leuven 
Leuven, Belgium 

Zsuzsanna Varga, University Hospital Zurich 
Zurich, Switzerland 

Lawrence von Karsa, International Agency for Research on Cancer 
Lyon, France 

Clive Wells, University College London 
London, United Kingdom 

Jelle Wesseling, The Netherlands Cancer Institute 
Amsterdam, The Netherlands 

Kenneth C. Young, Royal Surrey County Hospital 
Guildford, United Kingdom 

Vassiliki Zolota, University of Patras 
Patras, Greece 

Enrique Zozaya-Alvarez, Hospital de Navarra 
Pamplona, Spain 

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Preface 

The  completion  of  the  Supplements  to  the  Fourth  Edition  of  the  European  Guidelines  for  quality 
assurance in breast cancer screening and diagnosis is a further milestone towards high quality cancer 
screening and diagnosis.   

Cancers  may  be  cured,  or  the  prospects  of  cure  greatly  increased,  if  they  are  detected  early.  Well 
organized,  nationwide  screening  programmes  therefore  have  a  huge  potential  to  reduce  cancer 
mortality. There have been considerable achievements in cancer screening, as a result of coordinated 
work  at  EU  level  to  support  Member  States  in  the  implementation  of  national  cancer  screening 
programmes.  

This publication is a good illustration of the role the EU can play to improve the health of its citizens. 
The  Supplements  to  the  Fourth  Edition  of  the  European  Guidelines  for  quality  assurance  in  breast 
cancer  screening  and  diagnosis  take  into  account  recent  developments  and  will  improve  quality 
assurance before the publication of the next edition. They will help to give women a better chance of 
receiving timely treatment as a result of early diagnosis of breast cancer. 

Cancer  has  been  a  priority  issue  for  EU  public  health  policy  for  more  than  25  years  and  will  remain 
high  on  the  European  agenda.  At  this  juncture,  I  would  like  to  thank  all  partners  and  contributors 
involved in this project for their valuable contribution to this publication which moves us an important 
step  further  down  the  road  towards  the  common  goal  to  improve  public  health  throughout  the 
European Union. 

John-F. Ryan 
Acting Director,  
Public Health, DG Health and Consumers, 
European Commission 
Brussels 

European guidelines for quality assurance in breast cancer screening and diagnosis  Fourth edition  Supplements 

IX 

 
 
FFOORREEWWOORRDD  

Foreword 

The  fourth  edition  of  the  European  guidelines  for  quality  assurance  in  breast  cancer  screening  and 
diagnosis was published by the European Commission in 2006. The present supplements to the fourth 
edition  have  been  produced  by  the  same  groups  of  experts  originally  established  under  the  Europe 
Against  Cancer  programme  that  have  developed  and  updated  the  guidelines  since  the  early  1990s. 
Over  the  years,  the  scope  and  the  depth  of  the  multidisciplinary  guidelines  have  expanded,  and 
recommendations  and  protocols  have  been  updated  to  keep  pace  with  developments  in  the  field. 
Many  of  the  experts  who  contributed  to  the  early  editions  of  the  guidelines  are  no  longer  active  or 
have moved on to other endeavours, and in presenting the current supplements we wish to thank and 
pay tribute to the dedication of all current and previous contributors. 

The  present  supplements  are  appearing  at a  time  of  transition.  The  European  Parliament  has  called 
for European Union (EU)-wide accreditation of breast centres to ensure that all women in the EU have 
access  to  high-quality  breast  services.  The  European  Commission  has  allocated  funding  to  develop 
and pilot a voluntary accreditation scheme and to prepare the new, fifth edition of the guidelines that 
will be needed for the accreditation project. The Joint Research Centre of the European Commission 
has been commissioned to coordinate these key efforts. 

The  present  supplements  lay  a  cornerstone  for  a  new,  completely  revised  fifth  edition  of  the 
guidelines.  Their availability should not delay the important efforts at the European level to produce 
the  fifth  edition.  The  editors  would  also  like  to  point  out  that  for  the  foreseeable  future  dedicated, 
sustainable support is also required for the pan-European exchange of experience and collaboration in 
training,  monitoring  and  evaluation,  and  other  areas  of  quality  assurance  initiated  in  the  European 
Breast  Cancer  Screening  Network  established  under  the  former  Europe  Against  Cancer  programme. 
Such collaborative efforts will be essential to ensure that in the future breast screening and diagnostic 
services fulfilling the European standards are available to all women in the EU. 

Nicholas Perry 
The London Breast Institute 
Princess Grace Hospital 
London 

Sven Törnberg 
Department of Cancer Screening 
Regional Cancer Centre 
Karolinska University Hospital l 
Stockholm 

Mireille Broeders 
National Expert and Training Centre For Breast 
Cancer Screening / EUREF Office 
Nijmegen 

Roland Holland 
National Expert and Training Centre for Breast 
Cancer Screening / EUREF Office 
Nijmegen 

Chris de Wolf 
Swiss Cancer Screening Federation 
Fribourg 

Lawrence von Karsa 
Quality Assurance Group 
Section of Early Detection and Prevention 
International Agency for Research on Cancer 
Lyon 

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European guidelines for quality assurance in breast cancer screening and diagnosis  Fourth edition  Supplements 

 
 
 
 
 
 
 
 
 
TTAABBLLEE  OOFF  CCOONNTTEENNTTSS  

Table of contents 

List of editors 

List of authors, contributors and editors 

Preface 

Foreword 

Executive summary 

S1  Digital mammography update 

European protocol for the quality control of the physical and       
technical aspects of mammography screening 

Introduction 

Part 1 

Acceptance and constancy testing 

  2b.1 

Introduction 

  2b.2 

Image acquisition 

  2b.3 

Image processing 

  2b.4 

Image presentation 

Appendix 5  

Tables for determination of average glandular dose 

Appendix 7  

Linear system theory metrics and a practical guide to  
their measurement (optional) 

Appendix 8  

Description of CDCOM version 1.6 

Appendix 9  

Significance of test items 

Part 2 

European type testing 

1 

2 

3 

Introduction 

Type testing procedure 

Type testing protocol 

III 

IV 

IX 

X 

XIII 

1 

3 

5 

11 

13 

28 

29 

34 

38 

45 

51 

55 

58 

58 

61 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
TTAABBLLEE  OOFF  CCOONNTTEENNTTSS  

S2  Pathology update 

Quality assurance guidelines for pathology 

1 

Introduction 

2  Columnar cell lesions and atypical ductal hyperplasia 

3  Acceptable use of frozen sections 

4  Classifying invasive carcinoma 

5  Assessing the axilla 

6  Microinvasive carcinoma 

7  Pathological reporting of post-chemotherapy specimens 

8  Vacuum-assisted needle core biopsy (VANCB) 

Annex 1:  Successful implementation of population-based cancer 

screening programmes 

1a  Stockholm statement on successful implementation of      

population-based cancer screening programmes 

1b  Determinants of successful implementation of population-based     

cancer screening programmes 

73 

79 

79 

86 

87 

97 

102 

105 

109 

121 

123 

129 

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European guidelines for quality assurance in breast cancer screening and diagnosis  Fourth edition  Supplements 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Executive summary 

Authors 
N. Perry 
M. Broeders 
C. de Wolf 
S. Törnberg 
R. Holland 
L. von Karsa 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
EEXXEECCUUTTIIVVEE  SSUUMMMMAARRYY  

Authors 
N. Perry, United Kingdom 
M. Broeders, The Netherlands 
C. de Wolf, Switzerland 
S. Törnberg, Sweden 
R. Holland, The Netherlands 
L. von Karsa, IARC 

Declarations of interest 
Interests of N. Perry and C. de Wolf are reported on pages VII and V respectively. 

Disclaimer 
The views expressed in this document are those of the authors and do not necessarily reflect the offi-
cial  position  of  the  European  Commission.  Neither  the  European  Commission  nor  any  other 
organization, nor any person acting alone or on behalf of others can be held responsible for any use 
that may be made of the information in this document. 

Acknowledgements 
Financial  support  was  provided  by  the  European  Union  Public  Health  Programme  (Project  no. 
2006322,  European  Cooperation  on  Development  and  Implementation  of  Cancer  Screening  and 
Prevention Guidelines [ECCG]). 

Please cite this publication as follows 
Perry N, Broeders M, de Wolf C, Törnberg S, Holland R, von Karsa L (2013). Executive summary. In: 
European guidelines for quality assurance in breast cancer screening and diagnosis. Fourth edition, 
Supplements. Perry N, Broeders M, de Wolf C, Törnberg S, Holland R, von Karsa L (eds.). European 
Commission, Office for Official Publications of the European Union, Luxembourg, pp. XIV–XX. 

Corresponding author 
L. von Karsa 
Quality Assurance Group 
Section of Early Detection and Prevention 
International Agency for Research on Cancer 
150 cours Albert Thomas 
F-69372 Lyon cedex 08 
France 
Karsal@iarc.fr 
QAS@iarc.fr 

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For  women  in  Europe,  breast  cancer  is  currently  the  most  common  cancer  and  the  most  common 
cause  of  cancer-induced  death.  According  to  the  most  recently  available  estimates  from  cancer 
registry  data,  more  than  330 000  new  cases  and  nearly  90 000  deaths  due  to  the  disease  were 
reported in the 27 Member States of the European Union (EU) in 2008 (Ferlay et al., 2010). Nine out 
of 10 of those deaths were in women aged 50 years or older, making breast cancer a leading cause of 
age-related  mortality  in  women.  As  pointed  out  in  the  fourth  edition  of  the  European  guidelines  for 
quality assurance in breast cancer screening and diagnosis, published in 2006 (Perry et al., 2006; see 
also  Perry  et  al.,  2008),  systematic  early  detection  through  screening,  effective  diagnostic  pathways 
and  optimal  treatment  can  significantly  lower  current  breast  cancer  mortality  rates  and  reduce  the 
burden  of  disease  in  the  population.  For  these  benefits  to  be  obtained,  high-quality  services  are 
essential.  These  may  be  achieved  through  the  underlying  basic  principles  of  training,  specialization, 
volume  levels,  multidisciplinary  teamwork,  the  use  of  set  targets  and  performance  indicators  and 
audit.  Ethically,  these  principles  should  be  regarded  as  applying  equally  to  symptomatic  diagnostic 
services and screening. 

Since the fourth edition was published, the importance of continued efforts at the European level to 
implement  and  improve  breast,  cervical  and  colorectal  cancer  screening  programmes  in  the  EU 
Member States has been confirmed by resolutions of the European Parliament (European Parliament, 
2006;  European  Parliament,  2008a;  European  Parliament,  2008b)  and  conclusions  of  the  Council  of 
the EU (Council of the European Union, 2008; Council of the European Union, 2010). A new European 
Partnership  for  Action  Against  Cancer  (www.epaac.eu)  has  been  established  by  the  European 
Commission,  and  a  third  set  of  comprehensive  European  quality  assurance  guidelines,  which  deals 
with  colorectal  cancer  screening,  has  been  developed  by  experts  and  published  by  the  European 
Commission (Segnan et al., 2010). These efforts underline the current consensus on the importance 
of continuously updating the comprehensive evidence-based standards and recommendations for best 
practice provided in the European guidelines. 

A  full  revision  of  the  European  guidelines  for  quality  assurance  in  breast  cancer  screening  and 
diagnosis is now under way, and the new, fifth edition is planned for publication in the coming years. 
In  the  meantime,  these  supplements  to  the  current,  fourth  edition  have  been  developed  to  address 
those  fields  that  the  editors  felt  warranted  an  update  of  the  standards,  protocols  and  best  practice 
recommendations.  At  a  meeting  of  the  editorial  board  in  November  2009  in  London,  it  was  agreed 
that the supplements would be prepared by the same groups of experts engaged in the development 
of  the  fourth  edition  and  according  to  the  same  methodology.  The  authors  and  editors  welcome 
comments and feedback on these documents. 

Digital mammography update 

The first supplement (Digital mammography update) responds to the rapid technological development 
that has accompanied a wide increase in the use of  digital imaging in mammography screening and 
diagnosis  since the  fourth  edition was published. It has been prepared largely by the experts in the 
European  Reference  Organisation  for  Quality  Assured  Breast  Screening  and  Diagnostic  Services 
(EUREF) Physico-Technical  Steering Group, who have  been recruited from European medical physics 
quality assurance teams experienced in guideline development and in implementation of population-
based  mammography  screening  programmes.  Part  1  of  the  first  supplement  (Acceptance  and 
constancy testing; van Engen et al., 2013a) updates the digital mammography part of the European 
protocol for the quality control of the physical and technical aspects of mammography screening (van 
Engen  et  al.,  2006)  in  the  fourth  edition  (Perry  et  al.,  2006).  The  authors  indicate  the  changes 
compared  with  the  version  of  the  digital  mammography  protocol  in  the  fourth  edition,  and  in  some 
sections further guidance and clarification is provided. It is therefore essential to consult the original 
text and the supplement together. 

Only a few aspects of the updates to the digital mammography protocol can be highlighted here. Of 
prime  importance  are  the  changes  to  the  system  requirements  that  any  mammography  equipment 
must  fulfil.  They  include,  in  addition  to  other  elements,  a  fully  automatic  exposure  control  (AEC).  A 

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EEXXEECCUUTTIIVVEE  SSUUMMMMAARRYY  

system  with  solely  manual  exposure  control  (in  which  the  user  has  to  define  anode  material,  filter, 
tube voltage and dose) is not acceptable; neither is a system with semi-automated exposure control 
(that  adapts  dose  according  to  breast  transparency,  but  still  requires  the  user  to  define  anode 
material,  filter  and  tube  voltage).  For  quality  control  purposes  it  should  be  possible  to  output 
unprocessed images in DICOM format from the acquisition workstation or computed radiography (CR) 
reader. 

Part 2 of the first supplement (European type testing; van Engen et al., 2013b) adds a new dimension 
to  the  quality  assurance  philosophy  anchored  in  the  fourth  edition,  namely  type  testing  of  digital 
imaging systems. The need for a European type testing protocol based on the most recent version of 
the European guidelines became apparent during the preparation of the digital mammography update 
dealing with acceptance and constancy testing. Equipment users and manufacturers pointed out that 
an  additional  European  protocol  would  facilitate  avoidance  of  potential  quality  problems  before 
equipment is delivered to  users.  The editorial board  of the fourth edition of the guidelines therefore 
requested that the experts in the EUREF Physico-Technical Steering Group also develop a procedure 
and protocol suitable for standardizing type testing for mammography systems at the European level. 

The  standards  and  procedures  presented  in  Part  2  of  the  first  supplement  take  into  account  the 
updates  to  the  digital  mammography  physico-technical  protocol  that  are  reported  in  Part  1.  The 
European  type  testing  protocol  currently  aims  to  verify  whether  imaging  systems  of  a  given  type  or 
brand are fundamentally capable of fulfilling the acceptance criteria of the European physico-technical 
protocol. Furthermore, guidelines are provided on best practice in controlling dose and (clinical) image 
quality.  After  a  successful  type  test,  individual  mammography  units  of  the  same  type  or  brand  still 
need to undergo an acceptance test before clinical use. Passing the type test merely guarantees that 
the  system  is  in  principle  capable  of  meeting  the  requirements  of  the  European  physico-technical 
protocol; the type test report may also provide suggestions for optimal use, or may specify conditions 
to be avoided in practice. 

The  chapter  on  the  physico-technical  aspects  of  quality  control  in  the  fourth  edition  was  originally 
developed for acceptance and constancy testing and not for type testing. Therefore, some differences 
exist between Part 1 and Part 2 of the first supplement; these differences are reported in Part 2 of the 
supplement.  The  new  European  protocol  for  type  testing  (Part  2)  has  been  developed  for  digital 
mammography  (direct  radiography  and  computed  radiography)  systems.  In  the  future,  the  protocol 
may  be  expanded  to  include  type  testing  of  image-processing  algorithms,  workstations  and  film 
digitizers. 

The  preparation  of  the  new  and  revised  standards,  protocols  and  recommendations  in  the  first 
supplement was coordinated by the EUREF office based at the National Expert and Training Centre for 
Breast  Cancer  Screening  in  Nijmegen,  The  Netherlands.  It  involved  extensive  planning,  empirical 
measurements and numerous  scientific studies in the work  package  on digital  mammography in the 
project  ‘European  Cooperation  on  Development  and  Implementation  of  Cancer  Screening  and 
Prevention  Guidelines (ECCG)’, in which  key quality assurance centres in Belgium, France,  Germany, 
Italy, The Netherlands and the United Kingdom collaborated. Experience in the practical application of 
the new and further developed standards was gathered in site visits and training courses attended by 
medical  physicists  and  technicians  from  several  EU  Member  States,  including  those  that  acceded  to 
the EU in 2004 and 2007. This experience fed into the final formulation of the digital mammography 
supplements. The highly effective professional and scientific cooperation in the project was facilitated 
by the collaborative platform provided by participation of most of the authors in the EUREF Physico-
Technical Steering Group. 

Pathology update 

The second supplement (Pathology update; Wells et al., 2013) deals with several topics in the quality 
assurance  of  pathology  in  breast  cancer  screening  and  diagnosis  in  which  problems  and  practical 
solutions as well as new techniques and other advances have emerged in recent years. The authors 

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EEXXEECCUUTTIIVVEE  SSUUMMMMAARRYY  

felt that these topics warranted urgent attention pending a full revision of the pathology chapter. They 
include  the  classification  of  early  forms  of  neoplastic  changes  in  the  breast  and  the  differential 
diagnosis  of  columnar  cell  lesions  (CCLs),  atypical  ductal  hyperplasia  (ADH)  and  ductal  carcinoma  in 
situ (DCIS). Other sections provide an update on the classification of invasive carcinoma and on the 
diagnosis  and  differential  diagnosis  of  microinvasive  carcinoma.  Special  attention  is  paid  to  the 
assessment  of  the  axilla,  and  the  updated  guidance  on  axillary  dissection  and  preoperative  staging 
takes into account problems and pitfalls as well as the most recent revision of the TNM system (Sobin 
et al., 2009). The supplement also includes comprehensive practical recommendations on examination 
techniques  and  interpretation  of  sentinel  node  biopsy  specimens.  Best  practice  in  the  use  of  frozen 
sections,  an  update  on  vacuum-assisted  needle  core  biopsy  (VANCB)  and  recommendations  on 
pathological reporting of post-chemotherapy specimens are also provided. 

The  supplement  with  updates  on  pathology  has  been  prepared  by  the  European  Working  Group  on 
Breast Screening Pathology, which also prepared the chapter on pathology in the fourth edition (Wells 
et al., 2006) and in previous editions of the guidelines. The group consists of 38 breast pathologists in 
23  EU  Member  States,  Switzerland  and  Turkey  and  has  been  led  by  the  editor  of  the  chapter  on 
pathology  in  the  guidelines.  All  of  the  pathologists  in  the  group  are  leaders  in  the  field  of  breast 
pathology in their countries. The recommendations in the supplement have been drafted by selected 
members  of  the  group  and  have  been  discussed  and  agreed  upon  at  twice-yearly  meetings  held  in 
Hungary,  Switzerland,  Italy,  France,  The  Netherlands  and  Finland  since  the  fourth  edition  was 
published. 

Implementation of population-based cancer screening programmes 

In  Annex  1,  the  supplements  volume  also  includes  recommendations  on  implementation  of 
population-based cancer screening programmes that are relevant not only to breast cancer screening 
but  also  to  cervical  and  colorectal  cancer  screening.  The  Annex  consists  of  a  brief  statement  (von 
Karsa  et  al.,  2013)  and  a  longer  article  (Lynge  et  al.,  2012)  summarizing  the  results  of  a  pan-
European  workshop  organized  by  the  European  Science  Advisory  Network  for  Health  (EuSANH, 
www.EuSANH.eu)  in  Stockholm  in  February  2011.  At  the  meeting,  a  multidisciplinary  group  of 
scientists and professionals experienced in implementation and quality assurance of cancer screening 
programmes and in development of scientific advice on health policy reviewed the available evidence. 
The conclusions and comprehensive recommendations that emerged identify the major determinants 
of successful implementation of population-based cancer screening programmes. 

The  authors  emphasize  that  any  policy  decision  in  Europe  to  implement  a  cancer  screening 
programme  should  take  into  account  EU  recommendations  and  guidelines  based  on  the  available 
evidence  and  the  experience  in  Europe  in  implementing  population-based  cancer  screening 
programmes.  Key  references  in  this  regard  are  the  Recommendation  on  Cancer  Screening  of  2 
December  2003  of  the  Council  of  the  EU  (Council  of  the  European  Union,  2003),  the  European 
guidelines for quality assurance in breast, cervical and colorectal cancer screening (Perry et al., 2006; 
Arbyn et al., 2008; Segnan et al., 2010; see also Perry et al., 2008 and Arbyn et al., 2010) and recent 
reports dealing with the implementation of cancer screening programmes in the EU (von Karsa et al., 
2008; Commission of the European Communities, 2008; Anttila et al., 2009). 

The  experience  in  Europe  shows  that  quality-assured  implementation  of  population-based  cancer 
screening programmes generally involves a very long process, extending over 10 or more years and 
beginning with planning followed by feasibility testing, piloting and gradual rollout of the programme 
across  a  country.  Successful  completion  of  the  quality-assured  process  requires  engagement  of  civil 
society, including societal debate; effective cancer registration; good governance providing long-term 
political  commitment;  adequate  and  sustainable  resources  and  competent  oversight;  autonomous 
programme  management  with  coordination  of  numerous  stakeholders  and  activities;  organizational 
development  and  control  of  resources  (dedicated  budget  and  staff);  as  well  as  international 
collaboration in quality assurance. In a fully established programme, the proportion of the expenditure 

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devoted  to  quality  assurance  should  be  no  less  than  10–20%,  depending  on  the  scale  of  the 
programme. This investment is cost-effective and will save lives. 

Computerized  information  systems  and  accessible  registries  are  necessary  for  the  management  of 
effective and efficient screening services (e.g. for call and re-call systems and fail-safe procedures in 
follow-up  of  participants  with  abnormal  test  results).  They  are  also  needed  to  monitor  and  evaluate 
the performance and the outcome of the screening programme, e.g. through linkage of individual data 
on cancer occurrence and morbidity, screening history, diagnosis and treatment. 

Once  the  political  decision  has  been  taken  to  establish  a  population-based  cancer  screening 
programme, a competent programme coordinator should receive the mandate to manage and thereby 
adequately assure quality throughout the process of programme implementation. This is necessary to 
fulfil  the  European  principles  and  guidelines  and  relevant  national  standards  and  regulations.  The 
coordinator  should  be  provided  with  sufficient  organizational  and  financial  resources  to  effectively 
manage the screening programme and take further decisions as necessary. 

The  same  conclusions  apply  to  efforts  at  the  European  level  to  support  the  EU  Member  States  in 
implementing  the  Council  Recommendation  on  cancer  screening.  Their  success  in  making  evidence-
based  screening  programmes  recommended  by  the  EU  available  to  all  citizens  who  may  benefit  will 
depend  on  the  availability  of  comprehensive,  evidence-based  guidelines  that  are  updated 
continuously.  Successful  implementation  of  the  guidelines  across  the  EU  will  likewise  require 
engagement  of  civil  society  and  the  availability  of  an  autonomous  coordination  under  competent 
oversight, with adequate, sustainable resources and long-term political support. 

References 

Anttila  A,  Ronco  G,  Working  Group  on  the  Registration  and  Monitoring  of  Cervical  Cancer  Screening 
Programmes  in  the  European  Union;  within  the  European  Network  for  Information  on  Cancer 
(EUNICE)  (2009).  Description  of  the  national  situation  of  cervical  cancer  screening  in  the  member 
states of the European Union. Eur. J. Cancer, 45:2685–2708. 
http://www.ejcancer.info/article/S0959-8049(09)00576-0/abstract 

Arbyn  M,  Anttila  A,  Jordan  J,  Ronco  G,  Schenck  U,  Segnan  N,  Wiener  H,  Herbert  A,  von  Karsa  L 
(2010).  European  guidelines  for  quality  assurance  in  cervical  cancer  screening,  second  edition  – 
summary document. Ann. Oncol., 21:448–458. 

Arbyn M, Anttila A, Jordan J, Schenck U, Ronco G, Segnan N, Wiener H, Herbert A, Daniel J, von Karsa 
L  (eds.)  (2008).  European guidelines for quality assurance in cervical cancer screening. Second 
edition.  European  Commission,  Office  for  Official  Publications  of  the  European  Communities, 
Luxembourg. 
http://bookshop.europa.eu/is-bin/INTERSHOP.enfinity/WFS/EU-Bookshop-Site/en_GB/-
/EUR/ViewPublication-Start?PublicationKey=ND7007117 

Commission  of  the  European  Communities  (2008).  Report  from  the  Commission  to  the  Council,  the 
European  Parliament,  the  European  Economic  and  Social  committee  and  the  Committee  of  the 
Regions – Implementation of the Council Recommendation of 2 December 2003 on cancer screening 
(2003/878/EC) Brussels, Report no. COM(2008) 882 final. 
http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2008:0882:FIN:EN:PDF 

Council  of  the  European  Union  (2003).  Council  Recommendation  of  2  December  2003  on  cancer 
screening (2003/878/EC). Off. J. Eur. Union L 327:34–38. 
http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2003:327:0034:0038:EN:PDF 

Council of the European Union (2008). Council Conclusions on reducing the burden of cancer. 2876th 
Employment, Social Policy, Health and Consumer Affairs Council meeting. Luxembourg, 10 June 2008. 

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Brussels,  Belgium,  Press  Office  of  the  Council  of  the  European  Union.  10414/08  (Presse  166), 
http://www.consilium.europa.eu/ueDocs/cms_Data/docs/pressData/en/lsa/101031.pdf 

Council of the European Union (2010). Council Conclusions on Action Against Cancer, 3032nd Council 
meeting.  General  affairs.  Press  release  236,  13420/1/10  REV  1,  Brussels,  Belgium,  13  September 
2010, Press Office of the Council of the European Union. 
http://www.consilium.europa.eu/press/press-releases/latest-press-
releases/newsroomrelated?lang=en&bid=72&grp=17287&id=1851 

European  Parliament  (2006).  European  Parliament  Resolution  on  Breast  Cancer  in  the  Enlarged 
European Union. P6_TA(2006)0449. 

European Parliament (2008a). European Parliament resolution of 10 April on combating cancer in the 
enlarged European Union. P6_TA-PROV(2008)0121. 

European  Parliament  (2008b).  European  Parliament  resolution  of  9  October  2008  on  ‘Together  for 
Health: A Strategic Approach for the EU 2008-2013’. P6_TA(2008)0477. 

Ferlay  J,  Shin  HR,  Bray  F,  Forman  D,  Mathers  C,  Parkin  DM  (2010).  GLOBOCAN  2008,  Cancer 
Incidence  and  Mortality  Worldwide:  IARC  CancerBase  No.  10  [Internet]  International  Agency  for 
Research on Cancer, Lyon, France. http://globocan.iarc.fr/ 

Lynge  E,  Törnberg  S,  von  Karsa  L,  Segnan  N,  van  Delden  JJM  (2012).  Determinants  of  successful 
implementation of population-based cancer screening programmes. Eur. J. Cancer, 48:743–748. 

Perry N, Broeders M, de Wolf C, Törnberg S, Holland R, von Karsa L (2008). European guidelines for 
quality assurance in breast cancer screening and diagnosis, Fourth edition – Summary document. Ann 
Oncol., 19:614–622. 

Perry  N,  Broeders  M,  de  Wolf  C,  Törnberg  S,  Holland  R,  von  Karsa  L,  Puthaar  E  (eds.)  (2006). 
European guidelines for quality assurance in breast cancer screening and diagnosis. Fourth edition. 
European Commission, Office for Official Publications of the European Communities, Luxembourg. 

Segnan N, Patnick J, von Karsa L (eds.) (2010). European guidelines for quality assurance in colorectal 
cancer screening and diagnosis. First edition. European Commission, Office for Official Publications of 
the European Union, Luxembourg. 

Sobin LH, Gospodarowicz MK, Wittekind C (eds.) (2009). TNM Classification of Malignant Tumours, 7th 
edition. Wiley-Blackwell. 

van  Engen  RE,  Bosmans  H,  Dance  DR,  Heid  P,  Lazzari  B,  Marshall  N,  Schopphoven  S,  Thijssen  M, 
Young  KC  (2013a).  Digital  mammography  update.  European  protocol  for  the  quality  control  of  the 
physical  and  technical  aspects  of  mammography  screening.  S1,  Part  1:  Acceptance  and  constancy 
testing. In: European guidelines for quality assurance in breast cancer screening and diagnosis. Fourth 
edition, Supplements.  Perry  N,  Broeders  M,  de  Wolf  C,  Törnberg  S,  Holland  R,  von  Karsa  L  (eds.). 
European Commission, Office for Official Publications of the European Union, Luxembourg, pp. 1–54. 

van Engen RE, Bosmans H, Heid P, Lazzari B, Schopphoven S, Thijssen M, Young KC (2013b). Digital 
mammography update. European protocol for the quality control of the physical and technical aspects 
of  mammography  screening.  S1,  Part  2:  European  type  testing.  In: European guidelines for quality 
assurance in breast cancer screening and diagnosis. Fourth edition, Supplements.  Perry  N,  Broeders 
M,  de  Wolf  C,  Törnberg  S,  Holland  R,  von  Karsa  L  (eds.).  European  Commission,  Office  for  Official 
Publications of the European Union, Luxembourg, pp. 55–71. 

van Engen RE, Young KC, Bosmans H, Thijssen M (2006). European protocol for the quality control of 
the  physical  and  technical  aspects  of  mammography  screening.  Chapter  2b:  Digital  mammography. 
In: European guidelines for quality assurance in breast cancer screening and diagnosis. Fourth edition. 
Perry  N,  Broeders  M,  de  Wolf  C,  Törnberg  S,  Holland  R,  von  Karsa  L  (eds.).  European  Commission, 
Office for Official Publications of the European Communities, Luxembourg, pp. 105–165. 

von Karsa L, Anttila A, Primic Žakelj M, de Wolf C, Bielska-Lasota  M,  Törnberg  S, Segnan N (2013). 
implementation  of  population-based  cancer  screening 
Stockholm  statement  on  successful 

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programmes. Annex 1a. In: European guidelines for quality assurance in breast cancer screening and 
diagnosis. Fourth edition, Supplements. Perry N, Broeders M, de Wolf C, Törnberg S, Holland R, von 
Karsa  L  (eds.).  European  Commission,  Office  for  Official  Publications  of  the  European  Union, 
Luxembourg, pp. 123–128. 

von Karsa L, Anttila A, Ronco G, Ponti A, Malila N, Arbyn M, Segnan N, Castillo-Beltran M, Boniol M, 
Ferlay J, Hery C, Sauvaget C, Voti L, Autier P (2008). Cancer screening in the European Union, Report 
on the implementation of the Council Recommendation on cancer screening – First Report. European 
Commission, Office for Official Publications of the European Communities, Luxembourg.  
http://ec.europa.eu/health/ph_determinants/genetics/documents/cancer_screening.pdf 

Wells  CA,  Amendoeira  I,  Apostolikas  N,  Bellocq  JP,  Bianchi  S,  Boecker  W,  Borisch  B,  Bussolati  G, 
Connolly CE, Cserni G, Decker T, Dervan P, Drijkoningen M, Ellis IO, Elston CW, Eusebi V, Faverly DR, 
Heikkilä P, Holland R, Kerner H, Kulka J, Jacquemier J, Lacerda M, Martinez-Penuela J, de Miguel C,  
Nordgren  H,  Peterse  JL,  Rank  F,  Regitnig  P,  Reiner  A,  Sapino  A,  Sigal-Zafrani  B,  Tanous  AM, 
Thorstenson S, Zozaya E (2006). Chapter 6: Quality assurance guidelines for pathology. In: European 
guidelines for quality assurance in breast cancer screening and diagnosis. Fourth edition.  Perry  N, 
Broeders M, de Wolf C, Törnberg S, Holland R, von Karsa L (eds.). European Commission, Office for 
Official Publications of the European Union, Luxembourg, pp. 219–311. 

Wells CA, Amendoeira I, Bellocq JP, Bianchi S, Boecker W, Borisch B, Bruun Rasmussen B, Callagy GM, 
Chmielik E, Cordoba A, Cserni G, Decker T, DeGaetano J, Drijkoningen M, Ellis IO, Faverly DR, 
Foschini MP, Frković-Grazio S, Grabau D, Heikkilä P, Iacovou E, Jacquemier J, Kaya H, Kulka J, 
Lacerda M, Liepniece-Karele I, Martinez-Penuela J, Quinn CM, Rank F, Regitnig P, Reiner A, Sapino A, 
Tot T, Van Diest PJ, Varga Z, Wesseling J, Zolota V, Zozaya-Alvarez E (2013). S2: Pathology update. 
Quality assurance guidelines for pathology. In: European guidelines for quality assurance in breast 
cancer screening and diagnosis. Fourth edition, Supplements. Perry N, Broeders M, de Wolf C, 
Törnberg S, Holland R, von Karsa L (eds.). European Commission, Office for Official Publications of the 
European Union, Luxembourg, pp. 73–120. 

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European guidelines for 
quality assurance in 
breast cancer screening 
and diagnosis 

Fourth Edition 

Supplement 

Part 1 

Acceptance and constancy testing 

Part 2 

European type testing 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2 

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SSUUPPPPLLEEMMEENNTT  11  ––  DDIIGGIITTAALL  MMAAMMMMOOGGRRAAPPHHYY  UUPPDDAATTEE  

Introduction 

The aim of the European Reference Organisation for Quality Assured Breast Screening and Diagnostic 
Services (EUREF) is to improve the quality of mammography in Europe and to disseminate knowledge 
on high-quality breast imaging. Within this context, EUREF has produced the European guidelines for 
quality assurance in breast cancer screening and diagnosis (Perry et al., 2001; de Wolf & Perry, 1996). 
The current version of these guidelines is the fourth edition, published by the European Commission in 
2006 (Perry et al., 2006). It includes in Chapter 2 the European protocol for the quality control of the 
physical  and  technical  aspects  of  mammography  screening,  an  internationally  recognized  standard 
that is widely used in Europe and worldwide (van Engen et al., 2006a; van Engen et al., 2006b). In 
Part 2b of this protocol, the requirements for digital mammography imaging systems are defined and 
standards  and  protocols  relevant  to  acceptance  and  constancy  testing  of  equipment  are  described 
(van Engen et al., 2006b). Due to the rapid developments in imaging technology in recent years and 
further experience with digital mammography systems, some updating and extension of the scope of 
the protocol is warranted and is supplied here in the form of a supplement (S1: Digital mammography 
update). 

Part 1  of  the  supplement  (Acceptance  and  constancy  testing;  van  Engen  et  al.,  2013a)  deals  with 
relevant  aspects  of  acceptance  and  constancy  testing  of  digital  mammography  equipment  that  are 
addressed  in  Chapter 2b  in  the  fourth  edition.  During  the  preparation  of  these  aspects,  equipment 
users and manufacturers expressed the need for type testing of digital imaging equipment based on 
the fourth edition. The availability of an additional protocol for type testing enables manufacturers to 
avoid potential quality problems before equipment is delivered to the user. The editorial board of the 
fourth  edition  therefore  requested  that  the  experts  in  the  EUREF  Physico-Technical  Steering  Group 
also  develop  a  procedure  and  protocol  suitable  for  standardizing  type  testing  for  mammography 
systems  at  the  European  level.  The  developed  standards  are  presented  in  Part 2  of  the  supplement 
(European  type  testing;  van  Engen  et  al.,  2013b);  they  take  into  account  the  updates  presented  in 
Part 1 of the supplement. 

The type testing described in Part 2 of this supplement aims to verify whether imaging systems of a 
given  type  or  brand  are  fundamentally  capable  of  fulfilling  the  acceptance  criteria  of  the  European 
physico-technical protocol, and to provide guidelines for best practice in controlling dose and (clinical) 
image quality. After a successful type test, individual mammography units of the same type or brand 
still need to undergo an acceptance test before clinical use. Passing the type test merely guarantees 
that the system is in principle capable of meeting the requirements of the European physico-technical 
protocol; the type test report may also provide suggestions for optimal use or specify conditions to be 
avoided in practice. 

The  European  protocol  for  type  testing  is  currently  developed  for  digital  mammography  (direct 
radiography  [DR]  and  computed  radiography  [CR])  systems.  In  the  future,  the  protocol  may  be 
expanded to include type testing of image processing algorithms, workstations and film digitizers. 

This  supplement  has  been  prepared  by  the  experts  in  the  EUREF  Physico-Technical  Steering  Group 
who  have  been  recruited  from  European  medical  physics  quality  assurance  teams  experienced  in 
guideline  development  and  in  implementation  of  population-based  mammography  screening 
programmes.  The  authors  welcome  all  comments  and  feedback  on  this  document  to  improve  the 
standards and protocols. Future updates of the current version will be made available on the web sites 
of the European Commission (http://ec.europa.eu/health/index_en.htm) and EUREF (www.euref.org). 

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References 

de  Wolf  C,  Perry  N  (1996). European guidelines for quality assurance in mammography screening. 
Second edition.  European  Commission,  Office  for  Official  Publications  of  the  European  Communities, 
Luxembourg. 

Perry  N,  Broeders  M,  de  Wolf  C,  Törnberg  S,  Holland  R,  von  Karsa  L  (eds.)  (2006).  European 
guidelines for quality assurance in breast cancer screening and diagnosis. Fourth edition.  European 
Commission, Office for Official Publications of the European Communities, Luxembourg. 

Perry N, Broeders M, de Wolf C, Törnberg S, Schouten J (eds.) (2001). European guidelines for quality 
assurance in mammography screening. Third edition.  European  Commission,  Office  for  Official 
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van  Engen  RE,  Bosmans  H,  Dance  DR,  Heid  P,  Lazzari  B,  Marshall  N,  Schopphoven  S,  Thijssen  M, 
Young  KC  (2013a).  Digital  mammography  update.  European  protocol  for  the  quality  control  of  the 
physical  and  technical  aspects  of  mammography  screening.  S1,  Part  1:  Acceptance  and  constancy 
testing. In: European guidelines for quality assurance in breast cancer screening and diagnosis. Fourth 
edition, Supplements.  Perry  N,  Broeders  M,  de  Wolf  C,  Törnberg  S,  Holland  R,  von  Karsa  L  (eds.). 
European Commission, Office for Official Publications of the European Union, Luxembourg, pp. 1–54. 

van Engen RE, Bosmans H, Heid P, Lazzari B, Schopphoven S, Thijssen M, Young KC (2013b). Digital 
mammography update. European protocol for the quality control of the physical and technical aspects 
of  mammography  screening.  S1,  Part  2:  European  type  testing.  In: European guidelines for quality 
assurance in breast cancer screening and diagnosis. Fourth edition, Supplements.  Perry  N,  Broeders 
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Publications of the European Union, Luxembourg, pp 55–71. 

van Engen RE, van Woudenberg S, Bosmans H, Young KC, Thijssen M (2006a). European protocol for 
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(eds.).  European  Commission,  Office  for  Official  Publications  of  the  European  Communities, 
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van Engen RE, Young KC, Bosmans H, Thijssen M (2006b). European protocol for the quality control 
of the physical and technical aspects of mammography screening. Chapter 2b: Digital mammography. 
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Perry  N,  Broeders  M,  de  Wolf  C,  Törnberg  S,  Holland  R,  von  Karsa  L  (eds.).  European  Commission, 
Office for Official Publications of the European Communities, Luxembourg, pp. 105–165. 

Corresponding author 
R. van Engen 
EUREF office 
National Expert and Training Centre for Breast Cancer Screening 
Radboud University Nijmegen Medical Centre 
P.O. Box 6873 
6503 GJ Nijmegen 
The Netherlands 
R.vanEngen@euref.org 
info@euref.org 

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European guidelines for quality assurance in breast cancer screening and diagnosis  Fourth edition  Supplements 

 
 
 
 
 
 
 
European guidelines for 
quality assurance in 
breast cancer screening 
and diagnosis 

Fourth Edition 

Supplement 

Part 1 

Acceptance and constancy testing 

Authors 
R. van Engen 
H. Bosmans 
D. Dance 
P. Heid 
B. Lazzari 
N. Marshall 
S. Schopphoven 
M. Thijssen 
K. Young 

 
 
 
 
 
 
 
 
 
 
 
 
 
Authors 
R. van Engen, The Netherlands* 
H. Bosmans, Belgium* 
D. Dance, United Kingdom 
P. Heid, France* 
B. Lazzari, Italy* 
N. Marshall, Belgium 
S. Schopphoven, Germany* 
M. Thijssen, The Netherlands* 
K. Young, United Kingdom* 

* Member of the EUREF Physico-Technical Steering Group 

Declarations of interest 
An interest of H. Bosmans is reported on page IV. 

Disclaimer 
The views expressed in this document are those of the authors and do not necessarily reflect the offi-
cial  position  of  the  European  Commission.  Neither  the  European  Commission  nor  any  other 
organization  or  any  individual  may  be  held  responsible  for  any  use  that  may  be  made  of  the 
information contained herein. 

Acknowledgements 
Financial  support  was  provided  by  the  European  Union  Public  Health  Programme  (Project  no. 
2006322,  European  Cooperation  on  Development  and  Implementation  of  Cancer  Screening  and 
Prevention Guidelines [ECCG]). 

The comments and suggestions received from numerous colleagues in the European Cancer Network 
for  Screening  and  Prevention  and  the  European  Federation  of  Organisations  for  Medical  Physics 
(EFOMP) are gratefully acknowledged. 

The comments and suggestions received from the following companies are gratefully acknowledged: 
Adani,  Agfa  HealthCare,  Barco,  Carestream  Health,  Eizo,  General  Electric,  Hologic,  Konica  Minolta, 
Philips Healthcare, Planmed, Sectra and Siemens. 

Please cite this publication as follows 
van  Engen  RE,  Bosmans  H,  Dance  DR,  Heid  P,  Lazzari  B,  Marshall  N,  Schopphoven  S,  Thijssen  M, 
Young  KC  (2013).  Digital  mammography  update.  European  protocol  for  the  quality  control  of  the 
physical  and  technical  aspects  of  mammography  screening.  S1,  Part  1:  Acceptance  and  constancy 
testing. In: European guidelines for quality assurance in breast cancer screening and diagnosis. Fourth 
edition, Supplements.  Perry  N,  Broeders  M,  de  Wolf  C,  Törnberg  S,  Holland  R,  von  Karsa  L  (eds.). 
European Commission, Office for Official Publications of the European Union, Luxembourg, pp. 1–54. 

Corresponding author 
R. van Engen 
EUREF office 
National Expert and Training Centre for Breast Cancer Screening 
Radboud University Nijmegen Medical Centre 
P.O. Box 6873 
6503 GJ Nijmegen 
The Netherlands 
R.vanEngen@euref.org 
info@euref.org

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Table of contents 

This supplement contains updates of the following sections and appendices in Part 2b: Digital 
mammography in the European protocol for the quality control of the physical and technical aspects of 
mammography  screening  (van  Engen  et  al.,  2006b)  originally  published  in  the  fourth  edition  of  the 
European  guidelines  for  quality  assurance  in  breast  cancer  screening  and  diagnosis.  It  is  therefore 
essential to consult the original text and the supplement together. 

2b.1 

2b.1.2 

2b.1.5 

2b.2 

Introduction 

System requirements 

Definition of terms 

Image acquisition 

2b.2.1.1.1 

Focal spot size 

2b.2.1.1.2 

Source-to-image distance 

2b.2.1.1.3 

Alignment of X-ray field/image area 

2b.2.1.1.4 

Radiation leakage 

2b.2.1.1.5 

Tube output 

2b.2.1.2.2 

Half value layer 

2b.2.1.3.1 

Exposure control steps 

2b.2.1.3.3 

Short-term reproducibility 

2b.2.1.3.5 

Breast thickness and composition compensation 

2b.2.1.3.6 

Local dense area (only DR systems) 

2b.2.1.5 

Antiscatter grid 

2b.2.1.5.1 

Grid system factor 

2b.2.1.5.2 

Grid imaging 

2b.2.2.1.2 

Noise evaluation 

2b.2.2.3.1 

Image receptor homogeneity 

2b.2.2.3.2 

Detector element failure (DR systems) 

2b.2.2.4 

2b.2.2.5 

2b.2.2.6 

2b.2.3 

2b.2.3.1 

2b.2.3.2 

2b.2.4.1 

2b.2.4.2 

2b.2.4.3 

2b.2.4.4 

Interplate sensitivity variations and plate uniformity (CR systems) 

Influence of other sources of radiation 

Fading of latent image (CR systems) 

Dosimetry 

Dose to typical breasts simulated with PMMA 

Clinical breast doses 

Threshold contrast visibility 

Modulation transfer function (MTF) and noise power spectrum (NPS) 

Exposure time 

Geometrical distortion and artefact evaluation 

11 

11 

12 

13 

13 

13 

13 

13 

13 

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15 

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2b.3 

2b.4 

Image processing 

Image presentation 

2b.4.1 

Monitors 

2b.4.1.1 

Ambient light 

2b.4.1.2–5  

Constancy tests of monitor performance 

2b.4.1.8 

Luminance uniformity 

2b.4.2 

Printers 

2b.4.2.5 

Optical density range 

2b.4.3 

Viewing boxes 

2b.4.3.1 

Ambient lighting level 

28 

29 

29 

29 

30 

31 

33 

33 

33 

33 

Appendix 5:   Tables for determination of average glandular dose 

34 

Appendix 7:   Linear system theory metrics and a practical guide to  

their measurement (optional) 

A7.1 

A7.2 

A7.3 

A7.4 

A7.5 

A7.6 

A7.7 

Modulation transfer function (MTF), noise power spectrum (NPS) 
and detective quantum efficiency (DQE) 

Image type 

Collimation of X-ray field 

Detector response function 

Noise power spectrum 

Pre-sampled modulation transfer function 

Detective quantum efficiency (DQE) 

Appendix 8:   Description of CDCOM version 1.6 

A8.1 

A8.2 

A8.3 

A8.4 

A8.5 

A8.6 

A8.7 

A8.8 

The CDMAM phantom 

Disadvantages of human readout of the CDMAM phantom 

CDCOM 

Analysis of the DICOM header 

Transformation to a standardized input 

Grid detection 

Phantom-specific and image-specific corrections 

Individual disc detection 

Appendix 9:   Significance of test items 

References 

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38 

38 

38 

39 

40 

41 

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45 

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47 

47 

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List of figures 

Figure 1.1 

Set-up for the breast thickness and composition measurements, top view and 3D view 

16 

Figure 1.2 

Set-up for the breast thickness and composition measurements, front view and side view 

16 

Figure 1.3 

Position of the ROIs for calculating SDNR 

Figure 1.4 

Example of an evaluation of measured SDNR against target SDNR 

Figure 1.5 

Set-up for the local dense area measurement, top view and 3D view 

Figure 1.6 

Set-up for the local dense area measurement, side views 

Figure 1.7 

Position of dosimeter to estimate incident air kerma for dose estimation, top view and 
3D view 

Figure 1.8 

Position of dosimeter to estimate incident air kerma for dose estimation, front view and 
side view 

Figure 1.9 

Two examples of the MoniQA pattern. These patterns include checks for contrast 
visibility, geometrical distortion, spatial resolution, global image quality and artefacts 
(reprinted with permission from Med. Phys.) 

Figure 1.10 

Examples of features of the MoniQA pattern: (a) example of a sequence of characters 
with a low-contrast luminance difference from the background; (b) gradient bar of 
patches with decreasing pixel values and with randomly selected characters with a pixel 
value as in the adjacent patch; (c) grid pattern; (d) corner lines pattern; (e) resolution 
patterns: (left) high-contrast and (right) low-contrast; (f) horizontal and (g) vertical 
version of the hourglass object (all elements are shown with enhanced contrast for 
clarity) 

Figure A7.1 

Position of the collimation – if used, this should be in place for all the measurements 

Figure A7.2 

Positions of the edge for MTF measurement (any additional collimation that may be used 
is not shown) 

Figure A8.1 

The CDMAM phantom 

Figure A8.2 

The aluminium base contains the gold discs of the CDMAM phantom, the PMMA cover 
contains the grid lines 

Figure A8.3 

Example of human readout of the CDMAM phantom after nearest neighbour correction 

Figure A8.4a  Example of the result of a Hough transformation of a CDMAM image. The grid can be 

recognized as two columns with equidistant local maxima 

Figure A8.4b  Template matching: in an area of 21 × 21 pixels around the predicted crossing, the 

cross-correlation of the image with a template is determined 

Figure A8.5 

Schematic illustration of the calculated disc positions (yellow inner circles) and the disc 
search areas defined around them (purple outer circles) 

Figure A8.6 

Individual disc detection: (left) the disc search areas in each of the cell corners (purple 
outer circles) and the positions within each search area (blue inner circles) where the 
disc is most likely to be located (based on total pixel value); (right) close-up of the 
detection (blue inner circle) of a 0.5 mm disc within a search area (purple outer circle) 

16 

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30 

32 

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46 

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48 

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List of tables 

Table 1.1 

Table 1.2 

Calculated values of the parameters n, a and b for a range of target/filter combinations 
(Robson, 2001) 

PMMA thickness and equivalent breast thickness in terms of attenuation and 
glandularity, accurate over a wide range of X-ray spectra (Dance et al., 2009) 

Table 1.3 

z-Factors to calculate SDNRminimum at different thicknesses of PMMA 

Table 1.4 

Dose levels for typical breasts simulated with PMMA 

Table A5.1 

g-Factors for breasts simulated with PMMA 

Table A5.2 

c-Factors for breasts simulated with PMMA 

Table A5.3 

Typical HVL measurements for different tube voltage (kV) and target/filter combinations 
(data include the effect on measured HVL of attenuation by a compression plate) 

Table A5.4a 

s-Factors for clinically used spectra (Dance et al., 2000) 

Table A5.4b 

s-Factors for a tungsten target filtered by 0.5 mm aluminium 

Table A5.4c 

s-Factors for a tungsten target filtered by 0.7 mm aluminium 

Table A5.4d 

s-Factors for a tungsten target filtered by 0.5 mm aluminium 

Table A5.4e 

s-Factors for a tungsten target filtered by 0.7 mm aluminium 

Table A5.5 

Additional g-factors 

Table A5.6 

Additional c-factors for average breasts for women in the age group 50–64 

Table A5.7 

Additional c-factors for average breasts for women in the age group 40–49 

Table A7.1a 

Number of photons µGy–1 mm–2 (SNRin
1-2 

2) for 2 mm Al according to IEC standard 62220-

Table A7.1b 

Number of photons µGy–1 mm–2 (SNRin
for some spectra not included in the IEC standard 

2) for 2 mm Al according to Boone et al. (1997) 

14 

15 

18 

24 

34 

34 

34 

35 

35 

35 

36 

36 

37 

37 

37 

43 

44 

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2b.1 

Introduction 

The European guidelines for quality assurance in breast cancer screening and diagnosis (Perry et al., 
2006) include as Chapter 2 the European protocol for the quality control of the physical and technical 
aspects  of  mammography  screening.  In  Part 2b  of  this  protocol,  the  requirements  for  digital  mam-
mography imaging systems are defined (van Engen et al., 2006b). Due to the rapid developments in 
imaging technology in recent years and further experience with digital mammography systems, some 
updating of the protocol is required and is supplied here in the form of a supplement. 

The authors welcome all comments and feedback on this document to improve the protocol. Updates 
of the current version will be made available on the EUREF web site (www.euref.org). 

In this supplement, only the changes compared with the original version of the quality control protocol 
in  the  fourth  edition  are  indicated.  Items  that  are  not  mentioned  in  this  supplement  remain 
unchanged. In some sections, further guidance and clarification is provided. 

2b.1.2 

System requirements 

A  mammography  unit  should  incorporate  a  fully  automatic  exposure  control  (AEC).  A 
system  with  solely  manual  exposure  control  (in  which  the  user  has  to  define  anode 
material, filter, tube voltage and dose) is  not acceptable. Neither is a  system with semi-
automated  exposure  control  (in  which  the  user  has  to  define  anode  material,  filter  and 
tube voltage but adapts dose according to breast transparency). 

It should be possible to output unprocessed images in DICOM format from the acquisition 
workstation or CR reader for quality control purposes. 

In  addition  to  the  parts  of  the  DICOM  standard  mentioned  in  the  fourth  edition,  mammography 
equipment should fulfil the recommendations of the IHE Mammography Image profile (MAMMO) and 
the IHE Mammography Acquisition Workflow profile (MAWF). The equipment must be CE marked and 
must be sold as ‘usable for mammography purposes’. DICOM communication between X-ray unit and 
CR reader (complete transfer of exposure parameters) is recommended. 

The  acceptable  level  is  the  minimum  acceptable  level;  however,  it  is  recommended  that  systems 
operate as far as possible at a standard equal to or better than the achievable level. Slow screen-film 
systems  are  capable  of  operating  close  to  the  achievable  image  quality  level.  Faster  screen-film 
systems are capable of operating near the acceptable level. For the next edition of the guidelines, the 
acceptable and achievable levels will be reviewed. 

Section 2b.2.4.2,  Modulation transfer  function (MTF)  and noise power spectrum (NPS), of the fourth 
edition  has  been  moved  to  Appendix 7.  This  indicates  that  it  is  not  recommended  to  perform  these 
measurements  on  a  routine  basis  for  quality  control  (QC)  purposes.  In  practice,  however,  linear 
system  theory  metrics  are  being  used  in  system  acceptance  testing  or  in  regular  QC  procedures. 
Appendix 7  represents  an  effort  to  harmonize  the  methods  of  determining  linear  system  theory 
metrics in these cases. 

Printer 

This section applies when printed films are used for reading by either the first or the second reader (in 
current and subsequent screening rounds). 

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To obtain an optimal quality for reading hard-copy films on viewing boxes, requirements for printing 
mammographic images are: 

•  The hard-copy film type must be suitable for mammography. 

•  Printing two (or more) images on the same film is not recommended. 

•  To be able to print images with sufficient resolution, the pixel pitch of the printer should be similar 

to (or smaller than) the pixel pitch of the image and must always be ≤ 100 µm. 

•  All  images  must  be  printed  directly  without  any  manipulation  by  the  user  (contrast,  luminosity, 

etc.) at the (diagnosis) workstation. 

•  Clinical  information  must  be  printed  on  each  film:  the  name  of  the  patient,  laterality,  date  of 

exams, etc. 

After  each  film  refill  in  the  hard-copy  printer,  the  printer  must  be  calibrated  (if  this  is  not  done 
automatically).  After  a  period  of  inactivity  of  more  than  one  day,  a  calibration  must  be  done  before 
printing any diagnostic film. 

Different film formats are available on the market. For mammography, only 2 sizes should be used: 

•  200 mm × 250 mm (8 × 10 inches) 

•  250 mm × 300 mm (10 × 12 inches). 

Other formats are not recommended (i.e. 260 mm × 360 mm). 

2b.1.5  Definition of terms 

AEC sensor area (DR systems) 
The area of a DR detector in which the exposure factors for an image are determined during or after a 
pre-exposure.  For  some  AEC  systems,  the  size  and  location  of  the  AEC  sensor  area  depends  on  the 
tissue (or test object) being imaged. 

Dark noise image 
An image acquired without exposure to the detector; cover the detector with a sufficiently thick metal 
plate, e.g. lead or stainless steel, and set the lowest possible tube loading. 

Detector surface 
The  accessible  area  that  is  closest  to  the  image  receptor  plane.  Depending  on  removability,  the 
detector may include e.g. breast support, covers, antiscatter grid. 

Linearized pixel value 
For images of systems with a non-linear response, the pixel values must be linearized before analysis 
using  the  response  function  of  the  system  or  the  mathematical  relationship  provided  by  the 
manufacturer.  Offset  correction  and  linearization  must  be  performed  for  noise  evaluation  and 
determination of linear system theory metrics. In principle, for some other tests (like the calculation of 
SDNR) the images need to be linearized. However, for those tests the images are acquired at almost 
the same dose so that the system can be supposed to be locally linear. 

Modulation transfer function (MTF) 
The MTF describes the response of a system to a sinusoidal input signal; see Appendix 7. 

Noise power spectrum (NPS) 
The NPS describes the variance of an image intensity divided among its frequency components; see 
Appendix 7. 

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Reference region of interest (ROI) 
The size of the reference ROI is 5 mm × 5 mm, instead of 20 mm × 20 mm as originally stated in the 
fourth  edition.  The  centre  of  the  reference  ROI  is  positioned  60 mm  from  the  chest  wall  edge  and 
centred laterally. 

Standard image 
Image  made  by  an  exposure  of  a  45 mm  thick  polymethyl  methacrylate  (PMMA)  block  plus  8 mm 
spacers covering the whole image receptor. A standard compression of 100 N should be applied, and 
the exposure should be made in the standard clinical AEC mode. 

2b.2  Image acquisition 

2b.2.1.1.1  Focal spot size 
This  measurement  is  omitted.  Potential  image  quality  problems  are  identified  by  image  quality 
measurements. 

2b.2.1.1.2  Source-to-image distance 
This measurement is omitted. 

2b.2.1.1.3  Alignment of X-ray field/image area 
This measurement is optional. 

2b.2.1.1.4  Radiation leakage 
This measurement is omitted. 

2b.2.1.1.5   Tube output 
Tube output is measured  only  for  calculating mean  glandular doses and does  not have to meet any 
limiting values. It must be known for all clinically used beam qualities. The number of different beam 
qualities can be substantial. The parametric approach as published by Robson (2001) allows the tube 
output to be estimated for any tube voltage in the range 25 kVp–32 kVp from a single measurement 
at 28 kVp that uses the same target/filter combination. 

This is a 2-step procedure. First, the value of A is calculated from equation (1), in which Output is the 
measured  air  kerma  (mGy)  at  28 kVp,  (kV)  is  the  measured  tube  voltage  and  the  parameter  n  is 
target/filter beam-specific and can be obtained from Table 1.1: 

Second, the tube output at another tube voltage (kV) is obtained from the following equation: 

Output = A(kV)n 

log10(air kerma) = nlog10(kV) + log10(A) 

(1) 

(2) 

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Table 1.1:   Calculated values of the parameters n, a and b for a range of target/filter  

  combinations (Robson, 2001) 

Target/filter 
combination 

Mo/30 µm Mo 
Mo/25 µm Rh 
Rh/25 µm Rh 
W/50 µm Rh 
Rh/1.0 mm Al 
Mo/1.0 mm Al 

Measured 
filter 
thickness 
36.1 µm 
29.9 µm 
29.9 µm 
58.9 µm 
1.20 mm 
1.20 mm 

n 

a 

b 

3.06 
3.24 
3.03 
1.96 
4.39 
4.23 

–0.000326 
–0.000624 
–0.000514 
–0.000539 
–0.00113   
–0.000775 

0.0273 
0.0445 
0.0425 
0.0403 
0.0909 
0.0593 

2b.2.1.2.2  Half value layer 
Half  value  layer  (HVL)  is  measured  to  calculate  glandular  dose.  HVL  does  not  have  to  meet  any 
requirements. Typical values are given in Table A5.3 in the fourth edition. 

For patient dosimetry applications, HVLs of all clinically used beam qualities are required. The number 
of  different  beam  qualities  can  be  substantial.  The  parametric  approach  as  published  by  Robson 
(2001) allows the HVL to be estimated for any tube voltage in the range 25 kVp–32 kVp from a single 
measurement at 28 kVp that uses the same target/filter combination. 

As  with  the  tube  output,  this  is  a  2-step  procedure  based  on  parameters  from  Table 1.1.  First,  the 
value of c is calculated from the equation 

HVL = a(kVp)2 + b(kVp) + c 

(3) 

in which HVL is the measured HVL at 28 kVp, (kVp) is the measured tube voltage and the parameters 
a and b are target/filter beam-specific and can be obtained from Table 1.1. 

HVLs at other tube voltages can then be calculated from the same equation using a, b and c. 

2b.2.1.3.1  Exposure control steps 
If exposure control steps are available on a mammography system, then the control step should have 
known dose increments, e.g. 20% per step, and should be verified. 

2b.2.1.3.3  Short-term reproducibility 
The short-term reproducibility of the AEC system is calculated by the deviation of the linearized pixel 
value of 10 exposures in fully automatic mode of the standard test block. 

If  it  is  noticed  that  the  system  switches  between  two  spectra,  release  the  compression  paddle  and 
compress again or  use another PMMA thickness (add, e.g., 5 mm PMMA) to  force the choice of one 
single spectrum, and repeat the measurement. 

Limiting value 
Frequency 
Equipment 

Deviations from the mean value of 10 exposures ≤ ±5%, achievable ≤ ±2%. 
Every 6 months. 
Standard test block. 

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2b.2.1.3.5  Breast thickness and composition compensation  
Spacers  are  used  to  adjust  the  height  of  the  compression  paddle  equal  to  the  height  of  the 
compression paddle of the breast thickness with equivalent attenuation as given in Table 1.2. Dance 
and colleagues have verified that this table is accurate to within 1 mm or 2 mm across the wide range 
of spectra encountered in digital mammography (Dance et al., 2009). 

The spacers should not cover the part of the detector in which exposure factors are determined (AEC 
sensor area). 

Table 1.2:   PMMA thickness and equivalent breast thickness in terms of attenuation and 
glandularity, accurate over a wide range of X-ray spectra (Dance et al., 2009) 

PMMA 
thickness 
(mm) 

Equivalent 
breast 
thickness 
(mm) 

Glandularity 
of equivalent 
breast 
(%) 

20 
30 
40 
45 
50 
60 
70 

21 
32 
45 
53 
60 
75 
90 

97 
67 
41 
29 
20 
9 
4 

Images should be acquired in fully automatic mode; however, on some systems it may be convenient 
to mimic the exposure of the fully automatic mode in manual mode. In this case, it should be realized 
that the pre-exposure image is not used for the actual image on some types of system. This should be 
taken  into  account  when  determining  signal-difference-to-noise  ratio  (SDNR)  in  manual  mode.  It 
should  also  be  known  whether  the  pre-exposure  is  included  in  the  displayed  mAs  value  in  fully 
automatic mode. 

The  following  method  can  be  used  to  determine  whether  the  tube  load  (mAs)  of  the  exposure  is 
included  in  the  tube  load  indication  (mAs)  of  the  fully  automatic  exposure  mode.  Determine  the 
relationship  between  tube  load  and  pixel  value  (PV)  in  a  reference  ROI  for  a  series  of  manual 
exposures over the clinical working range. Make an exposure in  fully automatic  mode. Record beam 
quality and mAs value. Verify whether the PV in the reference ROI of this image is compatible with the 
PV of a manual exposure with the same tube load (mAs). 

The  dimensions  of  the  aluminium  object  are  10 mm  ×  10 mm  and  0.2 mm  thick.  The  object  is 
positioned  as  shown  in  Figures 1.1  and  1.2.  The  aluminium  object  is  positioned  between  the  two 
lowest 10 mm thick plates of PMMA. 

The ROI within the aluminium object is 5 mm  × 5 mm in the middle of the object. The background 
ROIs are 4 ROIs of 5 mm × 5 mm, on all 4 sides of the aluminium object; see Figure 1.3. 

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Figure 1.1:  Set-up for the breast thickness and composition measurements, top view  

and 3D view 

Figure 1.2:  Set-up  for  the  breast  thickness  and  composition  measurements,  front  view

and side view 

Figure 1.3:  Position of the ROIs for calculating SDNR 

10 mm 

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Calculate PV(background) and the standard deviation SD(background) according to: 

SD(backgro

und)

PV(backgro

und)

Calculate SDNR of the aluminium object: 

4
SD(ROI

)

n

∑=

1

4

PV(ROI

)

n

4

∑=

4

1

SDNR  

PV(signal) – PV(background) 

SD(signal)2 + SD(background)2  

2  

(4) 

(5) 

(6) 

To apply the standards in the European protocol, the limiting values for SDNR have to be determined. 
Two methods are described here. The first is a simplified method using threshold gold thickness, and 
the second involves calculating the threshold contrast for the beam quality used. It is assumed in both 
methods that the exposure factors for the CDMAM phantom and the 50 mm of PMMA are the same. If 
for some reason they are not, then a small correction can be applied. 

Simplified method using threshold gold thickness 

The limiting values  for SDNR are calculated using equations (7) and (8).  These equations determine 
the  SDNR  values  necessary  to  achieve  the  minimum  and  achievable  threshold  gold  thickness  in  the 
image  quality  measurements  for  the  0.1 mm  detail  size  at  this  thickness,  i.e.  50 mm  PMMA  or 
equivalent. 

     SDNRminimum = 

SDNR

Tg
×
measured Tg

measured

minimum

    SDNRachievable = 

SDNR

Tg
×
measured Tg

measured

achievable

 (7) 

 (8) 

where  Tgmeasured  is  the  threshold  gold  thickness  for  the  0.1 mm  detail  size  predicted  for  a  human 
observer,  and  Tgminimum  and  Tgachievable  are  the  limiting  values  for  threshold  gold  thickness  for  the 
0.1 mm detail size in the European protocol. 

It  is  estimated  that  the  maximum  error  in  estimating  the  target  SDNR  by  this  method  as  compared 
with calculations based on threshold contrasts (see next paragraph) is 4%. Thus, for routine QC this 
simplified method may be acceptable. 

Method using threshold contrast 

A more accurate method of defining the limiting values for SDNR involves estimating the contrast of 
the  gold  discs  for  the  beam  quality  used.  Such  a  transformation  from  gold  thickness  to  contrast  is 
necessary because of the non-linear relationship between these two properties. A simple tool for cal-

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culating  the  limiting  values  is  provided  on  the  EUREF  web  site,  and  the  method  used  is  described 
here. 

Limiting values for SDNR are calculated using equations (9) and (10). These equations determine the 
SDNR values necessary to achieve the minimum and achievable threshold gold thickness in the image 
quality measurements for the 0.1 mm detail size at this thickness, i.e. 50 mm PMMA or equivalent. 

   SDNRminimum = 

SDNR

Tc
measured Tc

×

measured

minimum

       SDNRachievable = 

where 

SDNR

Tc
measured Tc

×

measured

achievable

Tc

measured

−−=
e
1

µ

eff

⋅
Tg

measured

Tc

minimum

−−=
e
1

µ

eff

⋅
Tg

minimum

Tc

achievable

−−=
e
1

µ

eff

⋅
Tg

achievable

 (9) 

 (10) 

(11) 

(12) 

(13) 

where  Tcmeasured  is  the  threshold  contrast  for  the  0.1 mm  detail  size  calculated  from  the  measured 
threshold  gold  thickness,  Tcminimum  and  Tcachievable  are  the  threshold  contrasts  calculated  from  the 
limiting values for threshold gold thickness for the 0.1 mm detail size in the European protocol and µeff 
is  the  effective  attenuation  coefficient  used  to  estimate  the  contrast  of  gold  discs  in  the  CDMAM 
phantom  depending  on  the  beam  quality  used.  A  look-up  table  of  values  for  µeff  is  included  in  the 
software tool on the EUREF web site. 

The  methods  above  determine  the  limiting  values  for  SDNR  for  an  attenuation  equivalent  to  50 mm 
PMMA. The European protocol adjusts SDNRminimum for other thicknesses of PMMA using equation (14) 
and Table 1.3. The SDNRachievable limit can be applied across other PMMA thicknesses. 

            SDNRminimum = 

SDNR

Tg
×
measured Tg

measured

× z 

minimum

 (14) 

Table 1.3:   z-Factors to calculate SDNRminimum at different thicknesses of PMMA 

Thickness of PMMA 
(mm) 
20 
30 
40 
45 
50 
60 
70 

z-factor 

1.15 
1.10 
1.05 
1.03 
1.00 
0.95 
0.90 

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To evaluate the AEC performance, the measured SDNR should be plotted against the PMMA thickness 
and compared with the limiting SDNR values, as shown in Figure 1.4. In this case, the system failed to 
exceed the minimum acceptable SDNR at the 60 mm and 70 mm thicknesses of PMMA. 

Figure 1.4:   Example of an evaluation of measured SDNR against target SDNR 

20

15

10

5

l

A
m
m
2
.
0

r
o
f

R
N
D
S

SDNRminimum (5m PMMA)
SDNRminimum (50 mm PMMA) 
SDNRachievable (5cm PMMA)
SDNRachievable (50 mm PMMA) 
SDNR to meet European limiting value
SDNR to meet European limiting value 

Measured SDNR
Measured SDNR 

0

10

20

30

40

50
PMMA thickness (mm)

60

70

Note that in general a change to a higher SDNR will be associated with better image quality if all other 
factors  are  unchanged.  However,  if  such  a  change  is  associated  with  a  change  in  image  sharpness, 
the opposite may be true and an investigation of sharpness and image quality should be undertaken. 

2b.2.1.3.6  Local dense area (only DR systems) 
Most  systems  measure  the  attenuation  of  the  imaged  object  during  a  pre-exposure.  The  areas  with 
highest attenuation in the clinically relevant part of the image should determine the exposure factors 
for  imaging.  It  is  required  that  the  signal-to-noise  ratio  (SNR)  in  the  images  be  adjusted  to  the 
(relatively large) regions with highest density. 

Put  a  30  mm  stack  of  PMMA  plates  on  the  bucky.  Put  spacers  on  top  of  the  stack,  such  that  the 
compression  paddle  is  positioned  at  a  height  of  40 mm  above  the  breast  holder  (compression  force 
can be applied). The spacers should not cover the part of the detector in which exposure factors are 
determined  (AEC  sensor  area).  On  the  compression  paddle,  position  a  first,  small  PMMA  plate, 
representing a relatively large area with higher density (20 mm × 40 mm, 2 mm thick), in the central 
part of the detector with its lower edge 50 mm from the chest wall side. 1 (It must be ensured that this 
plate is within the AEC sensor area. If this is  not the  case, another position should be chosen.)  See 
Figures 1.5  and  1.6.  Make  an  exposure,  and  record  the  exposure  factors.  Add  another  small  PMMA 
plate on top of the previous one, and repeat the procedure until 10 small plates have been added. 

Measure  PV  and  standard  deviation  (SD)  in  the  area  of  extra  attenuation  (20 mm  ×  40 mm  PMMA 
plates)  with  a  ROI  of  5 mm  ×  5 mm.  Calculate  SNR  for  each  image  and  the  average  SNR  for  all 
images.  It  should  be  checked  whether  the  exposure  of  the  images  is  increased  with  increasing 
thickness and whether the extra attenuation is detected. For this, the following value can be used as 
guidance: the SNR of each image should be within 20% of the average SNR (provisional). 

1 The small PMMA plates may also be positioned in a non-central region but must be positioned within the AEC sensor area. 

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Guidance  
Frequency 
Equipment 

The SNR of each image should be within 20% of the average SNR (provisional). 
Every 6 months, or after AEC software upgrades. 
Three  150 mm  ×  180 mm  PMMA  plates  (10 mm  thick),  two  spacers  (10 mm 
thick), ten 20 mm × 40 mm PMMA plates (2 mm thick). 

Figure 1.5:   Set-up for the local dense area measurement, top view and 3D view 

Figure 1.6:   Set-up for the local dense area measurement, side views 

2b.2.1.5  Antiscatter grid 

2b.2.1.5.1  Grid system factor 
This measurement is omitted. 

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2b.2.1.5.2  Grid imaging 
This measurement is omitted. 

2b.2.2.1.2  Noise evaluation 
The scope of this test is the analysis of different noise components to provide additional information 
on  the  performance  of  the  imaging  system  and  to  optimize  troubleshooting  in  case  of  potentially 
decreased image quality. The method described here is reported in greater detail elsewhere (Evans et 
al., 2002; Borasi et al., 2003; Young et al., 2006b) and particularly in Bouwman et al. (2009). 

General requirement: For systems with a non-linear response, the pixel data must be linearized before 
analysis. 

Noise in images can be subdivided into electronic noise, quantum noise and structure noise: 

SD2 = ke

2 + kq

2 

2 
* p   + ks

* p2 

SD  =   standard deviation in reference ROI 
ke  =   electronic noise coefficient 
kq  =   quantum noise coefficient 
ks  =   structure noise coefficient 
p  =   average pixel value in reference ROI. 

(15) 

Electronic noise is assumed to be independent of the exposure level and arises from several sources: 
dark noise, readout noise and amplifier noise. 

Quantum noise arises due to the variations in X-ray flux and (if present) secondary carrier flux. 

Structure noise is present due to spatially fixed variations of the gain of an imaging system. The flat-
fielding performed in DR systems will largely remove the effects of structure noise. Due to the limited 
number of images used for the flat-field mask and the associated noise in the mask, some structure 
noise will still be present. 

Remove the compression paddle and all other removable parts (e.g. covers and antiscatter grid) from 
the X-ray beam. Position a 2 mm thick aluminium plate as close as possible to the X-ray tube. 

Set  the  target/filter  combination  and  the  tube  voltage  that  is  chosen  in  fully  automatic  mode  for  a 
45 mm thick PMMA object plus 8 mm spacers. In manual mode, set the minimum mAs value. Image 
the  aluminium  plate.  Increase  the  mAs  value  and  image  the  plate  again.  Take  a  large  number  of 
images  at  different  mAs  values  (e.g.  15  values  for  acceptance  tests,  8  values  for  subsequent  tests) 
over the whole range of available values with a typical spacing of approximately 40%.  Then, take a 
dark noise image. 

It  is  optional  to  repeat  the  measurement  for  all  target/filter  combinations,  with  a  clinically  relevant 
tube voltage for each combination. 

It  is  optional  to  measure  or  calculate  the  dose  on  the  detector  surface  from  tube  output  measure-
ments for all spectra, to be able to use detector air kerma instead of PV in this evaluation. 

Analysis steps: 

1.  Measure PV and SD in the reference ROI. 

2.  Plot PV against detector dose to determine the response function. 

3.  Plot SD² against PV (or detector dose). 

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4.  Fit the points using equation (15), and determine the noise coefficients. 

5.  Determine the detector dose range for which quantum noise is the largest noise component. 

Option:  The  calculated  noise  components  can  be  used  to  plot  PV  (or  detector  dose)  against  the 
percentage of the total relative noise for all noise components. In this graph, the magnitude (in %) of 
all noise components is visualized for the range of PVs (or detector doses). 

Limiting value 

Frequency 
Equipment 

Quantum  noise  should  be  the  largest  noise  component  for  the  pixel  value 
range (detector dose range) that is used clinically. 
Every 6 months. 
Aluminium plate (2 mm thick) covering the whole X-ray field (near the tube), 
appropriate software tools. 

2b.2.2.3.1  Image receptor homogeneity 
In addition to the test described in the fourth edition, with an ROI size of 10 mm × 10 mm, another 
ROI, of dimensions 2 mm × 2 mm, is used to calculate variance in each ROI. Equation (16) is used to 
calculate  variance.  This  parameter  is  sensitive  to  the  occurrence  of  artefacts  on  the  image  and 
supports visual artefact analysis by indicating deviations automatically. 

Var(X) =   

N   
∑  
i =1(xi – µ)2 
N – 1  

(16) 

More detailed information on the method described here is provided in van Engen et al. (2006a); see 
also Marshall (2006). 

Limiting value 

Frequency 

Equipment 

The  average  variance  of  each  ROI  should  be  compared  with  the  average 
variance of the neighbouring ROIs. If the variance in an ROI is ≥ 30% higher 
than  the  variance  in  neighbouring  ROIs,  the  image  should  be  investigated 
visually for an artefact at this position. 
Weekly (it is recommended to perform this test before and after calibration); 
optional: daily. 
Standard  test  block  covering  the  complete  detector,  appropriate  software 
tools. 

2b.2.2.3.2  Detector element failure (DR systems) 
The  method  and  limiting  values  of  the  fourth  edition  are  used.  The  bad  pixel  map  should  be  easily 
accessible for all users and should be provided e.g. as a table including number, size and location of 
the  defective  elements,  clusters  and  lines.  If  uncorrected  bad  pixels  are  visible  on  the  images,  this 
should be taken into account when evaluating detector element failure. 

2b.2.2.4 

Interplate sensitivity variations and plate uniformity (CR systems) 

In  addition  to  the  test  in  the  fourth  edition:  Take  an  image  receptor  homogeneity  image  (see 
Section 2b.2.2.3.1),  and  inspect  the  variance  map  for  all  plates.  It  may  be  necessary  to  clean  the 
plates, following the standard cleaning procedure given by the manufacturers, to determine whether 
some artefact can be removed. 

Limiting value 

No  artefacts  should  be  present.  If  the  variance  in  an  ROI  is  ≥ 10%  higher 
than  the  variance  in  neighbouring  ROIs,  the  image  should  be  investigated 
visually for an artefact at this position. 

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Frequency 
Equipment 

Monthly. 
Standard test object covering the complete detector. 

2b.2.2.5 

Influence of other sources of radiation 

This test is omitted. 

2b.2.2.6 

Fading of latent image (CR systems) 

This test is omitted. 

2b.2.3  Dosimetry 

This  section  makes  it  possible  to  apply  the  existing  dosimetric  procedures  to  the  wider  range  of 
target/filter  combinations  found  in  modern  X-ray  sets.  Typically,  these  involve  using  beam  qualities 
with  higher  HVL  than  provided  for  previously.  In  addition,  more  specific  guidance  is  given  for  the 
configuration to be used in determining the incident air kerma. Other aspects of the previous guidance 
are repeated here so that all the required information is available within this document. 

2b.2.3.1  Dose to typical breasts simulated with PMMA 

The doses to a range of typical breasts should be assessed with blocks of PMMA as breast substitutes 
using the usual clinically selected exposure factors, including any automatic selection of tube voltage 
and target/filter combination. This method relies on the equivalence in attenuation between different 
thicknesses of PMMA and typical breasts (Dance et al., 2000), as listed in Table A5.1 in Appendix 5. It 
should  be  noted  that  because  PMMA  is  denser  than  breast  tissue,  any  automatic  selection  of  tube 
voltage, target or filter may be slightly different from that for real breasts. This can be corrected by 
adding spacers (e.g. expanded polystyrene blocks) to the PMMA to make up a total thickness equal to 
that of the equivalent breast. Small pieces of more attenuating materials can also be used as spacers 
provided  they  are  outside  the  sensitive  area  of  the  AEC.  On  systems  that  determine  the  exposure 
factors using transmission, spacers should not be necessary. 

Set the AEC to normally used clinical settings, and expose PMMA plates of 20 mm thickness. Record 
the exposure factors chosen by the AEC. Repeat this measurement for 30, 40, 45, 50, 60 and 70 mm 
PMMA thickness. (For routine testing it is sufficient to use only a 45 mm thickness of PMMA.) Calculate 
the  average  glandular  dose  (D)  to  a  typical  breast  of  thickness  and  composition  equivalent  to  the 
thickness of PMMA by applying the following formula: 

D = Kgcs   

(17) 

where K is the incident air kerma (without backscatter) calculated at the upper surface of the PMMA 
using the method described later in this section. The g-factor corresponds to a glandularity of 50%, is 
derived from the values calculated by Dance (1990), Dance et al. (2000) and Dance et al. (2009) and 
is shown in Table A5.1 for a range of HVLs. The c-factor corrects for the difference in composition of 
typical  breasts  from  50%  glandularity  (Dance  et  al.,  2000;  Dance  et  al.,  2011)  and  is  given  in 
Table A5.2  for  typical  breasts  for  women  in  the  age  group  50–64.  Note  that  the  g-factors  and  c-
factors applied are those for the corresponding thickness of typical breast rather than the thickness of 
PMMA  block  used.  Where  necessary,  interpolation  may  be  made  for  different  values  of  HVL.  Typical 
values  of  HVL  for  various  spectra  are  given  in  Table A5.3,  but  HVLs  are  normally  measured  at  the 
same time as the measurements necessary to determine the incident air kerma. The s-factor shown in 

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Table A5.4a  corrects  for  any  difference  due  to  the  choice  of  X-ray  spectrum  (Dance  et  al.,  2000; 
Dance  et  al.,  2011).  Note  that  for  the  W/Al  target/filter  combination,  the  s-factor  varies  with  filter 
thickness and breast thickness (Tables A5.4b–e). 

Maximum average glandular dose 

Limiting value 

Frequency 
Equipment 

A maximum average glandular dose is set per PMMA thickness,  as shown in 
Table 1.4. 
Every 6 months. 
Calibrated mammographic dosimeter, 20–70 mm thick blocks of PMMA. 

Table 1.4:  

  Dose levels for typical breasts simulated with PMMA 

Thickness 
of PMMA 
(mm) 

Equivalent 
breast 
thickness  
(mm) 

Maximum average glandular 
dose to equivalent breasts 
(mGy) 

Acceptable level 

20 
30 
40 
45 
50 
60 
70 

21 
32 
45 
53 
60 
75 
90 

≤ 1.0 
≤ 1.5 
≤ 2.0 
≤ 2.5 
≤ 3.0 
≤ 4.5 
≤ 6.5 

Achievable 
level 
≤ 0.6 
≤ 1.0 
≤ 1.6 
≤ 2.0 
≤ 2.4 
≤ 3.6 
≤ 5.1 

Incident air kerma 

In the original publication by Dance (1990), the incident air kerma was calculated for a dosimeter in 
contact with and below a compression paddle. It follows that the determination of incident air kerma 
at the surface of PMMA test phantoms or breasts should be based on measurements made with this 
geometry to correctly include scatter from the paddle. The recommended geometry for the procedure 
is shown in Figures 1.7 and 1.8 and is described below. 

Calculate the incident air kerma for each of the beam qualities used in exposing the blocks of PMMA 
by  making  an  exposure  of  the  dosimeter  positioned  as  in  Figures 1.7  and  1.8  using  a  manually 
selected tube loading (e.g. 50 mAs). Estimate the incident air kerma at the upper surface of the PMMA 
by using the inverse square law and scaling to the appropriate value of tube loading (mAs). The HVL 
should  also  be  estimated  at  the  same  time  using  multiple  layers  of  aluminium,  as  described  in  the 
fourth edition. 

The chamber should be positioned on a line extending from the tube focus to a point on the mid-line 
of  the  breast  support  table  60 mm  from  the  chest  wall  edge.  If  the  chamber  has  backscatter 
correction, the recommended position is directly on the breast support with the paddle in contact. It 
would  also  be  possible  to  make  a  measurement  of  air  kerma  with  the  dosimeter  higher  above  the 
breast support and with the paddle in contact provided the appropriate inverse square law correction 
is  made.  This  approach  is  recommended  if  the  chamber  does  not  have  backscatter  correction.  The 
effect of scatter from the compression paddle on the measurement of incident air kerma is discussed 
in  Dance  et  al.  (2009),  where  it  is  shown  that  for  the  above  geometry  and  a  polycarbonate  paddle 
2.4 mm thick, scattered photons contribute 7% of the total measured air kerma. 

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Figure 1.7:   Position  of  dosimeter  to  estimate  incident  air  kerma  for  dose  estimation, 

top view and 3D view 

Figure 1.8:   Position of dosimeter to estimate incident air kerma for dose estimation,  

front view and side view 

2b.2.3.2  Clinical breast doses 

It is also possible to measure the average glandular dose for a series of breast examinations on each 
mammography  system.  To  do  this,  for  each  exposure  the  breast  thickness  under  compression  is 
measured  and  the  exposure  factors  are  recorded.  From  measurements  of  air  kerma  as  described 
previously  (Figures 1.7  and  1.8)  at  the  tube  voltage  and  target/filter  combination  used,  the  tube 
loading (mAs) may be used to estimate the incident air kerma and to determine the average glandular 
dose using equation (17). In this case, K is the incident air kerma calculated at the upper surface of 
the  breast.  For  the  appropriate  breast  thickness,  g-factors  should  be  interpolated  from  Table A5.5; 
c-factors for typical breast compositions for women in the age groups 50–64 and 40–49 are shown in 
Tables A5.6 and A5.7, respectively. Measurement of  compressed breast thickness for this purpose is 
performed by the radiographer, by reading the displayed compressed thickness on the X-ray set. The 

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accuracy of the displayed thickness should be verified by applying a typical force (e.g. 100 N) to rigid 
material  of  known  thickness.  It  may  be  necessary  to apply  correction  factors  if  the  displayed  values 
are  in  error.  An  accuracy  of  ≤  ±2 mm  is  required.  Software  for  making  such  dose  calculations  has 
been published by the United Kingdom Breast Screening Programme (Young, 2001). 

2b.2.4.1 

Threshold contrast visibility 

In  threshold  contrast  visibility  analysis,  the  pixel  value  (PV)  and  SNR  are  assumed  to  be  relatively 
constant  over  the  imaging  fields.  If  low-frequency  trends  in  PV  are  present,  it  may  be  necessary  to 
correct for such a trend before analysis. 

Threshold  contrast  visibility  is  determined  for  cylindrical  details  with  diameters  in  the  range  from 
0.1 mm  to  1 mm.  The  details  are  imaged  on  a  background  object  with  an  attenuation  equivalent  to 
50 mm of PMMA. The details must be positioned at a height of 20–25 mm above the breast support 
table.  Use  the  exposure  factors  that  are  selected  in  fully  automatic  mode  for  50 mm  PMMA  with 
10 mm thick spacers, as found when measuring breast thickness and composition compensation. 

Take  at  least  16  images  of  the  details,  and  move  the  details  slightly  between  the  images  to  obtain 
images in which the relative positions of the details and the detector elements are different. The ‘for 
processing’ version of the images should be used for analysis. 

Automated threshold contrast measurement using CDMAM 

If the CDMAM phantom is used, it is recommended that automated computer reading be performed to 
determine  the  threshold  gold  thickness  for  each  detail  size.  Software  tools  for  doing  this  are 
downloadable  from  the  EUREF  web  site  (www.euref.org).  This  will  involve  downloading  the  latest 
version of CDCOM. Appendix 8 provides a description of how CDCOM works. 

Using  the  output  of  CDCOM,  a  detection  matrix  is  constructed  and  for  each  diameter  of  cylindrical 
details a psychometric curve is fitted (Veldkamp et al., 2003): 

p(d)

=

0.75
−
(
Cfe

1

+

+

25.0

−

Ct

)

(18) 

  C  = logarithm of signal contrast; C = log(1 − e−μd) 
  Ct = signal contrast at the threshold of 62.5% 

f

  = fitting parameter 

    p(d) = the probability of detection of an object with size d. 

A threshold at 62.5% correct response is used to determine the threshold contrast. Results for which 
the  psychometric  curve  is  fitted  with  only  a  few  data  points  are  disregarded.2  To  use  the  limiting 
values in the existing protocol (in the fourth edition), the resulting thresholds for each diameter have 
to be converted to human readout. 

A  tool  called  ‘CDMAM  analysis  software  tool’  uses  the  output  from  CDCOM  for  a  set  of  images  to 
determine threshold gold thicknesses for the different detail sizes. A software description and software 
manual  for  ‘CDMAM  analysis  software  tool’  is  also  available  for  download  from  the  EUREF  web  site 
(www.euref.org). Because  the automated analysis is  more successful at locating the gold discs than 
human  observers  are,  ‘CDMAM  analysis  software  tool’  also  provides  the  threshold  gold  thickness 
expected for a typical observer. Two basic methods of converting from automated thresholds to those 
predicted  for  human  observers  have  been  used.  In  the  original  approach  described  by  Young  et  al. 

2 A typical range for which the psychometric curve can be fitted is 0.1 mm to 1.0 mm (CDMAM version 3.4). 

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(2006a), the thresholds are scaled up using a value for each detail diameter (referred to as the United 
Kingdom  method).  More  recently,  a  formula  such  as  that  shown  in  equation (19)  and  described  in 
Young et al. (2008) has been used, which scales the threshold gold thickness independent of diameter 
(referred to as the EU method). Both methods are currently implemented in ‘CDMAM analysis software 
tool’  to  provide  retrospective  compatibility.  However,  it  is  recommended  that  the  United  Kingdom 
method be adopted. 

                         Tpredicted = a[Tauto]n 

(19) 

 Tpredicted = predicted human threshold gold thickness 
 Tauto = computer readout of threshold gold thickness 
 a and n = fitted parameters with a = 1.441, n = 0.895. 

‘CDMAM analysis software tool’ also fits the resulting predicted threshold gold thicknesses with a third-
order polynomial function (Equation (20)) to obtain the contrast-detail curve. 

T = a +  

b 

x 

+  

c 
x2 

d 
x3 

        (20) 

T = threshold gold thickness (µm) 
x = detail diameter (mm) 
a, b, c and d = coefficients adjusted to achieve 

a least-squares fit; all are ≥ 0 

The values from the fitted curve should be checked against the limiting values for human readout of 
threshold gold thickness as published in the fourth edition. 

Limiting value 
Frequency 
Equipment 

See fourth edition. 
Every 6 months. 
CDMAM  structure  plate  compliant  with  version  3.4  (or  higher)  and  four 
10 ± 0.2 mm thick PMMA plates of the same size; appropriate software tools. 

Comments and tips 

The results of these measurements are related in a predictable manner to the exposure factors used 
for a given system in terms of radiation dose, all other things being equal. Therefore, it is important to 
record  the  exposure  factors  used  and  to  calculate  the  corresponding  radiation  dose  in  terms  of  the 
mean glandular dose (MGD) to the standard breast simulated using a 50 mm thickness of PMMA, as 
described in the dosimetry section. Care should be taken when an exposure in fully automatic mode 
(from the thickness compensation measurement) is mimicked in manual mode. Account needs to be 
taken of whether the  pre-exposure is included in the displayed mAs value in automatic mode. Once 
threshold  gold  thickness  is  known  for  one  dose  level,  it  is  relatively  straightforward  to  predict  the 
results at other dose levels. 

Whereas  automated  analysis  works  quite  consistently  for  a  given  phantom,  the  results  vary  more 
between phantoms. Several methods to reduce this problem are being explored and are expected to 
result  in  improved  versions  of  CDCOM  and/or  a  calibration  procedure  for  phantoms.  The  type  and 
serial number of the phantom used should be recorded. 

In threshold contrast visibility analysis, the PV and SNR are assumed to be relatively constant over the 
imaging fields. If large low-frequency trends in PV are present, it may be necessary to correct for such 
a  trend  before  analysis  e.g.  by  applying  a  flat-field  correction  to  the  images.  However,  this  is  rarely 
necessary because most manufacturers already apply such a correction to their unprocessed images. 

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If reasonable doubts exist  about the automated readout of the phantom images, the images should 
be scored by human observers. 

2b.2.4.2  Modulation transfer function (MTF) and noise power spectrum (NPS) 

Moved to Appendix 7. 

2b.2.4.3 

Exposure time 

The time for an exposure in all clinically used AEC modes is measured at 45 mm PMMA thickness. 

2b.2.4.4  Geometrical distortion and artefact evaluation 

Image the phantoms in fully automatic mode. Artefact evaluation should also be performed using the 
variance map mentioned in Section 2b.2.2.3.1. 

2b.3  Image processing 

It  is  not  yet  possible  to  perform  objective  quantitative  measurements  on  image  processing  in  the 
context of an acceptance test. Due to the importance of the subject, some guidance on the evaluation 
of image processing is given in this section. The method described here is reported in greater detail 
elsewhere (Van Ongeval et al., 2008; van Engen et al., 2013). 

An unprocessed image (DICOM: ‘for processing’) with a linear relationship between detector dose and 
PV, which is the output of most current DR systems, is not the most suitable image for radiologists to 
read.  In  this  type  of  image,  the  PV  is  related  to  the  number  of  X-ray  quanta  interacting  in  the 
detector. A radiologist, however, is interested in structures in the breast and the amount of radiation 
attenuated  by  these  structures.  This  ‘attenuation  image’  is  obtained  by  transforming  PVs 
logarithmically. For most CR systems the images are already scaled logarithmically by the hardware of 
the  reader,  so  the  unprocessed  images  have  a  non-linear  relationship  between  image  receptor  dose 
and PV. 

In  the  next  stage,  the  image  is  further  processed  to  enhance  the  visibility  of  the  clinically  relevant 
information, yielding a processed image (DICOM: ‘for presentation’). 

Processing techniques that are applied to mammographic images include: 

• 

• 

• 

LUT and Bit operations 

thickness equalization at the edge of the breast 

sharpening of the image 

•  noise reduction 

• 

contrast optimization. 

Objective  evaluation  of  image  processing  algorithms  is  very  difficult.  Image  characteristics,  like  PV 
distribution  (histogram),  shape,  etc.,  are  used  in  image  processing  algorithms.  This  means  that 
phantoms  whose  characteristics  differ  from  those  of  a  breast  cannot  be  used  to  evaluate  image 
processing. The difference in characteristics causes the processing of phantom images to be different 

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from that of images of breasts. Artefacts may also be introduced because image processing algorithms 
presume a breast edge (skin line) that may not be present in technical test objects. 

Therefore, to date only subjective evaluation of image processing algorithms could be performed, by 
radiologists scoring mammograms. 

After installation of a system and the acceptance test, it is recommended to carefully evaluate a series 
of  clinical  images.  If  possible,  clinical  images  taken  with  the  new  system  should  be  compared  with 
previous images of the breasts of the same woman taken with a diagnostically established modality. 

The following image characteristics may be taken into account when comparing images: 

1. 

2. 

3. 

4. 

5. 

6. 

7. 

8. 

9. 

the visualization of the skin line 

the visibility of vascular structures through dense parenchyma 

the visualization of vascular and fibrous structures and pectoral muscle 

the visualization of structures along the pectoral muscle 

the  visualization  of  Cooper’s  ligaments  and  vascular  structures  in  the  low-  and  high-PV  areas  of 
the image 

the outlines of microcalcifications 

the noise in the low- and high-PV areas of the image 

the contrast in the low- and high-PV areas of the image 

the appearance of glandular tissue 

10.  the appearance of the background area (the area directly exposed to the X-ray field without any 

attenuation by the imaged object) 

11.  the confidence of the radiologist with the representation of the image 

12.  the presence of artefacts. 

It must be realized that large numbers of cases of different breast types, breast thicknesses and dose 
levels should be reviewed before conclusions about the quality of images can be drawn, because the 
visibility of structures may differ in individual cases, e.g. due to differences in positioning or variations 
in anatomical structures. 

2b.4  Image presentation 

2b.4.1   Monitors 

2b.4.1.1   Ambient light 

For  LCD  displays,  the  maximum  ambient  light  value  is  increased  to  20 lux.  For  CRT  displays,  the 
maximum ambient light level remains 10 lux. 

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2b.4.1.2–5 Constancy tests of monitor performance 

In the fourth edition, it is stipulated that the following parameters of a monitor should be evaluated 
daily:  geometrical  distortion  (on  CRT  displays)  (2b.4.1.2),  contrast  visibility  (2b.4.1.3)  and  display 
artefacts (2b.4.1.5). It was recommended that these tests should be performed by using the TG18-QC 
test pattern of the American Association of Physicists in Medicine (AAPM). In this section, alternative 
test  patterns  are  described  that  can  be  used  to  test  contrast  visibility,  geometrical  distortion  and 
display  artefacts  as  efficiently  as  with  the  AAPM  test  patterns  (Jacobs  et  al.,  2007).  The  complete 
procedure includes the use of a newly generated test pattern for every evaluation and a fill-in sheet 
for  comparing  the  readings  with  the  true  values.  This  procedure  overcomes  inattentive  scoring  and 
allows adherence to the QC procedures to be verified easily. The software for generating and scoring 
the test patterns is downloadable from the EUREF web site (www.euref.org). 

The MoniQA pattern is divided into 4 equally sized rectangular segments with 4 uniform background 
values  of  different  intensities.  The  values  were  chosen  to  be  0%,  33%,  66%  and  100%  of  the 
maximum  grey  level.  The  position  of  these  rectangles  swaps  randomly  each  time  the  pattern  is 
generated, with one restriction: the rectangle with a grey level of 0% (Lmin) will always have a mutual 
border with the rectangle with a grey level of 100% (Lmax). This guarantees a black-to-white or white-
to-black  transition  between  the  patches  with  the  maximum  and  the  minimum  grey  level.  This 
transition can be either horizontal or vertical. Figure 1.9 shows two examples of the variable pattern. 

Figure 1.9:   Two  examples  of  the  MoniQA  pattern.  These  patterns  include  checks  for 
contrast  visibility,  geometrical  distortion,  spatial  resolution,  global  image 
quality and artefacts (reprinted with permission from Med. Phys.) 

Extra tests: 

i. 

Low-contrast characters 

In the centre of each rectangular segment there is a set of five characters that have a low contrast 
with  the  background  PV  (Figure 1.10a).  Each  time  the  pattern  is  generated,  the  characters  are 
randomly  chosen  out  of  a  subset  of  the  Latin  alphabet,  i.e.  ABCDEHJKLMPSTUZ.  Each  set  of 
characters  has  PV  differences  of  7,  5,  3,  2  and  1  between  background  and  character.  The  observer 
has to read as many characters as possible. It is suggested that the observer guess the identity of one 
character more than those seen with certainty. 

Score criteria: If characters are not discriminated from the background, points are subtracted from the 
initial  score  of  100  according  to  the  PV  difference  between  character  and  background.  If  the  least 

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visible  character is not identified  correctly,  1 point is deducted. The next character has a  value  of  2 
points;  the  third  character  has  a  value  of  3  points.  For  the  fourth  character,  5  points  are  deducted, 
and if the highest contrast character is not detectable, 7 points are deducted. 

ii.  Gradient bar of patches with increasing PVs and low-contrast characters 

In the centre of the display, a gradient bar of 18 distinct greyscale steps is drawn, with PVs as used in 
the central rectangle of the AAPM TG18-LN patterns. This bar is horizontal or  vertical but will never 
divide the rectangles with 0% and 100% of the maximum grey level. A randomly chosen character is 
placed on each step of the gradient.  The bar is divided into  2 equally sized parts, a northern and  a 
southern part or a western and  an eastern part. In each part of the gradient bar, each  character is 
unique.  The  characters  are  selected  from  the  same  subset  of  the  Latin  alphabet  as  used  for  the 
selection  of  the  low-contrast  characters.  The  greyscale  value  of  each  character  is  the  same  as  the 
greyscale  value  of  the  preceding  luminance  patch  (Figure 1.10b),  with  the  whitest  and  darkest 
patches at the extremes. 

To evaluate this pattern, characters are to be read starting in the middle and then reading, according 
to the orientation of the bar, towards the west and east or north and south. If a luminance character 
is  visible,  it  is  concluded  that  the  underlying  patch  can  be  clearly  distinguished  from  the  adjacent 
patch. In the AAPM TG18-QC and the DIN test patterns, the purpose of this gradient bar is to verify 
whether  the  different  steps  are  distinguishable.  This  is  most  critical  for  the  lowest  and  highest  PVs. 
When evaluating the MoniQA pattern, only the two last visible characters have to be registered. 

Score criteria: 10 points are deducted for each incorrectly identified or invisible low-luminance patch, 
and this is done for both extremities of the gradient bar. If no character has been identified correctly, 
9 × 10 points are deducted. 

iii.  The  MoniQA  pattern  can  be  used  to  test  geometrical  distortion,  whether  all  pixels  of  the  test 
image  are  shown,  high-  and  low-contrast  spatial  resolution  and  artefacts  (black-to-white  and 
white-to-black transition problems). Any imperfection lowers the score by 5 points, except a dead 
pixel, which lowers the score by 11 points. 

The MoniQA pattern is highly variable. There are 16 combinations of background positions, 4 positions 
for  the  resolution  pattern  inside  each  background  field  and  2  resolution  types  (high-  and  low-
contrast), which means the total number of possible configurations is 128. In addition, there is a very 
large number of combinations of characters for the low-contrast visibility checks. 

Limiting value 
Frequency 
Equipment 

Score obtained from MoniQA pattern should be ≥ 95. 
Daily; optional: weekly. 
MoniQA test pattern. 

2b.4.1.8 

Luminance uniformity 

Limiting value of luminance deviation 

CRT 

LCD 

Test pattern TG18-UNL10    ≤ 30%   ≤ 30% 

Test pattern TG18-UNL80    ≤ 30%   ≤ 15% 

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Figure 1.10:  Examples  of  features  of  the  MoniQA  pattern:  (a) example  of  a  sequence  of 
characters  with  a  low-contrast  luminance  difference  from  the  background; 
(b) gradient  bar  of  patches  with  increasing  pixel  values  and  with  randomly 
selected  characters  with  a  pixel  value  as  in  the  adjacent  patch;  (c) grid 
pattern; (d) corner lines pattern; (e) resolution patterns: (left) high-contrast 
and  (right) low-contrast;  (f) horizontal  and  (g) vertical  version  of  the 
hourglass object (all elements are shown with enhanced contrast for clarity) 

gridlines 

corner lines 

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2b.4.2   Printers 

General  remark:  For  all  test  items  in  this  section,  each  test  pattern  should  be  printed  3  times.  If 
optical  densities  (ODs)  are  to  be  measured,  the  average  OD  from  the  3  prints  should  be  used  for 
further analysis. 

The suggestions for QC made by AAPM Task Group 18 have been adapted slightly. The Task Group 18 
measurements  are  based  on  measuring  OD  of  a  printed  test  pattern.  From  a  QC  point  of  view,  a 
standard  viewing  box  has  been  defined  (luminance  of  the  viewing  box  without  film:  4000 cd/m²; 
luminance  contribution  due  to  ambient  illuminance  reflecting  on  the  printout:  1 cd/m²).  The  ODs  of 
the test pattern should be such that the printout in combination with this virtual viewing box conforms 
to the greyscale standard display function (GSDF). The luminance of the viewing boxes is controlled 
by the tests described in the screen-film section of the fourth edition. 

•  AAPM TG18 patterns must be in DICOM MG format. 

•  AAPM  test  patterns  must  be  printed  from  the  acquisition  workstation  (or  printing  server)  and,  if 

applicable, from the diagnosis workstation. 

•  AAPM test patterns must be printed for all film formats that are used. 

2b.4.2.5  Optical density range 

Print the TG18-PQC test pattern. Measure Dmin and Dmax on this image. 

Limiting value 
Frequency 
Equipment 

Dmin ≤ 0.25 OD, Dmax ≥ 3.60 OD. 
Every 6 months. 
Suitable densitometer, TG18-PQC test pattern. 

2b.4.3 

Viewing boxes 

If mammograms are read on printed images, check the viewing boxes using the method and limiting 
values described in the fourth edition (page 82). 

2b.4.3.1  Ambient lighting level 

The artefacts and loss of image quality associated with reflections from the display surface depend on 
the level of ambient lighting. It is important to verify that the ambient lighting in the room is below 
the maximum limit. The conditions for the tests should be similar to those during normal use of the 
equipment. 

If  mammograms  are  read  on  printed  images,  check  ambient  light  using  the  method  and  limiting 
values described in the fourth edition (page 82). 

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Appendix 5: Tables for determination of average glandular dose 

Most of the data in the following tables are from Dance (1990), Dance et al. (2000), Dance et al.. 
(2009) and Dance et al. (2011). 

Table A5.1:  g-Factors for breasts simulated with PMMA 

PMMA 
thickness 
(mm) 

Equivalent 
breast 
thickness 
(mm) 

Glandularity 
of 
equivalent 
breast 
(%) 

g-factor (mGy/mGy) 

HVL (mm Al) 

0.30  0.35  0.40  0.45  0.50  0.55  0.60  0.65  0.70  0.75  0.80 

20 

30 

40 

45 

50 

60 

70 

80 

21 

32 

45 

53 

60 

75 

90 

103 

97 

67 

41 

29 

20 

9 

4 

3 

0.378  0.421  0.460  0.496  0.529  0.559  0.585  0.609  0.631  0.650  0.669 

0.261  0.294  0.326  0.357  0.388  0.419  0.448  0.473  0.495  0.516  0.536 

0.183  0.208  0.232  0.258  0.285  0.311  0.339  0.366  0.387  0.406  0.425 

0.155  0.177  0.198  0.220  0.245  0.272  0.295  0.317  0.336  0.354  0.372 

0.135  0.154  0.172  0.192  0.214  0.236  0.261  0.282  0.300  0.317  0.333 

0.106  0.121  0.136  0.152  0.166  0.189  0.210  0.228  0.243  0.257  0.272 

0.086  0.098  0.111  0.123  0.136  0.154  0.172  0.188  0.202  0.214  0.227 

0.074  0.085  0.096  0.106  0.117  0.133  0.149  0.163  0.176  0.187  0.199 

Table A5.2:  c-Factors for breasts simulated with PMMA 

PMMA 
thickness 
(mm) 

Equivalent 
breast 
thickness 
(mm) 

Glandularity 
of equivalent 
breast 
(%) 

0.30  0.35  0.40  0.45  0.50  0.55  0.60  0.65  0.70  0.75  0.80 

c-factor* 

HVL (mm Al) 

20 

30 

40 

45 

50 

60 

70 

80 

21 

32 

45 

53 

60 

75 

90 

103 

97 

67 

41 

29 

20 

9 

4 

3 

0.889  0.895  0.903  0.908  0.912  0.917  0.921  0.924  0.928  0.933  0.937 

0.940  0.943  0.945  0.946  0.949  0.952  0.953  0.956  0.959  0.961  0.964 

1.043  1.041  1.040  1.039  1.037  1.035  1.034  1.032  1.030  1.028  1.026 

1.109  1.105  1.102  1.099  1.096  1.091  1.088  1.082  1.078  1.073  1.068 

1.164  1.160  1.151  1.150  1.144  1.139  1.134  1.124  1.117  1.111  1.103 

1.254  1.245  1.235  1.231  1.225  1.217  1.207  1.196  1.186  1.175  1.164 

1.299  1.292  1.282  1.275  1.270  1.260  1.249  1.236  1.225  1.213  1.200 

1.307  1.299  1.292  1.287  1.283  1.273  1.262  1.249  1.238  1.226  1.213 

* for typical breasts for women in the age group 50–64 

Table A5.3:  Typical  HVL  measurements  for  different  tube  voltage  (kV)  and  target/filter 
combinations  (data  include  the  effect  on  measured  HVL  of  attenuation  by  a 
compression plate) 

HVL (mm Al) for target/filter combination 

kV 

Mo Mo 

Mo Rh 

Rh Rh 

W Rh 

W Ag 

0.32 ± 0.02 
0.35 ± 0.02 
0.38 ± 0.02 
0.40 ± 0.02 

0.38 ± 0.02 
0.42 ± 0.02 
0.45 ± 0.02 
0.47 ± 0.02 

0.37 ± 0.02 
0.42 ± 0.02 
0.45 ± 0.02 
0.47 ± 0.02 

0.51 ± 0.03 
0.50 ± 0.03 
0.58 ± 0.03 
0.53 ± 0.03 
0.61 ± 0.03 
0.56 ± 0.03 
0.59 ± 0.03 
0.64 ± 0.03 
0.62 ± 0.03   0.67 ± 0.03 

W Al 
W Al 
(0.5 mm) 
(0.7 mm) 
0.34 ± 0.03  0.42 ± 0.03 
0.39 ± 0.03  0.49 ± 0.03 
0.44 ± 0.03  0.55 ± 0.03 
0.49 ± 0.03  0.61 ± 0.03 
0.53 ± 0.03  0.66 ± 0.03 

25 
28 
31 
34 
37 

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Table A5.4a:  s-Factors for clinically used spectra (Dance et al., 2000) 

Target material 

Filter 
material 

Filter 
thickness 
(µm) 

Mo 

Mo 

Rh 

W 

W 

Mo 

Rh 

Rh 

Rh 

Ag 

30 

25 

25 

50–60 

50–75 

s-factor 

1.000 

1.017 

1.061 

1.042 

1.042 

Table A5.4b:  s-Factors for a tungsten target filtered by 0.5 mm aluminium 

PMMA  
thickness  
(mm) 

Equiv. breast  
thickness 
(mm) 

s-factor 

20 

30 

40 

45 

50 

60 

70 

80 

21 

32 

45 

53 

60 

75 

90 

103 

1.075 

1.104 

1.134 

1.149 

1.160 

1.181 

1.198 

1.208 

Table A5.4c:  s-Factors for a tungsten target filtered by 0.7 mm aluminium. 

PMMA  
thickness  
(mm) 

Equiv. breast  
thickness 
(mm) 

s-factor 

20 

30 

40 

45 

50 

60 

70 

80 

21 

32 

45 

53 

60 

75 

90 

103 

1.052 

1.064 

1.082 

1.094 

1.105 

1.123 

1.136 

1.142 

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Table A5.4d:  s-Factors for a tungsten target filtered by 0.5 mm aluminium 

Breast 
thickness 
(mm) 

Glandularity 
range 
(%) 

Typical 
glandularity, 
age 50–64 
(%) 

Typical 
glandularity, 
age 40–49 
(%) 

kV range 
(kV) 

s-factor 

20 

30 

40 

50 

60 

70 

80 

90 

100 

110 

80–100 

100 

100 

62–82 

40–65 

23–49 

11–35 

2–24 

0.1–17 

0.1–14 

0.1–13 

0.1–13 

72 

50 

33 

21 

12 

7 

4 

3 

3 

82 

65 

49 

35 

24 

14 

8 

5 

5 

25–40 

29–40 

29–40 

30–40 

30–40 

30–40 

30–40 

30–40 

30–40 

30–40 

1.069 

1.104 

1.127 

1.139 

1.154 

1.180 

1.187 

1.198 

1.206 

1.212 

Table A5.4e:  s-Factors for a tungsten target filtered by 0.7 mm aluminium 

Breast 
thickness 
(mm) 

Glandularity 
range 
(%) 

Typical 
glandularity, 
age 50–64 
(%) 

Typical 
glandularity, 
age 40–49 
(%) 

kV range 
(kV) 

s-factor 

20 

30 

40 

50 

60 

70 

80 

90 

100 

110 

80–100 

100 

100 

62–82 

40–65 

23–49 

11–35 

2–24 

0.1–17 

0.1–14 

0.1–13 

0.1–13 

72 

50 

33 

21 

12 

7 

4 

3 

3 

82 

65 

49 

35 

24 

14 

8 

5 

5 

25–50 

25–50 

25–50 

25–50 

25–50 

28–50 

28–50 

28–50 

28–50 

28–50 

1.052 

1.060 

1.076 

1.087 

1.105 

1.121 

1.129 

1.136 

1.140 

1.144 

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Table A5.5:  Additional g-factors 

HVL 
(mm Al) 
0.30 
0.35 
0.40 
0.45 
0.50 
0.55 
0.60 
0.65 
0.70 
0.75 
0.80 

Breast thickness (mm) 
3 
2.74 
3.09 
3.42 
3.74 
4.06 
4.37 
4.66 
4.91 
5.14 
5.35 
5.55 

4 
2.07 
2.35 
2.61 
2.89 
3.18 
3.46 
3.74 
3.99 
4.21 
4.41 
4.60 

2 
3.90 
4.33 
4.73 
5.09 
5.43 
5.73 
5.87 
6.22 
6.44 
6.63 
6.82 

5 
1.64 
1.87 
2.09 
2.32 
2.58 
2.87 
3.10 
3.32 
3.52 
3.71 
3.89 

6 
1.35 
1.54 
1.72 
1.92 
2.14 
2.36 
2.61 
2.82 
3.00 
3.17 
3.33 

7 
1.14 
1.30 
1.45 
1.63 
1.77 
2.02 
2.24 
2.44 
2.59 
2.74 
2.89 

8 
0.98 
1.12 
1.26 
1.40 
1.54 
1.75 
1.95 
2.12 
2.27 
2.41 
2.54 

9 
0.859 
0.981 
1.106 
1.233 
1.357 
1.543 
1.723 
1.879 
2.017 
2.143 
2.270 

10 

11 

0.763  0.687 
0.873  0.786 
0.986  0.887 
1.096  0.988 
1.207  1.088 
1.375  1.240 
1.540  1.385 
1.682  1.520 
1.809  1.638 
1.926  1.746 
2.044  1.856 

The table is in units of mGy/mGy. 
Additions to the table in Dance et al. (2000) are highlighted in grey. 

Table A5.6:  Additional c-factors for average breasts for women in the age group 50–64 

0.9 

Breast 
thickn.  Gland.  HVL (mm Al) 
(mm) 
20 
30 
40 
50 
60 
70 
80 
90 
100 
110 

(%) 
100 
72 
50 
33 
21 
12 
7 
4 
3 
3 

0.30  0.35  0.40  0.45  0.50  0.55  0.60  0.65  0.70  0.75  0.80 
0.885  0.891 
0.905  0.91  0.914  0.919  0.923  0.928  0.932  0.936 
0.925  0.929  0.931  0.933  0.937  0.94  0.941  0.947  0.950  0.953  0.956 
1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000  1.000 
1.086  1.082  1.081  1.078  1.075  1.071  1.069  1.064  1.060  1.057  1.053 
1.164  1.160  1.151  1.15  1.144  1.139  1.134  1.124  1.117  1.111  1.103 
1.232  1.225  1.214  1.208  1.204  1.196  1.188  1.176  1.167  1.157  1.147 
1.275  1.265  1.257  1.254  1.247  1.237  1.227  1.213  1.202  1.191  1.179 
1.299  1.292  1.282  1.275  1.27 
1.26  1.249  1.236  1.225  1.213  1.200 
1.307  1.298  1.29  1.286  1.283  1.272  1.261  1.248  1.236  1.224  1.211 
1.306  1.301  1.294  1.291  1.283  1.274  1.266  1.251  1.240  1.228  1.215 

Additions to the table in Dance et al. (2000) are highlighted in grey. 

Table A5.7:  Additional c-factors for average breasts for women in the age group 40–49 

0.9 

Breast 
thickn.  Gland.  HVL (mm Al) 
(mm) 
20 
30 
40 
50 
60 
70 
80 
90 
100 
110 

(%) 
100 
82 
65 
49 
35 
24 
14 
8 
5 
5 

0.30  0.35  0.40  0.45  0.50  0.55  0.60  0.65  0.70  0.75  0.80 
0.905  0.91  0.914  0.919  0.923  0.928  0.932  0.936 
0.885  0.891 
0.894  0.898  0.903  0.906  0.911  0.915  0.918  0.924  0.928  0.933  0.937 
0.940  0.943  0.945  0.947  0.948  0.952  0.955  0.956  0.959  0.961  0.964 
1.005  1.005  1.005  1.004  1.004  1.004  1.004  1.004  1.003  1.003  1.003 
1.080  1.078  1.074  1.074  1.071  1.068  1.066  1.061  1.058  1.055  1.051 
1.152  1.147  1.141  1.138  1.135  1.130  1.127  1.117  1.111  1.105  1.098 
1.220  1.213  1.206  1.205  1.199  1.190  1.183  1.172  1.163  1.154  1.145 
1.270  1.264  1.254  1.248  1.244  1.235  1.225  1.214  1.204  1.193  1.181 
1.295  1.287  1.279  1.275  1.272  1.262  1.251  1.238  1.227  1.215  1.203 
1.294  1.290  1.283  1.281  1.273  1.264  1.256  1.242  1.232  1.220  1.208 

Additions to the table in Dance et al. (2000) are highlighted in grey. 

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Appendix 7: Linear system theory metrics and a practical guide to 

their measurement (optional) 

A7.1  Modulation transfer function (MTF), noise power spectrum (NPS) and detective 

quantum efficiency (DQE) 

Linear  system  theory  metrics  offer  reproducible,  objective  estimates  of  X-ray  detector  noise  and 
resolution  properties  and  are  sensitive  to  changes  in  detector  performance  over  time.  The 
International  Electrotechnical  Commission  (IEC)  standard  62220-1-2  describes  the  measurement  of 
these parameters (IEC, 2004). However, this document is intended for use by the manufacturers; they 
can  remove  the  X-ray  detector  from  the  system  and  perform  a  separate  bench  test.  This  is  not 
possible  for  detectors  in  clinical  use  and  hence  a  pragmatic  approach,  suitable  for  routine  QC 
conditions, is presented here. Measurement geometry is likely to vary between systems, resulting in a 
loss of generality, and hence caution must be exercised when using these metrics to compare across 
systems.  However,  measured  with  care,  these  parameters  offer  significant  insight  into  the 
performance of an individual detector; they can isolate performance changes over time and are useful 
when  troubleshooting  the  entire  imaging  chain.  Definitions  of  the  equations  used  to  calculate  these 
parameters  are  given  in  the  recommended  literature;  a  firm  grasp  of  the  theory  underlying  these 
parameters is required before performing these measurements. Given that many QC physicists will not 
have  the  time  to  develop  the  required  software,  validated/verified  software  can  be  used  for  the 
calculations. 

The  IEC  document  prescribes  standard  measurements  to  be  performed  at  ‘the  detector  surface’ 
(defined  as  ‘the  accessible  area  which  is  closest  to  the  image  receptor  plane’);  for  routine  QC 
measurements,  there  will  be  additional  non-removable  parts  (e.g.  breast  support  table,  antiscatter 
grid  and/or  detector  covers)  in  the  X-ray  beam  during  the  measurement.  With  this  in  mind,  a 
consistent  geometry  should  be  used  for  a  given  system/model.  When  comparing  quantitative 
measurements from different physics centres, the data acquisition conditions must be stated explicitly 
for  the  sake  of  transparency.  These  include  the  geometry  (position  of  antiscatter  grid  and  breast 
support table, use of collimation/field area), beam energy and detector air kerma, along with the data 
conditioning  parameters  used  in  the  calculation  of  the  MTF  and  NPS  (ROI  dimensions,  de-trending 
used, sectioning, etc.). 

A7.2 

Image type 

The first step is to identify/select ‘for processing’ images on the system. These are images that have a 
fixed  gain  between  detector  output  signal  and  air  kerma  at  the  detector  (no  ‘autoranging’  of  the 
signal) and have minimal additional processing. For example, DR systems will generally apply detector 
offset and gain corrections together with pixel corrections; this is acceptable. Processing such as edge 
enhancement  or  proprietary  image  processing  that  prepares  images  ‘for  display’  etc.  must  be 
disabled/not used. These image types are sometimes listed as a specific ‘series’ and ‘study description’ 
by the manufacturer. 

A7.3  Collimation of X-ray field 

Collimation can be used to reduce the influence of scattered radiation on the measurements. The use 
of  collimation  represents  good  practice  but  may  be  time-consuming  to  set  accurately  during  routine 
QC  (depending  on  the  collimation  type  available).  If  collimation  is  used,  a  field  area  of  100 mm  × 
100 mm should be set at the beginning of the tests and kept in place for all the measurements (air 
kerma, detector response, NPS, MTF). Figure A7.1 shows suggested positioning of the collimation. 

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Figure A7.1:   Position of the collimation – if used, this should be in place for all the    

  measurements 

A7.4  Detector response function 

Quantitative analysis requires the measurement of the detector response function, relating air kerma 
at the detector input plane to pixel value (PV). This is used for linearization of the images from which 
the quantitative image quality metrics are calculated. Measurement of the detector response requires 
an estimate of the air kerma at the detector entrance plane. 

For this measurement, set the same X-ray spectrum as used for a standard image, and place 2 mm Al 
at the X-ray tube. Remove the compression plate from the X-ray beam, protect the X-ray detector and 
measure air kerma as a function of mAs. Sample low mAs settings more finely because mAs linearity 
can be worse at low mAs values; furthermore, it is likely that low mAs values will be used in images 
for  NPS  estimation,  given  the  filter  efficiency/transmission  of  2 mm  Al.  Calculate  air  kerma  at  the 
detector  (K),  applying  an  inverse  square  law  correction  to  obtain  the  values  at  the  level  of  the 
detector, and apply a grid transmission factor (use a factor appropriate for the geometry) if the grid is 
not  removed.  Fit  a  first-order  polynomial  function  and  confirm  linearity  of  K  with  mAs;  carefully 
examine mAs linearity at low mAs settings. Use this equation to calculate the mAs values needed for a 
range  of  detector  air  kerma  values,  e.g.  12.5,  25,  50,  100,  200,  400  and  800 μGy.  This  will  enable 
testing of the detector at a fixed air kerma level for the lifetime of the detector and allow changes in 
performance to be tracked. Remove the grid,  set the calculated mAs values (closest mAs station on 
the system) and acquire uniformly exposed (flood) images over the air kerma range. Measure PV and 
standard  deviation  at  the  standard  position  using  the  standard  ROI  size.  Plot  PV  vs  K,  fit  the 
appropriate  curve  for  the  system  type  (linear,  logarithmic  or  power)  and  record  the  fit  parameters. 
This  function  is  used  to  linearize  the  PV  data  on  a  pixel-wise  basis  in  the  edge  and  flood  images 
before calculating MTF and NPS. This must be done for all systems, even systems that produce linear 
‘for processing’ images. After this step, the linearized images will have unity gain and zero offset (the 
mean PV in this image should be equal to the air kerma used to acquire the image). 

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A7.5  Noise power spectrum (NPS) 

The  NPS  describes  the  variance  of  an  image  intensity  (image  PV)  divided  among  its  frequency 
components  and  is  calculated  from  ROIs  taken  from  a  region  of  a  uniformly  exposed  image.  In 
practice, the NPS is calculated using: 

NPS

vu
),(

=

∆∆
yx
⋅
256

M

⋅

256

M

256

256

∑ ∑∑

m

=
1

i

=
1

j

=
1

((
yxI
i

,

j

)

−

))
eyxS

,(

2

−

π
(2

xui
in

+

yv
k

j

)

(A7.1) 

where an ROI dimension of 256 × 256 pixels has been used. Here, M is the number of ROIs, Δx is the 
pixel spacing in the x direction, Δy is the pixel spacing in the y direction, I(xi,yj) are the (linearized) 
pixel data, S(x,y) is a 2-dimensional polynomial function fitted to the entire extracted region used for 
NPS analysis (not to the individual ROIs). 

Select  a  flood  image  acquired  at  some  reference  detector  air  kerma,  e.g.  at  50  or  100 μGy,  and 
calculate the NPS for this region. Use an image acquired at the same air kerma throughout the life of 
the detector. Linearize the image using the detector response curve. IEC 62220-1 defines an area of 
50 mm  ×  50 mm  for  the  NPS  estimation,  divided  into  ROIs  of  256  ×  256 pixels  that  overlap  each 
other by 128 pixels. This strictly limits the physical region from which the NPS is calculated, reducing 
the effects of non-stationarity and large area non-uniformity on the NPS; however, several images are 
required  to  increase  the  number  of  spectra  in  the  ensemble  and  hence  reduce  uncertainty  of  the 
spectral estimate. For QC purposes, a region of 100 mm × 100 mm can be used and ROIs of 256 × 
256 pixels taken from this area. To reduce statistical uncertainty, the spectra from several identically 
acquired  images  can  be  averaged.  It  is  recommended  that  a  2-dimensional  polynomial  function  be 
fitted to and subtracted from the 100 mm × 100 mm area before extraction of the ROIs of 256 × 256 
pixels. The final spectrum is sectioned from the ensemble. For systems with an isotropic NPS, this can 
be a radial average; for detectors with a non-isotropic NPS, the spectra sectioned from the 0° and 90° 
axes should be recorded separately. The axes (0° and 90° spatial frequency bins) contain information 
about  the  axial  structured  noise  of  the  detector/image  and  should  be  included  in  the  spectral 
estimate. The spectral ensemble (averaged over the number of individual spectra in the ensemble) is 
then normalized to give the normalized noise power spectrum (NNPS) by dividing by the mean PV of 
the  linearized  flood  image  used  to  calculate  the  spectral  estimate,  i.e.  by  dividing  by  the  air  kerma 
used to acquire the flood image. 

The IEC standard specifies the use of collimation of 100 mm × 100 mm when acquiring the flood and 
edge  images,  to  control  the  quantity  of  the  scattered  radiation  in  the  image.  A  higher  quantity  of 
scattered radiation effectively leads to a higher detector air kerma per image and hence an increased 
NPS. Whereas collimation is essential for laboratory detector measurements, the value of collimation 
in a QC setting is limited and it should be considered optional (the collimation is heavy, and exactly 
the same collimator dimension must be used across QC visits). 

The  antiscatter  grid  can  influence  the  measured  NPS  in  several  ways.  First,  the  grid  can  introduce 
structured noise, predominantly of low spatial frequencies, which is often seen along the 0° and 90° 
NPS axes. Structured noise is multiplicative in nature and increases relative to other noise sources as 
detector  air  kerma  is  increased.  The  spatially  periodic  nature  of  the  grid  can  also  introduce  spikes, 
indicating  increased  noise  power  at  distinct  spatial  frequencies;  this  may  indicate  a  grid  motion 
problem.  For  example,  a  linear  grid  with  30  lines cm–1  will  generate  spikes  at  3.0 mm–1  (and 
associated  harmonics)  in  the  NPS;  these  will  be  seen  on  the  axis  (0°  or  90°)  that  is  parallel  to  the 
direction of grid movement in the image. 

The presence of the antiscatter grid in the X-ray beam during detector calibration presents a further 
complication. Some systems may have flat-field  corrections explicitly  for the case of grid in and grid 

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out of the X-ray beam, whereas others may have a single flat-field correction which presumes that the 
grid  is  present.  For  this  latter  system  type,  an  ‘imprint’  of  the  flat-field  correction  will  be  applied  to 
flood  images  that  have  been  acquired  with  the  grid  removed,  leading  to  a  potential  increase  in  the 
structured noise present in the image and hence in the NPS. 

Record  the  NPS  at  0.5 mm–1  and  2.0 mm–1  (either  a  radial  average  or  the  0°  and  90°  axis  values 
separately). 

Limiting value 

Frequency 
Equipment 

Expect ≤ ±15% change in NPS at 0.5 mm–1 and 2.0 mm–1 from previous QC 
visit value and from baseline. 
Every 6 months. 
2 mm  Al  filter  (minimum  99%  purity),  calibrated  dose  meter,  software  for 
calculating objective image quality parameters. 

A7.6  Pre-sampled modulation transfer function 

The MTF describes the spatial frequency response of a linear, spatially invariant imaging system and is 
typically determined using  a slanted radio-opaque edge placed at the detector input plane, a robust 
technique suitable for routine QC. This method generates the detector pre-sampled MTF, a parameter 
that describes the blurring due to the detector pixel aperture and the X-ray converter layer. The pre-
sampled  MTF  is  measured  in  two  directions  across  the  detector:  the  left-right  and  front-back  (chest 
wall-nipple) directions. A stainless steel square of thickness 0.8 mm and dimensions 60 mm × 60 mm 
can be used; the provisos are that the edges must be sharp and straight and the edge must be radio-
opaque.  If  the  edge  is  not  radio-opaque,  then  scattered  radiation  can  influence  the  edge  spread 
function  (ESF)  and  hence  the  MTF.  Alternative  materials  can  be  used,  such  as  niobium,  tantalum, 
tungsten,  lead,  etc.  However,  the  edge  must  be  of  sufficient  thickness  (radio-opaque)  and  the 
material should not generate large quantities of characteristic radiation that may influence the ESF. 

The  pre-sampled  MTF  is  calculated  from  a  finely  sampled  (‘over-sampled’)  ESF,  generated  by  re-
binning  or  re-projecting  the  (linearized)  PV  data  in  some  region  containing  the  edge.  The  over-
sampled ESF is differentiated to generate the line spread function (LSF): 

LSF (x) =    ESF(x) 

d 
dx 

         (A7.2) 

The  pre-sampled  MTF  is  obtained  from  the  LSF  by  using  the  fast  Fourier  transform  (FFT)  and 
calculating the magnitude: 

MTF = |F[LSF(x)]| 

         (A7.3) 

With  regard  to  practical  measurements,  set  the  same  beam  quality  as  used  to  acquire  the  flood 
images  and  an  mAs  setting  to  produce  an  air  kerma  at  the  detector  that  is  approximately  3×  the 
typical K value for AEC images. There must be no saturation in the high-signal region of the ESF, and 
there must be no clipping or truncation to zero linearized PV in the low-signal region of the ESF. This 
is  generally  achieved  by  ensuring  that  the  PVs  in  the  edge  image  (before  linearization)  all  lie  within 
the  range  covered  by  the  detector  response  function.  Place  the  edge  on  the  breast  support  table 
(‘detector  surface’)  with  an  approximate  angle  of  1°  to  3°  with  respect  to  the  pixel  matrix.  In  a  full 
evaluation,  4  edge  images  are  acquired,  positioned  to  measure  the  MTF  at  the  lateral  centre  of  the 
detector  and  at  6 cm  from  the  chest  wall  edge  (Figure A7.2).  An  MTF  is  calculated  for  each 
acquisition: the left-right direction (low to high signal and high to low signal changes for the ESF) and 
similarly for the chest wall-nipple direction. The final MTF is an average of the two edge orientations; 

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e.g.  the  left-right  MTF  would  be  averaged  from  the  0°  and  180°  edge  orientations  in  Figure A7.2. 
Extract  a  sufficiently  large  region  containing  the  edge  such  that  glare  (low-frequency  signal  spread) 
within  the  detector  is  characterized.  The  actual  ROI  dimension  will  depend  on  the  characteristic 
distance  of  the  glare;  however,  an  ROI  of  at  least  40 mm  ×  40 mm  should  be  used.  Linearize  the 
image  PV  data  before  calculating  the  MTF.  Note  the  conditioning  applied  when  obtaining  the  MTF 
result (smoothing, windowing, extrapolation of the LSF tails, etc.). 

Figure A7.2:  Positions of the edge for MTF measurement (any additional collimation that 

may be used is not shown) 

If a metal square with at least two sharp, straight edges is available, then the MTF can be calculated 
from a single image for the two detector directions, although in this case the MTF will be evaluated at 
different positions on the detector. This is acceptable for routine QC measurements. 

Corrections for non-uniformity in the MTF image can be applied to remove low-frequency trends using 
a  uniformly  exposed  image  (i.e.  with  the  edge  removed)  acquired  with  exactly  the  same  technique 
factors, although great care must be taken when making this kind of correction. As with the NPS, the 
X-ray  beam  can  be  collimated  to  100 mm  ×  100 mm  to  reduce  scattered  radiation,  although  this  is 
optional for QC measurements. 

Record the spatial frequencies at which the MTF reaches 50% (left-right and chest wall-nipple direc-
tions). 

Limiting value 
Frequency 
Equipment 

Expect ≤ ±10% change in the spatial frequency for the 50% MTF point. 
Every 6 months. 
Radio-opaque edge of minimum dimensions 60 mm × 60 mm with sharp and 
straight edges, 2 mm Al filter, calibrated dose meter, software for    
calculating objective image quality parameters. 

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A7.7  Detective quantum efficiency (DQE) 

The  DQE  describes  the  degradation  of  the  input  SNR  by  the  X-ray  detector  due  to  detection, 
conversion  and  amplification  of  the  X-ray  signal.  DQE  is  defined  as  the  square  of  the  ratio  of  the 
detector output SNR to the SNR at the detector input. It is common to compare the detector against a 
perfect photon counting device, and hence the reference SNR at the detector input is the number of 
X-ray photons per unit area (mm–2). 

DQE

u
)(

=

(
K

a

2

MTF
)
2

SNR
in

u
)(
NNPS

         (A7.4) 

u
)(

This  equation  is  given  for  the  1-dimensional  case; MTF(u)  is  the  pre-sampled  MTF, NNPS(u)  is  the 
2 is the number of X-
measured NNPS, Ka is the estimated air kerma at the detector surface and SNRin
2 gives the total number of X-
ray photons µGy–1 mm–2 for the beam quality used. Hence, Ka × SNRin
ray photons mm–2 at the detector input. Table A7.1a gives SNRin
2 for some typical spectra (with added 
2 mm Al at the X-ray tube) used by current X-ray systems, as provided also by IEC 62220-1. The data 
2 for spectra that are not 
of Boone and colleagues (Boone et al., 1997) can be used to calculate SNRin
included in the IEC standard, using the formula: 

SNR
in

2

=

∫

Φ

)

(
,
VE
K

a

dE

(A7.5) 

where Φ(E,V) is the photon fluence at energy E when a tube voltage V is applied. Table A7.1b gives 
SNRin

2 values for some other spectra, calculated according to Boone et al. (1997). 

MTF and NPS are sensitive image quality parameters and are sufficient to track  changes in detector 
performance  for  QC  purposes.  The  DQE  is  an  important  image  quality  metric  when  comparing  the 
absolute  performance  of  detectors,  either  of  a  similar  type  or  between  manufacturers.  However, 
calculation of the DQE requires an accurate estimate of the air kerma at the detector input plane and 
the true number of photons per unit air kerma for the photon spectrum used.  Both of these  can be 
difficult to achieve in practice. The DQE can be compared against manufacturer reference data. 

Limiting value 
Frequency 
Equipment 

None. 
Every 6 months. 
2 mm Al filter, calibrated dose meter, software for calculating objective image 
quality parameters, spectral modelling tool. 

Table A7.1a:   Number of photons µGy–1 mm–2 (SNRin

2) for 2 mm Al according to IEC   

standard 62220-1-2 

Tube 
potential (kV) 

Anode 

System filter 

28 
28 
28 
28 
28 

Mo 
Mo 
Rh 
W 
W 

Mo (32 µm) 
Rh (25 µm) 
Rh (25 µm) 
Rh (50 µm) 
Al (500 µm) 

2 

SNRin
(µGy–1 mm–
2) 
4981 
5439 
5944 
5975 
6575 

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Table A7.1b:    Number of photons µGy–1 mm–2 (SNRin2) for 2 mm Al according to Boone 
et al. (1997) for some spectra not included in the IEC standard 

Tube 
potential (kV) 

Anode 

System filter 

29 
35 
32 

Rh 
W 
W 

Rh (25 µm) 
Al (500 µm) 
Ag (50 µm) 

2 

SNRin
(µGy–1 mm–
2) 
6248 
8823 
7143 

Further reading 
The  following  publications  are  recommended  for  further  reading:  Cunningham  (2000),  Neitzel  et  al. 
(2004),  Carton  et  al.  (2005),  Dobbins  et  al.  (2006),  Samei  et  al.  (2006),  Marshall  (2007),  Marshall 
(2009a), Marshall (2009b) and Mackenzie et al. (2010). 

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Appendix 8: Description of CDCOM version 1.6 

A8.1  The CDMAM phantom 

The  CDMAM  phantom  was  designed  to  derive  contrast-detail  visibility  threshold  information  for 
mammography systems by conducting four alternative forced choice (4-AFC) experiments. It contains 
a grid marking of 205 cells, and each cell contains one gold disc at the centre and one disc in one of 
the  corners  (Figure A8.1).  The  corner  in  which  a  disc  is  located  varies  randomly  between  cells.  The 
combination  of  disc  diameter  and  thickness  is  unique  to  each  cell.  A  total  of  16  different  diameters 
and  16  different  thicknesses  are  present  in  the  phantom  (Bijkerk  et  al.,  2001;  Bijkerk  et  al.,  2002). 
The CDMAM phantom is built up as an aluminium base on which the gold discs have been deposited 
by  evaporation.  The  base  is  attached  manually  to  a  PMMA  cover,  which  contains  the  grid  lines  and 
information about disc thickness and diameter (Figure A8.2). 

After imaging the CDMAM phantom, the 4-AFC experiment is conducted by asking observers to mark 
the corner of each individual cell containing a gold disc. Afterwards, the observer output is compared 
with the true disc locations. This produces a grid with ‘true’ and ‘false’ scores. To reduce the impact of 
isolated true or false scores in the matrix, a nearest neighbour correction scheme should be applied 
on this matrix before the detection threshold is derived for each diameter. 

Combining  these  detection  thresholds  for  multiple  readers  and  images  for  each  disc  diameter 
produces  the  contrast-detail  threshold  information  (Figure A8.3).  For  more  detailed  information,  see 
Young et al. (2006) and Young et al. (2008). 

Figure A8.1:  The CDMAM phantom 

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Figure A8.2:  The aluminium base contains the gold discs of the CDMAM phantom; the  

PMMA cover contains the grid lines 

Figure A8.3:  Example of human readout of the CDMAM phantom after nearest neighbour 

correction 

A8.2  Disadvantages of human readout of the CDMAM phantom 

Human readout of the CDMAM phantom does have several disadvantages: 

•  The reading of images is time-consuming. 

•  Due  to  the  long  reading  time,  in  practice  only  small  numbers  of  images  and  readers  are  used, 

which decreases reliability. 

• 

• 

Inter-reader variability, the variation in phantom image score from reader to reader. 

Intra-reader variability, the variation in phantom image score by one reader. 

•  There is a learning effect: readers may know the positions of the discs by heart. This influences 

their score. 

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•  The nearest neighbour correction may not be the best scheme to obtain contrast-detail curves. 

To eliminate and reduce these disadvantages, computer readout of CDMAM phantom images has been 
introduced. 

A8.3  CDCOM 

CDCOM is a software tool developed to automate the tasks of reading CDMAM  version  3.4 phantom 
images and generating score sheets. CDCOM does not read CDMAM version 3.2 images. CDCOM 
does not aim to predict human readout, however. Instead, it tries to use the information present in 
the image more optimally to conduct a 4-AFC experiment. The results of CDCOM can therefore not be 
used  directly  in  combination  with  contrast-detail  visibility  limits  set  for  human  observers.  In 
Section 2b.2.4.1 of this protocol, the procedure is given to predict results for human observers from 
CDCOM  results.  To  download  software  for  automated  readout  of  CDMAM  images,  see  Visser  & 
Karssemeijer (2012). 

The automated image analysis by CDCOM can be separated into five phases: 

•  Analysis of the DICOM header 

•  Transformation to a standardized input 

•  Grid detection 

•  Phantom-specific and image-specific corrections 

• 

Individual disc detection. 

A8.4  Analysis of the DICOM header 

CDCOM needs the following elements in the DICOM header to correctly assess the image: 

• 

• 

• 

• 

• 

• 

• 

(0018,1164)  Imager  Pixel  Spacing  (used  only  as  an  initial  estimator  of  image  scale).  If  not 
present, use (0028,0030) Pixel Spacing. 

(0028,0010) Rows 

(0028,0011) Columns 

(0028,0100) Bits Allocated 

(0028,0101) Bits Stored 

(0028,1041)  Pixel  Intensity  Relationship  Sign  (used  to  facilitate  grid  detection;  can  be  overruled 
by manual selection). If not present, use (0028,0004) Photometric Interpretation. 

(7fe0,0010) Pixel Data. 

A8.5  Transformation to a standardized input 

The images of the CDMAM phantom are read by CDCOM and are transformed to a standardized form: 
(1) the image is cropped to the image of the phantom, (2) the image is rotated to the standardized 
orientation and (3) the image is scaled to a pixel size of 50 µm. This step is performed to eliminate 
differences  in  the  detection  of  discs  within  the  search  area  for  images  with  different  pixel  size  (see 
Section A8.8, Individual disc detection). 

A8.6  Grid detection 

As  is  the  case  for  the  human  observer,  the  gridlines  are  used  as  a  reference  for  global  positioning. 
First, a linear Hough transform is performed at a reduced resolution of 400 µm per pixel, allowing the 
position  of  the  gridlines  to  be  detected  as  two  sets  of  equidistant  maxima  in  Euclidian  space 
(Figure A8.4a).  The  cell  corners  can  be  calculated  as  the  points  where  two  gridlines  intersect.  Next, 

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the  locations  of  the  corners  of  each  cell  are  determined  more  accurately  by  applying  template 
matching  (Figure A8.4b)  to  the  area  around  the  approximate  locations  of  each  cell  corner.  In  this 
procedure,  the  template  of  the  line  crossing  at  the  estimated  position  is  correlated  with  the  image 
data within a small area (21 × 21 pixels) around the predicted crossing. The location with the highest 
cross-correlation  is  the  optimal  location  of  the  crossing.  This  step  prevents  image  deformations 
(geometrical  distortion),  e.g.  caused  by  a  concave  bucky  shape,  from  influencing  the  results.  No 
special  template  for  the  (partial)  crossing  at  the  boundaries  is  used;  hence,  this  procedure  may 
occasionally  fail.  Therefore,  the  consistency  of  the  final  result  must  be  checked.  If  an  outlying 
boundary  crossing  is  found,  this  is  corrected  by  interpolation  from  surrounding  points  (Veldkamp  et 
al., 2003). 

Figure A8.4a:  Example of the result of a Hough transformation of a CDMAM image. The  

grid can be recognized as two columns with equidistant local maxima 

Figure A8.4b:  Template matching: in an area of 21 × 21 pixels around the predicted   

crossing, the cross-correlation of the image with a template is determined 

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A8.7  Phantom-specific and image-specific corrections 

CDCOM  performs  a  4-AFC  experiment  with  an  ideal  observer  model.  It  is  based  on  the  assumption 
that  for  each  disc  (with  known  diameter)  there  are  four  possible  positions  (yellow  circles  in 
Figure A8.5), of which the possible locations are exactly known. In practical situations, however, there 
will always be some inaccuracy in the determination of these positions (through human and computed 
observations)  caused  by  the  production  process  of  the  phantom,  the  geometrical  distortion  of  the 
phantom  image  and  the  limited  resolution  of  the  imaging  system.  Therefore,  CDCOM  needs  to  vary 
slightly  by  applying  the  model  observer  in  a  search  region  around  each  calculated  (theoretical) 
position (purple circles in Figures A8.5 and A8.6). It is crucial to understand that increasing the size of 
the search region will increase the influence of the image noise at the disc detection step. Therefore, 
increasing the search region will result in deterioration of the detection results, especially for smaller 
diameters. To limit the influence of the noise specific to every individual image, the disc search region 
has to be kept as small as possible, while avoiding the possibility of missing (part of) the disc under 
investigation. 

Figure A8.5:  Schematic illustration of the calculated disc positions (yellow inner circles) 

and the disc search areas defined around them (purple outer circles) 

To avoid having to increase the search region, an estimate of the phantom-specific and image-specific 
translation, rotation and scaling is made by analysing the position of all easily detectable centre discs 
(large  diameter  and  high  contrast)  using  a  relatively  large  search  area  of  500  μm2.  A  template  with 
the correct positions of all discs is rotated, translated and scaled to match the easily detectable discs, 
and  calculated  positions  of  all  discs  are  obtained.  Using  a  search  area  of  200  μm2  around  the 
calculated disc positions has proven to give reliable results (Visser et al., 2005). 

A8.8 

Individual disc detection 

Due  to  the  phantom-specific  correction  of  the  calculated  disc  positions,  the  disc  search  area  for 
individual disc detection can be limited to 200 µm2 around the calculated positions. Within this search 
area, the location in which a disc of the specified size is most likely to be located is determined. 

This  is  done  by  finding  the  (by  approximation)  disc-shaped  area  that  has  the  lowest  or  highest 
(depending  on  the  image  properties)  total  PV;  see  Figure A8.6a.  In  Figure A8.6b,  the  template  is 
shown that is used to detect the circular discs on the phantom image. Due to the digital nature of the 
image,  the  shape  of  the  circle  is  approximated  by  the  template.  This  approximation  would  not  be 
equal for different pixel sizes and would introduce differences in detection of the disc. Therefore, the 
CDMAM image is rescaled to a pixel size of 50 µm (see Section A8.5). 

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Figure A8.6:   Individual  disc  detection:  (left)  the  disc  search  areas  in  each  of  the  cell 
corners  (purple  outer  circles)  and  the  positions  within  each  search  area 
(blue  inner  circles)  where  the  disc  is  most  likely  to  be  located  (based  on 
total  pixel  value);  (right)  close-up  of  the  detection  (blue  inner  circle)  of  a 
0.5 mm disc within a search area (purple outer circle) 

The  average  values  of  the  pixels  in  the  four  locations  are  then  compared  to  decide  which  corner  is 
most likely to contain the gold disc by determining the corner with the highest (or lowest, in the case 
of pixel values decreasing with higher object density) pixel value. If the corner selected is the corner 
actually containing the disc, CDCOM has correctly detected the disc; otherwise, it failed to detect it. 

This process is repeated for the centre disc together with the 3 corners not containing a disc to obtain 
a second phantom image reading. 

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Appendix 9: Significance of test items 

The test items described in the digital section of the European protocol for the quality control of the 
physical and technical aspects of mammography screening in the  fourth edition and in Part 1  of the 
supplement  to  the  digital  section  can  be  divided  into  four  categories:  (1) essential  test  items,  which 
must be measured; (2) desirable test items, which should be measured; (3) optional test items, which 
could be measured and (4) test items that have been omitted in the supplement. This last  category 
consists  of  (a)  test  items  that  have  been  proven  to  be  of  low  importance,  (b)  test  items  that  are 
(indirectly)  covered  by  other  tests  and  (c)  test  items  that  are  difficult  to  measure  by  individual 
physicists and are covered by the supplier/manufacturer when installing a system. 

Essential test items: 

2b.2.2.1.1  Response function/2b.2.2.1.2 Noise evaluation 
2b.2.1.3.3  AEC short-term reproducibility 
2b.2.1.3.4  AEC long-term reproducibility (weekly/daily QC) 
2b.2.1.3.5  AEC Breast thickness and composition compensation 
2b.2.2.3.1  Image receptor homogeneity  
2b.2.3   
2b.2.4.1  Threshold contrast visibility 
2b.2.4.5  Ghost image/erasure thoroughness 

Dosimetry (requires 2b.2.1.2.2 Half value layer) 

Desirable test items: 

2b.2.1.2.1  Tube voltage 
2b.2.1.3.1  Exposure control steps (if applicable) 
2b.2.1.3.2  Back-up timer and security cut-off 
2b.2.1.3.6  Local dense area 
2b.2.1.4  Compression 
2b.2.2.2  Missed tissue at chest wall side 
2b.2.2.3.2  Detector element failure 
2b.2.2.4 
2b.2.4.3 

Interplate sensitivity variations 
Exposure time 

Optional test items: 

2b.2.1.1.3  Alignment of X-ray field/image area 
2b.2.1.1.5  Tube output 
2b.2.4.2  Modulation  transfer  function  (MTF),  noise  power  spectrum  (NPS)  and  detective  quantum 

efficiency (DQE) 

Omitted test items: 

2b.2.1.1.1  Focal spot size 
2b.2.1.1.2  Source-to-image distance 
2b.2.1.1.4  Radiation leakage 
2b.2.1.5.1  Grid system factor 
2b.2.1.5.2  Grid imaging 
2b.2.2.5 
2b.2.2.6 

Influence of other sources of radiation 
Fading of latent image 

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digital mammography. Med. Phys., 30:1712–1718. 

Visser  R,  Beckers  B,  Gennaro  G,  Baldelli  P,  van  Engen  R  (2005).  Comparison  of  individual  CDMAM 
phantoms  using  automated  image  analysis.  In: Proceedings of the International Workshop in Digital 
Mammography (IWDM 2004). University of North Carolina, Chapel Hill, NC, pp. 123–130. 

Visser  R,  Karssemeijer  N  (2012).  CDCOM  Manual:  software  for  automated  readout  of  CDMAM  3.4 
images. 

Young  KC  (2001). Breast Dose Surveys in the NHSBSP: Software and Instruction Manual.  NHSBSP, 
Sheffield, United Kingdom, Report no. NHSBSP Report 01/10. 

Young  KC,  Al  Sager  A,  Oduko  JJM,  Bosmans  H,  Verbrugge  B,  Geertse  T,  van  Engen  R  (2008). 
Evaluation  of  software  in  reading  images  of  the  CDMAM  test  object  to  assess  digital  mammography 
systems. In: Proceedings of SPIE Medical Imaging 2008. Hsieh J, Samei E (eds.), pp. 6913–6947. 

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Young KC, Cook JJH, Oduko JJM (2006). Automated and human determination  of  threshold contrast 
for  digital  mammography  systems.  In:  Digital Mammography.  Flynn  MJ,  Hsieh  J  (eds.).  Springer, 
Heidelberg, Berlin, pp. 266–272. 

Young KC, Cook JJH, Oduko JJM, Bosmans H (2006a). Comparison of software and human observers 
in reading images of the CDMAM test object to assess digital mammography systems. In: Proceedings 
of SPIE Medical Imaging 2006. Flynn MJ, Hsieh J (eds.), pp. 1–13. 

Young  KC,  Oduko  JJM,  Bosmans  H,  Nijs  K,  Martinez  L  (2006b).  Optimal  beam  quality  selection  in 
digital mammography. Br. J. Radiol., 79:981–990. 

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European guidelines for 
quality assurance in 
breast cancer screening 
and diagnosis 

Fourth Edition 

Supplement 

Part 2 

European type testing 

Authors 
R. van Engen 
H. Bosmans 
P. Heid 
B. Lazzari 
S. Schopphoven 
M. Thijssen 
K. Young 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Authors 
R. van Engen, The Netherlands* 
H. Bosmans, Belgium* 
P. Heid, France* 
B. Lazzari, Italy* 
S. Schopphoven, Germany* 
M. Thijssen, The Netherlands* 
K. Young, United Kingdom* 

Contributors 
J. A. Lelivelt, J. Jacobs, C. van Ongeval 

* Member of the EUREF Physico-Technical Steering Group 

Declarations of interest 
An interest of H. Bosmans is reported on page IV. 

Disclaimer 
The views expressed in this document are those of the authors and do not necessarily reflect the offi-
cial  position  of  the  European  Commission.  Neither  the  European  Commission  nor  any  other 
organization  or  any  individual  may  be  held  responsible  for  any  use  that  may  be  made  of  the 
information contained herein. 

Acknowledgements 
Financial  support  was  provided  by  the  European  Union  Public  Health  Programme  (Project  no. 
2006322,  European  Cooperation  on  Development  and  Implementation  of  Cancer  Screening  and 
Prevention Guidelines [ECCG]). 

Please cite this publication as follows 
van Engen RE, Bosmans H, Heid P, Lazzari B, Schopphoven S, Thijssen M, Young KC (2013). Digital 
mammography update. European protocol for the quality control of the physical and technical aspects 
of  mammography  screening.  S1,  Part  2:  European  type  testing.  In: European guidelines for quality 
assurance in breast cancer screening and diagnosis. Fourth edition, Supplements.  Perry  N,  Broeders 
M,  de  Wolf  C,  Törnberg  S,  Holland  R,  von  Karsa  L  (eds.).  European  Commission,  Office  for  Official 
Publications of the European Union, Luxembourg, pp. 55–71. 

Corresponding author 
R. van Engen 
EUREF office 
National Expert and Training Centre for Breast Cancer Screening 
Radboud University Nijmegen Medical Centre 
P.O. Box 6873 
6503 GJ Nijmegen 
The Netherlands 
R.vanEngen@euref.org 
info@euref.org 

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Table of contents 

1 

2 

2.1 

2.2 

2.3 

2.4 

2.5 

3 

3.1 

3.1.1 

3.1.2 

3.2 

3.2.1 

3.2.2 

3.2.3 

3.2.4 

3.2.5 

Introduction 

Type testing procedure 

Technical and clinical phases 

Duration of a type test 

Final report 

Non-disclosure of confidential information 

Publication of results 

Type testing protocol 

Technical evaluation protocol 

Relevant test items based on Chapter 2b of the fourth edition 

Thickness indication 

Clinical evaluation protocol 

Introduction 

Procedure for acquiring the images 

Procedure for scoring the images 

The scoring form 

Procedure for evaluating the data 

3.2.5.1  Dose evaluation 

3.2.5.2  Stability test 

3.2.5.3  Additional comments 

3.2.6 

3.2.7 

3.2.8 

Requirements for the set-up at the clinical test site 

Set-up at the reference site 

Clinical evaluation form for European type testing 

References 

List of figures 

Figure 2.1 

Thickness indication check 

Figure 2.2 

Software set-up at clinical test site 

Figure 2.3a 

Example input format for selected patient cases  

Figure 2.3b 

Example output format for selected patient cases 

Figure 2.4 

Software set-up at reference site 

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1 

Introduction 

The  protocol  described  in  Part 2  of  this  supplement  has  been  developed  to  test  whether  digital 
imaging  systems  of  a  given  type  or  brand  are  fundamentally  capable  of  fulfilling  the  acceptance 
criteria  of  the  European  protocol  for  the  quality  control  of  the  physical  and  technical  aspects  of 
mammography  screening  (van  Engen  et  al.,  2006),  which  has  been  updated  in  Part 1  of  this 
supplement  (van  Engen  et  al.,  2013).  The  European  type  testing  protocol  takes  into  account  the 
updates reported in Part 1 of this supplement and it provides guidelines for best practice in controlling 
dose  and  (clinical)  image  quality.  Differences  between  the  type  testing  protocol  and  the  applicable 
standards  and  procedures  for  acceptance  and  constancy  testing  are  also  pointed  out  in  this  second 
part of the supplement. After a successful type test, individual mammography units of the same type 
or brand still need to undergo an acceptance test before clinical use. 

The European protocol for type testing is currently developed for digital mammography (DR and CR) 
systems.  In  the  future,  the  protocol  may  be  expanded  to  include  type  testing  of  image-processing 
algorithms, workstations and film digitizers. 

The  authors  welcome  all  comments  and  feedback  on  this  document  to  improve  the  standards  and 
protocols.  Future  updates  of  the  current  version  will  be  made  available  on  the  web  sites  of  the 
European Commission (http://ec.europa.eu/health/index_en.htm) and EUREF (www.euref.org). 

2 

Type testing procedure 

2.1 

Technical and clinical phases 

A type test encompasses two evaluation phases: technical evaluation and clinical evaluation. 

•  Phase 1: Technical evaluation 

In  the  first  phase,  two  full  physico-technical  evaluations  are  performed  on  different  systems  in  dif-
ferent  locations.  The  medical  physics  experts  testing  the  equipment  are  appointed  by  the  medical 
physics  team  of  the  unit  conducting  the  type  test.  They  must  be  highly  experienced  in  physico-
technical  quality  control  of  mammography  systems  and  in  quality  assurance  of  clinical  aspects  of 
breast cancer screening and diagnosis. The type test applicant (i.e. the manufacturer) must arrange in 
advance the locations and all logistic preparations with the unit conducting the type test. The systems 
must  be  available  for  the physico-technical  evaluations  for  a  period  of  at  least 3  days.  The  physico-
technical tests are primarily based on the measurements specified in Chapter 2b of the fourth edition 
(van Engen et al., 2006) and the updates to that  chapter (van Engen et al.,  2013). However, some 
tests have been modified for type testing, and some additional tests that are described in Section 3.2 
must be performed. 

After all results of the technical evaluation are available, the medical physics team of the unit conduct-
ing the type test will meet to discuss the results and decide whether phase 2, the clinical evaluation, 
can be initiated. To prepare the decision, the results of the physico-technical evaluation are compiled 
in a report and comments on the findings in the report are requested from the applicant and from the 
medical  physics  team  of  the  unit  conducting  the  type  test.  The  medical  physics  team  will  consider 
whether problems have been detected that would need to be solved in order to pass the test, and if 

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so,  whether  the  applicant  is  likely  to  be  able  to  respond  effectively.  If  the  team  determines  that  a 
solution is unlikely, the type test may be aborted by either the medical physics team or the applicant. 

If the two physico-technical evaluations yield conflicting results, the medical physics team may decide 
that (some) tests must be repeated on a third system. 

For CR systems, the physico-technical tests must be performed on two X-ray units of different brands. 
The  applicant  should  provide  appropriate  information  on  the  set-up  of  the  X-ray  units  for  the  appli-
cant’s CR system and ensure that the mammography units are set up correctly for the applicant’s CR 
plates at the sites of type testing. 

•  Phase 2: Clinical evaluation 

After the technical evaluation phase is completed, the performance of the digital system is evaluated 
under clinical use for a period of at least 3 months at one of the sites at which the technical evaluation 
was  performed.  At  this  site,  reading  must  be  by  soft  copy  and  all  workstations  must  pass  the 
European protocol for viewing conditions.  The site must also have sufficient workflow (i.e. similar to 
that used in European screening centres with an average of at least 50 clients or patients per system 
per day). The site is chosen by the applicant in cooperation with the unit conducting the type test. 

Before the clinical test is allowed to start, images of 50 patients must be sent to the unit conducting 
the test for pre-review to determine whether the configuration of the image processing requires opti-
mization. At the start of the clinical test, an application specialist of the manufacturer requesting the 
type test and a representative of the unit conducting the type test will be present at the clinical site 
for a period of at least 2 days to help start the clinical evaluation. 

During the first week of the clinical evaluation, experts of the unit conducting the evaluation perform 
an initial assessment of the images. If image quality is not satisfactory or if dose exceeds permissible 
levels,  adjustments  to  the  equipment  must  be  made  by  the  applicant.  If  image  quality  and/or  dose 
levels  remain  unsatisfactory,  the  clinical  evaluation  may  be  aborted  by  the  unit  conducting  the 
evaluation. Further adjustments during the period of clinical testing are only allowed after consultation 
with  the  unit  conducting  the  evaluation.  Some  adjustments  may  require  an  additional  technical 
evaluation. 

During  the  clinical  evaluation  period,  a  homogeneity  image  must  be  acquired  every  day  in  fully 
automatic mode to monitor the stability of the equipment. A record must be kept of all artefacts on 
clinical images and of all problems that occur with the equipment, by the radiographers/radiologists at 
the test site. At the end of the clinical evaluation period, a bad pixel map is obtained to determine the 
number of detector elements that became defective during the evaluation period. 

When problems occur, the medical physics group of the unit conducting the type test has the right to 
extend the clinical evaluation period as necessary or to abort the clinical evaluation. 

In addition to the stability test, a dose survey is conducted. For the dose survey, X-ray exposure data 
must be available, and the respective images must be available for verification. The mean glandular 
dose recorded in the DICOM header is compared with the values from the dose survey. 

At  the  end  of  the  clinical  testing  period,  a  set  of  clinical  images  is  evaluated  by  a  team  of  experts 
consisting of two radiologists with substantial experience in digital mammography, who are invited by 
the  unit  conducting  the  type  test,  and  one  of  the  members  of  the  unit’s  medical  physics  team.  The 
evaluated images consist of two groups: 50 patients or clients selected based on breast thickness, and 
20  cases  randomly  selected  out  of  referred  patients.  If  a  system  with  more  than  one  mode  is 
evaluated, at least 30 images of each mode are required. 

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In  the  event  that  the  evaluation  team  is  unable  to  reach  a  firm  conclusion  about  the  adequacy  of 
overall  image  quality  using  the  above-mentioned  clinical  images,  additional  evaluation  may  be 
required,  e.g.  through  insertion  of  simulated  lesions  in  unprocessed  images  to  assess  image 
processing. 

2.2 

Duration of a type test 

After the two technical evaluations are performed, the results of both systems will be discussed by the 
unit conducting the type test, and permission to start the clinical evaluation will be given, depending 
on the adequacy of the technical results. The duration of the clinical evaluation is at least 3 months. 

2.3 

Final report 

After completion of the clinical evaluation, the unit conducting the type test prepares a final report; it 
includes the overall result of the type test and is sent to the applicant. If a system passes, the results 
will be published on the web site of the unit conducting the test. If a system fails, the results will not 
be published on the web site (see Section 2.5). 

2.4 

Non-disclosure of confidential information 

Type tests might be performed on systems using techniques that are different from currently existing 
systems.  For  such  systems,  current  methods  of  measurement  might  be  unsuitable  and  adaptations 
may  be  necessary  and  new  test  items  may  need  to  be  added  that  are  not  specified  in  the  current 
version of the type testing protocol. The applicant must therefore provide the medical physics team of 
the unit conducting the type test with all relevant information on the system being tested. 

Relevant  information  includes:  basic  principles  of  the  mammography  system  and  particularly  the 
image  receptor,  philosophy  and  operation  of  the  AEC  system,  pre-exposure  parameters, 
reconstruction  technique  of  bad  pixels,  accepted  number  of  bad  pixels,  etc.  It  is  recommended  that 
the unit conducting the type test consult the EUREF Physico-Technical Steering Group before initiating 
a type test, for advice on whether test items need to be adapted and/or new test items need to be 
added.  If  requested  by  the  applicant,  any  relevant  information  provided  can  be  regarded  as 
confidential and a non-disclosure agreement can be signed with the parties involved. 

2.5 

Publication of results 

The  full  report  on  the  results  of  the  type  test  will  be  made  available  to  the  applicant.  If  a  system 
passes the type test, the results will be published on the web site of the unit conducting the type test. 
The  applicant  of  the  test  will  be  able  to  comment  on  the  report  before  publication  on  the  web  site. 
The unit conducting the type test will not use the information obtained from performing or reporting 
the results of the test in other publications without the consent of the test applicant. 

In consensus with the applicant, it may be mentioned on the web site of the unit performing the test 
whether a specific system is under (technical or clinical) evaluation. If a system fails, its name will be 

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removed from the list. It will not be mentioned on the web site that a specific system has failed the 
type test. 

3 

Type testing protocol 

By  definition,  type  testing  is  performed  on  new  types  of  equipment.  Therefore,  type  tests  may  be 
performed on systems that use techniques that are different from those of existing systems. For such 
systems,  the  current  methods  of  measurement  could  be  unsuitable  and  adaptations  may  be 
necessary. It is also possible that new, additional tests will be required. Therefore the medical physics 
team of the unit conducting the test must be provided by the system manufacturer with all relevant 
information  on  the  system  being  type  tested.  If  measurement  techniques  require  adaptation,  this 
must be communicated in advance to the applicant whenever possible by the unit conducting the test. 
If differences are noticed during type testing, adaptations of methods of measurement will be made 
on  the  spot  and  discussed  afterwards.  This  discussion  must  take  place  before  the  second  physico-
technical test is performed. 

It  is  recommended  that  the  unit  conducting  the  type  test  consult  the  EUREF  Physico-Technical 
Steering  Group  before  initiating  a  type  test,  for  advice  on  whether  test  items  need  to  be  adapted 
and/or  new  test  items  need  to  be  added.  Prior  contact  also  facilitates  further  communication  in  the 
event that ad hoc advice is requested during performance of measurements. 

Section  3.1  provides  an  overview  of  all  technical  tests  performed  in  a  European  type  test.  Some 
additional clinical tests are described in Section 3.2. 

For CR systems, at least 4 cassettes of standard size (18 × 24 cm) and 4 cassettes of large size (24 × 
30 cm)  should  be  available  during  the  technical  evaluation;  at  the  site  of  the  clinical  evaluation,  at 
least 8 cassettes should be available. If cassettes of large size are available, they may also be used at 
the clinical site. 

3.1 

Technical evaluation protocol 

3.1.1 

Relevant test items based on Chapter 2b of the fourth edition 

The following test items described in Chapter 2b of the fourth edition (van Engen et al., 2006) and in 
Part 1  of  this  supplement  (van  Engen  et  al.,  2013)  are  measured  in  a  European  type  test  technical 
evaluation: 

2b.2.1.1.5 

Tube  output:  Use  the  method  described  in  Part 1  of  this  supplement.  Do  not  use 
limiting values. 

2b.2.1.2 

Tube voltage and beam quality 

2b.2.1.2.1 

Tube voltage: Use the method described in Chapter 2b. 

2b.2.1.2.2 

Half value layer: Use the method described in Part 1 of this supplement. 

2b.2.1.3 

AEC system 

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2b.2.1.3.2 

Back-up  timer  and  security  cut-off:  Use  the  method  and  limiting  values  in 
Chapter 2b. 

2b.2.1.3.3 

Short-term  reproducibility:  Use  the  method  and  limiting  values  in  Part 1  of  this 
supplement. 

2b.2.1.3.4 

Long-term reproducibility: Use the method in Chapter 2b. Use the limiting values 
of  Chapter 2b  as  action  limits  for  further  investigation.  In  the  final  report,  present 
measurements on long-term stability from the clinical test period. 

2b.2.1.3.5 

Breast thickness and composition compensation: Use the method and limiting 
values in Chapter 2b (see ‘Object thickness’) and in Part 1 of this supplement. 

2b.2.1.3.6 

Local dense area: Use the method and limiting values in Part 1 of this supplement. 

2b.2.2 

Image receptor 

2b.2.2.1 

Image receptor response 

2b.2.2.1.1 

Response function: Use the method and limiting values in Chapter 2b. 

2b.2.2.1.2 

Noise evaluation: Use the method and limiting values in Part 1 of this supplement. 

2b.2.2.2 

Missed  tissue  at  chest  wall  side:  Use the method and limiting  values in Chapter 
2b. 

2b.2.2.3 

Image receptor homogeneity and stability 

2b.2.2.3.1 

Image receptor homogeneity:  Use the method and limiting  values in Chapter 2b 
and in Part 1 of this supplement. 

2b.2.2.3.2 

Detector  element  failure  (DR  systems):  Use  the  method  and  limiting  values  in 
Chapter 2b. The bad pixel map should be easily accessible for all users. If uncorrected 
bad  pixels  are  visible  on  the  images,  this  should  be  taken  into  account  when  evalu-
ating detector element failure. 

2b.2.2.3.3 

Uncorrected  defective  detector  elements  (DR  systems):  Use  the  method  and 
limiting values in Chapter 2b. 

2b.2.2.4 

Interplate  sensitivity  variations  (CR  systems):  Use  the  method  and  limiting 
values in Chapter 2b of the fourth edition and in Part 1 of this supplement. At least 4 
cassettes of each size should be present. 

2b.2.2.6 

Fading of latent image (CR systems): Use the method in Chapter 2b. 

2b.2.3 

Dosimetry:  Use  the  method  and  limiting  values  in  Chapter 2b  and  in  Part 1  of  this 
supplement. 

2b.2.4 

Image quality 

2b.2.4.1 

Threshold  contrast  visibility:  Use  the  method  and  limiting  values  in  Chapter 2b 
and in Part 1 of this supplement. 

Threshold contrast visibility is determined at several dose levels: the clinical glandular dose level and 
2–4  other  dose  levels,  which  will  be  chosen  such  that  a  large  range  of  dose  levels  is  covered  (e.g. 
between ½ and 2 times the clinical dose level). 

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For  details  of  0.1,  0.25,  0.5  and  1.0 mm  diameter,  threshold  contrast  is  plotted  against  glandular 
dose.  The  dose  is  calculated  at  which  the  minimum  acceptable  image  quality  standard,  and  the 
achievable image quality standard, is obtained for the 0.1, 0.25, 0.5 and 1.0 mm diameter objects on 
the contrast threshold visibility phantom. 

2b.2.4.2 

Modulation  transfer  function  (MTF),  noise  power  spectrum  (NPS)  and 
detective quantum efficiency (DQE): Use the method described in Appendix 7 of 
Part 1 of this supplement. 

2b.2.4.3 

Exposure time: Use the method and limiting values in Chapter 2b. 

2b.2.4.4 

Geometrical  distortion  and  artefact  evaluation:  Use  the  method  and  limiting 
values in Chapter 2b. 

2b.2.4.5 

Ghost  image/erasure  thoroughness:  Use  the  method  and  limiting  values  in 
Chapter 2b. 

3.1.2 

Thickness indication 

European type testing includes a clinical evaluation (see Section 3.2). In the clinical evaluation, a dose 
survey  is  conducted  that  requires  prior  checking  of  the  indicator  of  the  height  of  the  compression 
paddle. 

Two  foam  blocks  with  compressed  thickness  of  about  20 mm  and  40 mm  are  used  for  this 
measurement.  A  strip  is  cut  out  of  the  foam  block  to  allow  measurement  of  thickness  during 
compression (see Figure 2.1). Thickness indication can be checked when the foam blocks (180 mm × 
240 mm) are placed on the bucky. Position the blocks such that half of the block is positioned on the 
bucky  and  half  of  the  block  is  positioned  over  the  edge  of  the  bucky  at  the  chest  wall  side  (see 
Figure 2.1).  Apply  compression  (approximately  100 N),  record  the  thickness  indication  and  measure 
thickness  at  the  reference  point  with  an  appropriate  device  (e.g.  a  calliper).  Perform  this 
measurement for the two foam blocks separately and together (so that measurements can be done at 
about 20, 40 and 60 mm compressed thickness). 

Figure 2.1: Thickness indication check 

     foam block 

3.2 

Clinical evaluation protocol 

3.2.1 

Introduction 

The imaging chain consists of several components, beginning with a patient or client who is being X-
rayed  and  extending  to  the  radiologist  who  is  reading  and  reporting  the  images.  During  physico-
technical  evaluation,  each  component  is  checked  separately.  The  clinical  part  of  the  European  type 
testing protocol is essentially a global test. The quality of clinical images is affected interdependently 
by all components, including the image processing, which is not evaluated technically. The clinical part 
of the protocol therefore cannot be conducted separately; it must be performed on a system that has 
passed the technical evaluation. 

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The  clinical  evaluation  includes  an  assessment  of  the  image  quality  by  a  team  of  experts  including 
radiologists,  a  stability  test  and  a  clinical  dose  evaluation.  The  required  duration  of  the  clinical 
evaluation is 3 months, but if problems occur, the unit conducting the clinical evaluation may decide 
to extend the period accordingly or to abort the evaluation. 

The site at which the clinical images are obtained will be mutually decided by the unit conducting the 
clinical evaluation and the applicant. It must be one of the two sites at which the preceding technical 
evaluation was performed. It must have a sufficient workflow of 4 images per patient/client, and soft-
copy  reading  is  required.  The  clinical  images  will  be  sent  to  and  scored  by  the  unit  conducting  the 
clinical evaluation. The workstations used to evaluate the images must pass the European guidelines 
quality criteria. If an applicant prefers that the images be scored on the applicant’s own workstation, 
the  workstation  must  be  provided  to  the  unit  conducting  the  evaluation.  Before  use,  the  applicant’s 
workstation will be checked to verify that it passes the European guidelines quality criteria. 

3.2.2 

Procedure for acquiring the images 

The clinical evaluation will be performed for a minimum of 3 months. Before the evaluation can start, 
anonymized images of 50 patients must be sent to the unit conducting the clinical evaluation for pre-
review to determine whether the configuration of the image processing requires optimization. At the 
beginning  of  the  clinical  evaluation,  a  representative  of  the  unit  conducting  the  evaluation  will  be 
present  at  the  clinical  test  site,  together  with  a  specialist  of  the  applicant.  The  unit  conducting  the 
evaluation will install a hard disk onto which all images from the clinical test period will be copied. The 
DICOM headers of all images must be correctly filled in, but all patient or client data on the hard disk 
must  be  anonymized.  Any  image  quality  issues  that  may  occur  at  the  clinical  test  site,  such  as 
artefacts, must be recorded and reported to the unit conducting the evaluation. 

3.2.3 

Procedure for scoring the images 

The images of 70 selected women will all be scored by a reading team consisting of radiologists and a 
physicist who have experience in digital mammography and in the assessment of image quality. These 
70 cases will be selected from the images collected during the clinical test period as follows. First, the 
information  on  the  DICOM  headers  is  used  to  calculate  the  doses  of  all  women  who  received  a 
mammogram during the clinical test period. The data are also used to plot the mean glandular dose 
as a function of compressed breast thickness. This permits both determination of the dose distribution 
of  clinical  images  and  systematic  selection  of  the  cases  to  be  scored  by  the  reading  team  (all 
thicknesses, all types of tissues). The images are divided into 5 classes based on compressed breast 
thickness.  In  each  thickness  class,  patients  are  ranked  as  a  function  of  their  dose;  10  patients  are 
then selected in ranked series from each of the 5 classes using the image at the 10th percentile of the 
dose distribution, the image at the 20th percentile, the image at the 30th percentile, etc. A total of 50 
cases  are  chosen  in  this  manner.  The  other  20  cases  are  randomly  selected  from  referred  patients; 
the respective images must include opacities and microcalcifications. 

Reading  for  image  scoring  is  performed  simultaneously  by  two  radiologists  and  a  physicist.  A  third 
radiologist  with  substantial  experience  in  digital  mammography  and  evaluating  image  quality  is 
appointed  in  case  of  image  quality  problems.  This  could  be  either  a  radiologist  from  the  unit 
conducting the clinical evaluation or an external radiologist. 

3.2.4 

The scoring form 

The scoring form is based on experience with type testing in the Belgian and Dutch breast screening 
programmes  (Van  Ongeval  et  al.,  2005;  Van  Ongeval  et  al.,  2008).  The  first  part  (13  questions) 
requires  ‘yes’  or  ‘no’  answers  from  the  panel  of  experts;  it  includes  questions  about  anatomical 

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structures, noise, and contrast in low and high pixel value areas. In the second part (4 questions), the 
panel of experts scores the contrast and sharpness of the images on a scale between –2 and +2. In 
the third part (3 questions), the panel of experts rates the images on a scale from 1 to 10 according 
to certain characteristics and their potential impact on the interpretation of the image. The scoring is 
performed at the workstation where the reading team views the images. 

3.2.5 

Procedure for evaluating the data 

The unit conducting the type test should have software for data entry during evaluation and analysis, 
including  comparison  with  results  of  previous  testing  of  other  types.  Ideally,  the  program  should 
display the images and the score could be entered directly for the respective image. The software can 
be used to generate the median score for each question and also the number of ‘yes’ or ‘no’ answers 
for  each  question.  The  results  are  compared  with  other  systems;  any  significantly  lower  value  on  a 
question for a system will be investigated in detail in collaboration with the third radiologist. 

3.2.5.1

  Dose evaluation 

A dose survey is conducted during the clinical evaluation period; this requires access to the relevant X-
ray exposure data and breast thickness data, which must be available in the image header. The mean 
glandular  dose  is  compared  with  calculated  values.  When  testing  CR  systems,  the  applicant  should 
ensure  that  the  mammography  unit  and  reader  are  connected  to  fill  in  the  DICOM  header  with  the 
exposure values, breast thickness and dose indicator. 

3.2.5.2

  Stability test 

During the clinical evaluation period, an image of a 45 mm homogeneous block of PMMA covering the 
whole image receptor must be acquired every day in fully automatic mode to monitor the stability of 
the equipment. A record must be kept of all artefacts on clinical images and of all problems that were 
noticed  by  the  radiographers/radiologists  at  the  test  site.  At  the  beginning  and  at  the  end  of  the 
clinical  evaluation  period,  a  bad  pixel  map  may  be  obtained  to  determine  the  number  of  detector 
elements that became defective during this test period. These QC images and records will be sent to 
the unit conducting the type testing for evaluation. 

3.2.5.3

  Additional comments 

Comments  about  potential  special  features,  ergonomics  and  other  relevant  characteristics  or 
conditions that may affect  the results will be noted by the representative of the unit conducting the 
evaluation,  who  will  be  present  at  the  start  of  the  clinical  evaluation  period.  In  addition,  comments 
may also be requested from the radiologists and radiographers at the clinical evaluation site. 

3.2.6 

Requirements for the set-up at the clinical test site 

The software set-up at the clinical test sites is shown in Figure 2.2: 

1.  All  image  data  (both  clinical  and  technical)  are  sent  in  parallel  to  the  Picture  Archiving  and 
Communication  System  (PACS)  normally  used  at  the  site  and  also  to  a  local,  dedicated  DICOM 
Service Class Provider (SCP). To enable this, the vendor must configure a DICOM output node at 
the mammography unit. 

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2.  A software package (e.g. Gladys) (Jacobs et al., 2006) is installed on a local computer. This is a 
DICOM  SCP  that  can  be  scripted  to  perform  specific  actions  based  on  the  values  of  the  DICOM 
headers.  All  data  are  stored  on  an  external  hard  drive,  provided  by  the  unit  conducting  the 
evaluation. In the paragraphs below, the requirements for Gladys are used as an example. Other 
software  packages  with  similar  functionality  are  also  allowed.  The  requirements  for  these  other 
packages may differ. 

Requirements: 

a.  A computer that is connected to the mammography unit via the network 
b.  A free USB 2.0 port 
c.  A fixed IP address 
d.  An  administrator  access  to  this  computer  to  install  the  software  package  as  a  Windows 

service. 

Figure 2.2:   Software set-up at clinical test site 

3.  For the stability test, the homogeneous images (only ‘for processing’ images) are stored by Gladys 
on  the  external  hard  drive.  The  technical  analysis  is  performed  in  a  QC  reference  centre.  To 
distinguish  between  patient  data  and  the  homogeneity  data,  the  patient  name  (‘QCMAMMO’)  is 
taken by convention and action is undertaken by Gladys based on this patient name. 

4.  All  clinical  images  (both  ‘for  presentation’  and  ‘for  processing’  images)  are  also  sent  to  Gladys. 
Using  a  one-way  hash  algorithm,  these  image  data  are  anonymized  and  stored  on  the  external 
hard drive in a specific folder structure. The DICOM headers that need to be anonymized can be 
different  at  each  clinical  test  site,  and  Gladys  can  therefore  be  configured.  This  action  will  be 
performed on all data with a patient name that is different from ‘QCMAMMO’. 

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5.  For the collection of patient dosimetry data, a second copy of the anonymized patient data (only 
‘for presentation’ images) is stored without any image information. These DICOM files are used by 
the unit conducting the evaluation to simplify the patient dosimetry study. 

6.  For the collection of the selected 20 referred cases, local radiologists are asked to note down the 
unique  identifiers  of  at  least  20  possible  cases.  They  must  include  opacities  and  microcalcifica-
tions.  To  preserve  confidentiality,  the  unique  identifiers  of  the  selected  clinical  cases  must  be 
anonymized at the clinical  test site. For this purpose, the identifiers are saved as a text file in a 
format similar to that shown in Figure 2.3a. Gladys converts this text file using the same one-way 
hash algorithm as in (4). An example output file can be seen in Figure 2.3b. These steps assure 
that no client/patient-related information leaves the clinical test site. This procedure is performed 
by a representative of the unit conducting the evaluation. 

Figure 2.3a:   Example input format for selected patient cases 

Figure 2.3b: Example output format for selected patient cases 

3.2.7 

Set-up at the reference site 

The set-up at the reference site of the unit conducting the evaluation is shown in Figure 2.4: 

1.  All data are transferred from the clinical test site to the reference site using the external hard disk 

provided by the unit conducting the evaluation. 

2.  The  homogeneous  acquisitions  are  evaluated  for  artefacts,  and  the  stability  over  time  of  the 

mammography unit is monitored. 

3.  The  DICOM  headers  without  the  image  data  are  scanned  for  dosimetry-related  DICOM  data. 
These  header values are used to calculate the patient dose using the method  of Dance  (Dance, 

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1990; Dance et al., 2000; Dance et al., 2009; Dance et al., 2011). Calculated values are compared 
with the current European guidelines levels. 

4.  The  clinical  image  quality  is  evaluated  using  a  dedicated  software  platform  to  perform  observer 
studies by means of a visual grading analysis following the clinical evaluation form, which can be 
found  at  the  end  of  this  document  (Section  3.2.8)  (Jacobs  et  al.,  2008).  This  task  must  be 
performed in a  controlled  environment  using DICOM-calibrated viewing stations. If the applicant 
prefers to use a different workstation, that must be mutually agreed with a representative of the 
unit conducting the evaluation before the clinical evaluation period. 

Figure 2.4:   Software set-up at reference site 

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3.2.8 

Clinical evaluation form for European type testing 

Client 
number 

Please answer the following questions with ‘yes’ or ‘no’ (or N/A): 

Yes 

No 

N/A 

1 

Is the skin line visualized well? 

2  Are the vascular structures visible through the dense parenchyma? 

3 

Is the pectoral muscle visualized sharply? 

4 

Are the Cooper’s ligaments and vascular structures in the 
subcutaneous and pre-pectoral area visualized well? 

5  Are the microcalcifications well visualized and well outlined? 

6 

7 

Is the contrast in the dark areas sufficient (e.g. no saturation of 
intensity of signals, no fully dark regions)? 

Is the contrast in the white areas sufficient (e.g. no fully white 
regions)? 

8 

Is the glandular tissue sufficiently white? 

9 

Is the background sufficiently dark? 

10 

Do all images appear in the same way? 
(if not, please comment) 

11 

Is there disturbing noise in the dark areas? 

12 

Is there disturbing noise in the white areas? 

13  Are there any artefacts? 

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For the following questions, please grade the images with a number from –2 (bad) to +2 (good). 
Please use the whole range. 

–2  –1  0  1  2 

1  Contrast in the white regions 

2  Contrast in the dark regions 

3  Overall contrast  

4  Sharpness  

For the following questions, please rate the images with a number from 1 (bad) to 10 (good). Please 
use the whole range. 

1  2  3  4  5  6  7  8  9  10 

5 

How satisfied are you with the representation of micro- 
calcifications? 

6  How satisfied are you with the representation of opacities? 

7 

How satisfied are you with the representation of the 
image? 

Remarks: 

Thank you very much for providing this assessment. 

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References 

Dance DR (1990). Monte Carlo calculation of conversion factors for the estimation of mean glandular 
breast dose. Phys. Med. Biol., 35:1211–1219. 

Dance DR, Skinner CL, Young KC, Beckett JR, Kotre CJ (2000). Additional factors for the estimation of 
mean  glandular  breast  dose  using  the  UK  mammography  dosimetry  protocol.  Phys. Med. Biol., 
45:3225–3240. 

Dance DR, Young KC, van Engen RE (2009). Further factors for the estimation of mean glandular dose 
using the United Kingdom, European and IAEA breast dosimetry protocols. Phys. Med. Biol., 54:4361–
4372. 

Dance  DR,  Young  KC,  van  Engen  RE  (2011).  Estimation  of  mean  glandular  dose  for  breast 
tomosynthesis:  factors  for  use  with  the  UK,  European  and  IAEA  breast  dosimetry  protocols.  Phys. 
Med. Biol., 56:453–471. 

Jacobs J, Deprez T, Marchal G, Bosmans H (2006). The automatic analysis of digital images for quality 
control purposes made easy with a generic extendable and scriptable DICOM router. In: Proceedings 
of the Scientific Assembly and Annual Meeting of the RSNA, Chicago, IL. 

Jacobs J, Zanca F, Marchal G, Bosmans H (2008). Implementation of a novel software framework for 
increased  efficiency  in  observer  performance  studies  in  digital  radiology.  In:  Proceedings of the 
Scientific Assembly and Annual Meeting of the RSNA, Chicago, IL. 

van  Engen  RE,  Bosmans  H,  Dance  DR,  Heid  P,  Lazzari  B,  Marshall  N,  Schopphoven  S,  Thijssen  M, 
Young  KC  (2013).  Digital  mammography  update.  European  protocol  for  the  quality  control  of  the 
physical  and  technical  aspects  of  mammography  screening.  S1,  Part  1:  Acceptance  and  constancy 
testing. In: European guidelines for quality assurance in breast cancer screening and diagnosis. Fourth 
edition, Supplements.  Perry  N,  Broeders  M,  de  Wolf  C,  Törnberg  S,  Holland  R,  von  Karsa  L  (eds.). 
European Commission, Office for Official Publications of the European Union, Luxembourg, pp. 1–54. 

van Engen RE, Young KC, Bosmans H, Thijssen M (2006). European protocol for the quality control of 
the  physical  and  technical  aspects  of  mammography  screening.  Chapter  2b:  Digital  mammography. 
In: European guidelines for quality assurance in breast cancer screening and diagnosis. Fourth edition. 
Perry  N,  Broeders  M,  de  Wolf  C,  Törnberg  S,  Holland  R,  von  Karsa  L  (eds.).  European  Commission, 
Office for Official Publications of the European Communities, Luxembourg, pp. 105–165. 

Van  Ongeval  C,  Bosmans  H,  Van  Steen  A  (2005).  Current  challenges  of  full  field  digital 
mammography. Radiat. Prot. Dosimetry., 117:148–153. 

Van  Ongeval  C,  Van  Steen  A,  Geniets  C,  Dekeyzer  F,  Bosmans  H,  Marchal  G  (2008).  Clinical  image 
quality criteria for full field digital mammography: a first practical application. Radiat. Prot. Dosimetry., 
129:265–270. 

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European guidelines for 
quality assurance in 
breast cancer screening 
and diagnosis 

Fourth Edition 

Supplement 

Editor 
C.A. Wells 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Produced by the European Working Group on Breast Screening Pathology 
C.A. Wells, Dept. of Cytopathology, University College Hospital, London, United Kingdom 
I. Amendoeira, Dept. of Pathology, Instituto de Patologia & Imunologia Molecular da Universidade do 
Porto and Hospital S. João, Porto, Portugal 
J.P. Bellocq, Dept. of Pathology, University Hospital Strasbourg, Strasbourg, France 
S. Bianchi, Division of Pathological Anatomy, Dept. of Medical and Surgical Critical Care, University of 
Florence, Italy 
W. Boecker, Pathologie-Praxis, Hamburg, Germany 
B. Borisch, Dept. of Pathology, University of Geneva, Switzerland 
B. Bruun Rasmussen, Dept. Of Pathology, Herlev Hospital, Herlev, Denmark 
G.M. Callagy, Dept. of Pathology, National University of Ireland, Galway, Ireland 
E. Chmielik, Dept. of Pathology, Maria Sklodowska-Curie Memorial Cancer Center, Gliwice, Poland 
A. Cordoba, Servicio de Anatomía Patológica, Complejo Hospitalario de Navarra, Pamplona, Spain 
G. Cserni, Dept. of Pathology, University of Szeged, Hungary, and Dept. of Pathology, Bács-Kiskun 
County Teaching Hospital, Kecskemét, Hungary 
T. Decker, Dept. of Pathology, Dietrich Bonhoeffer Medical Center, Neubrandenburg, Germany 
J. DeGaetano, Dept. of Pathology Mater Dei Hospital, Malta 
M Drijkoningen, Dept. of Pathology, University Hospitals Leuven, Leuven, Belgium 
I.O. Ellis, Dept. of Histopathology, Nottingham City Hospital, Nottingham, United Kingdom 
D.R. Faverly, CMP pathology laboratory and CCR Community Reference Center for cancer screening, 
Brussels, Belgium 
M.P. Foschini, Dept. of Pathology, University of Bologna, at Bellaria Hospital, Bologna, Italy 
S. Frković-Grazio, Dept. of Gynaecological Pathology and Cytology, University Clinical Hospital, 
Ljubljana, Slovenia 
D. Grabau, Dept. of Pathology, Skåne University Hospital, Lund, Sweden 
P. Heikkilä, Dept. of Pathology, University of Helsinki and HUSLAB, Helsinki, Finland 
E. Iacovou, Dept. of Pathology, Nicosia General Hospital, Cyprus 
J. Jacquemier, Dept. of Molecular Oncology, Institut Paoli Calmettes, Marseille, France 
H. Kaya, Dept. of Pathology, Marmara University School of Medicine, Istanbul, Turkey 
J. Kulka, 2nd Dept. of Pathology, Semmelweis University, Budapest, Hungary 
M. Lacerda, Center for Neuroscience and Cell Biology, University of Coimbra, Portugal 
I. Liepniece-Karele, Riga Eastern Clinical University Hospital, Riga, Latvia 
J. Martinez-Penuela, Dept. of Pathology, Navarra Hospital Complex, Pamplona, Spain 
C.M. Quinn, Dept. of Pathology, St Vincent's University Hospital, Dublin, Ireland 
F. Rank, Dept. of Pathology, Rigshospitalet, Copenhagen University Hospital, Denmark   
P. Regitnig, Institute of Pathology, Medical University of Graz, Austria 
A. Reiner, Institute of Pathology, Danube Hospital, Vienna, Austria 
A. Sapino, Dept. of Biomedical Science and Human Oncology, University of Turin, Turin, Italy 
T. Tot, Dept. of Pathology and Clinical Cytology, Central Hospital Falun, Falun, Sweden 
P.J. Van Diest, Dept. of Pathology, University Medical Center Utrecht, The Netherlands 
Z. Varga, Dept. of Pathology, Institute of Surgical Pathology, University Hospital Zurich, Switzerland 
J. Wesseling, Dept. of Pathology, Netherlands Cancer Institute/Antoni van Leeuwenhoek Hospital, 
Amsterdam, The Netherlands 
V. Zolota, Dept. of Pathology, Medical School, University of Patras, Rion, Patras, Greece 
E. Zozaya-Alvarez, Navarra Hospital Complex, Pamplona, Spain 

Declaration of interest 
An interest of D. Grabau is reported on page VI. 

Disclaimer 
The views expressed in this document are those of the authors and do not necessarily reflect the offi-
cial  position  of  the  European  Commission.  Neither  the  European  Commission  nor  any  other 
organization  or  any  individual  may  be  held  responsible  for  any  use  that  may  be  made  of  the 
information contained herein. 

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Acknowledgements 
Financial  support  was  provided  by  the  European  Union  Public  Health  Programme  (Project  no. 
2006322,  European  Cooperation  on  Development  and  Implementation  of  Cancer  Screening  and 
Prevention Guidelines [ECCG]). 

Please cite this publication as follows 
Wells CA, Amendoeira I, Bellocq JP, Bianchi S, Boecker W, Borisch B, Bruun Rasmussen B, Callagy GM, 
Chmielik  E,  Cordoba  A,  Cserni  G,  Decker  T,  DeGaetano  J,  Drijkoningen  M,  Ellis  IO,  Faverly  DR, 
Foschini  MP,  Frković-Grazio  S,  Grabau  D,  Heikkilä  P,  Iacovou  E,  Jacquemier  J,  Kaya  H,  Kulka  J, 
Lacerda M, Liepniece-Karele I, Martinez-Penuela J, Quinn CM, Rank F, Regitnig P, Reiner A, Sapino A, 
Tot T, Van Diest PJ, Varga Z, Wesseling J, Zolota V, Zozaya-Alvarez E (2013). S2: Pathology update. 
Quality  assurance  guidelines  for  pathology.  In: European guidelines for quality assurance in breast 
cancer screening and diagnosis. Fourth edition, Supplements.  Perry  N,  Broeders  M,  de  Wolf  C, 
Törnberg S, Holland R, von Karsa L (eds.). European Commission, Office for Official Publications of the 
European Union, Luxembourg, pp. 73–120. 

Corresponding author 
C.A. Wells 
Dept. of Cytopathology 
University College Hospital 
Level 2, Rockefeller Building 
21 University Street 
London WC1E 6JJ 
United Kingdom 
c.a.wells@me.com 

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Table of contents 

1 

2 

2.1 

2.2 

2.3 

Introduction 

Columnar cell lesions and atypical ductal hyperplasia 

Background 

Terminology 

Classification of columnar cell lesions (CCLs) 

2.3.1 

Columnar cell change (CCC) 

2.3.2 

Columnar cell hyperplasia 

2.3.3 

Columnar cell change with atypia 

2.3.4 

Columnar cell hyperplasia with atypia 

2.4 

Differential diagnosis 

2.4.1 

Atypical ductal hyperplasia/low-grade ductal carcinoma in situ (DCIS) 

2.4.2  Ductal carcinoma in situ (DCIS) 

2.4.3 

Apocrine change 

2.4.4 

Lactational change 

2.5 

2.6 

2.7 

2.8 

2.9 

2.10 

2.11 

3 

3.1 

3.2 

3.3 

3.4 

3.5 

4 

4.1 

4.2 

4.3 

4.4 

4.5 

Immunohistochemistry 

Genetic aberrations 

Significance of columnar cell lesions 

Reproducibility of current classification of columnar cell lesions 

Clinical management of columnar cell lesions in needle core biopsies 

Columnar cell lesions in surgical excision specimens 

Atypical ductal hyperplasia (ADH) 

Acceptable use of frozen sections 

Palpable breast tumours 

Margin assessment 

Sentinel lymph node biopsy 

Non-palpable breast tumours 

Needle core biopsy and vacuum-assisted needle core biopsy 

Classifying invasive carcinoma 

Towards molecular classification of breast cancer 

Special type versus mixed type and “no special type” 

Immunohistochemistry of breast cancer 

Assessing predictive and prognostic markers 

Infiltrating lobular carcinoma 

79 

79 

79 

80 

80 

80 

80 

81 

81 

81 

81 

81 

81 

81 

82 

82 

82 

84 

84 

84 

85 

86 

86 

86 

86 

87 

87 

87 

87 

88 

89 

89 

90 

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4.6 

4.7 

4.8 

4.9 

Tubular carcinoma 

Invasive cribriform carcinoma 

Mucinous carcinoma 

Invasive micropapillary carcinoma 

4.10 

Neuroendocrine breast cancer 

4.11 

Apocrine carcinoma 

4.12 

Medullary-like carcinoma 

4.13 

Metaplastic carcinoma 

4.14 

Salivary gland-like cancers 

4.15 

Secretory carcinoma 

4.16 

Ductal – no special type (ductal-NST) 

4.17 

Other malignant tumours 

4.18 

Not assessable 

5 

5.1 

5.2 

Assessing the axilla 

Preoperative staging 

Problems and pitfalls 

5.2.1 

Epidermal cysts and skin appendage tumours 

5.2.2 

Lymph node inclusions 

5.2.3  Granulomatous inflammatory processes 

5.2.4  Dermatopathic lymphadenopathy 

5.2.5 

Lipoma 

5.2.6  Metastatic tumours 

5.3 

Examination and interpretation of sentinel lymph node biopsy specimens 

5.3.1 

Isolated tumour cells (ITCs) 

5.3.2  Methods of nodal assessment 

5.3.3 

Intraoperative assessment 

6 

6.1 

6.2 

6.3 

7 

7.1 

7.2 

7.3 

Microinvasive carcinoma 

Definition 

Pathological diagnosis 

Differential diagnosis 

Pathological reporting of post-chemotherapy specimens 

Macroscopic examination 

Microscopic examination 

Reporting of prognostic and predictive factors 

91 

92 

92 

92 

93 

94 

94 

95 

95 

96 

96 

97 

97 

97 

97 

98 

98 

98 

99 

99 

99 

99 

99 

100 

100 

101 

102 

103 

103 

104 

105 

106 

106 

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7.4 

7.5 

8 

8.1 

Microscopic reporting of lymph nodes 

Reporting of tumour response 

Vacuum-assisted needle core biopsy (VANCB) 

Multidisciplinary correlation 

References 

List of tables 

Table 1  Characteristics of columnar cell lesions and ADH/DCIS 

Table 2  Molecular typing of breast cancer based on common immunohistochemical markers (Abd El-

Rehim et al., 2005; Goldhirsch et al., 2011) 

Table 3  Recommended classification of response to chemotherapy 

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107 

109 

110 

110 

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108 

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1 

Introduction 

The  present  supplement  deals  with  several  topics  in  the  quality  assurance  of  pathology  in  breast 
cancer screening and diagnosis in which problems and practical solutions as well as new techniques 
and  other  advances  have  emerged  in  recent  years.  The  authors  felt  that  these  topics  warranted 
urgent  attention  pending  a  full  revision  of  the  pathology  chapter.  They  include  the  classification  of 
early forms of neoplastic changes in the breast and the differential diagnosis of columnar cell lesions 
(CCLs), atypical ductal hyperplasia (ADH) and ductal carcinoma in situ (DCIS). Other sections provide 
an update on the classification of invasive carcinoma and on the diagnosis and differential diagnosis of 
microinvasive  carcinoma.  Special  attention  is  paid  to  the  assessment  of  the  axilla,  and  the  updated 
guidance  on  axillary  dissection  and  preoperative  staging  takes  into  account  problems  and  pitfalls  as 
well as the most recent revision of the TNM system (Sobin et al., 2009). The supplement also includes 
comprehensive  practical  recommendations  on  examination  techniques  and  interpretation  of  sentinel 
node  biopsy  specimens.  Best  practice  in  the  use  of  frozen  sections,  an  update  on  vacuum-assisted 
needle  core  biopsy  (VANCB)  and  recommendations  on  pathological  reporting  of  post-chemotherapy 
specimens are also provided. 

The supplement has been prepared by the European Working Group on Breast Screening Pathology, 
which also prepared the chapter on pathology in the fourth edition (Wells et al., 2006) and in previous 
editions  of  the  guidelines.  The  group  consists  of  38  breast  pathologists  in  23  EU  Member  States, 
Switzerland and Turkey and has been led by the editor of the chapter on pathology in the guidelines. 
The  recommendations  in  the  supplement  have  been  drafted  by  selected  members  of  the  group  and 
have  been  discussed  and  agreed  upon  at  twice-yearly  meetings  held  in  Hungary,  Switzerland,  Italy, 
France, the Netherlands and Finland since the fourth edition was published. 

2 

Columnar cell lesions and atypical ductal 
hyperplasia 

2.1 

Background 

In  recent  years  there  has  been  a  growing  interest  and  awareness  of  epithelium  having  a  columnar 
morphology  within  breast  biopsies.  One  of  the  common  accompaniments  of  this  change  is  the 
presence of secretions within lumina, which are often distinctly eosinophilic and associated with micro-
calcifications  (Fraser  et  al.,  1998).  These  microcalcifications  are  detectable  by  mammography,  and 
consequently more of these lesions are being detected with the introduction and expansion of breast 
screening programmes, especially since the implementation of digital mammography (Feeley & Quinn, 
2008; Verschuur-Maes et al., 2011a). 

Diverse  terminology  has  been  used  for  this  epithelium,  e.g.  columnar  cell  lesions  (CCLs)  (Schnitt  & 
Vincent-Salomon,  2003),  flat  epithelial  atypia  (FEA)  (Tavassoli  &  Devilee,  2003),  columnar  cell 
alteration with apical snouts and secretions (CAPSS) (Fraser et al., 1998), enlarged lobular units with 
columnar  alteration  (McLaren  et  al.,  2005),  atypical  cystic  lobules  (Oyama  et  al.,  1999),  ductal 
intraepithelial  neoplasia  flat  type  (Tavassoli,  1998),  atypical  cystic  ducts  (Kusama  et  al.,  2000)  and 
clinging carcinoma (Azzopardi et al., 1979). This diverse terminology, the increased detection of this 
lesion  at  screening  and  the  uncertainties  about  its  biology  continue  to  cause  concern  among  both 
diagnostic breast pathologists and their clinical colleagues in the breast care team. In this supplement, 

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we  present  a  proposal  for  a  simplified  terminology  for  lesions  with  columnar  epithelium  and 
histological  criteria  for  recognizing  these  (Walker  et  al.,  2010).  These  proposals  are  not  carved  in 
stone and are likely to change as more knowledge is acquired about the pathobiology of these lesions 
and their natural course. 

2.2 

Terminology 

In  general,  CCLs  are  characterised  by  enlarged  terminal  duct/lobular  units  (TDLUs)  lined  with 
“columnar”  epithelium,  meaning  tall  cells  with  eosinophilic  cytoplasm  and  small  cytoplasmic  snouts 
protruding  into  the  lumina.  Intracytoplasmic  vacuoles  (like  those  in  lobular  neoplasia)  are  regularly 
seen.  Usually,  the  nuclei  are  located  basally  within  the  cell,  adjacent  to  the  myoepithelium.  Often, 
there  is  microcalcification  in  the  lumina,  and  there  may  be  extensive  mucin  production,  which  may 
even rupture into the stroma, producing a mucocoele-like lesion (Verschuur-Maes & Van Diest, 2011). 
Necrosis is extremely rare. 

These  lesions  comprise  a  spectrum  from  the  earliest  columnar  changes  in  otherwise  almost-normal 
acinar epithelium to low-grade ductal carcinoma in situ (DCIS). Further, there may be a cross-over to 
lobular neoplasia, usual ductal hyperplasia and apocrine lesions. 

Different  classifications  have  been  proposed  for  CCLs.  The  simplest  classification  and  probably  the 
most  reproducible  system  for  “pure”  CCLs  has  been  proposed  by  Schnitt  et  al.  (Schnitt  &  Vincent-
Salomon, 2003). This system discerns 4  groups  of  CCLs:  columnar  cell  change  (CCC),  columnar  cell 
hyperplasia, CCC with atypia and columnar cell hyperplasia with atypia. The morphology of those with 
atypia  corresponds  to  FEA,  as  detailed  in  the  latest  WHO  classification,  and  corresponds  to  ductal 
intraepithelial  neoplasia  1a  (DIN1a)  (Tavassoli  &  Devilee,  2003).  Sometimes  CCLs  may  co-exist  with 
lobular neoplasia. 

2.3 

Classification of columnar cell lesions (CCLs) 

2.3.1 

Columnar cell change (CCC) 

Classic  CCC  consists  of  lobular  acini,  usually  enlarged  and  lined  by  epithelial  cells  that  are  tall  and 
snouted in a manner similar to that observed in tubular carcinoma. The cytoplasm is eosinophilic, and 
often  there  are  luminal  secretions  and/or  microcalcifications.  There  is  morphological  diversity  within 
these groups. For example, the hyperchromasia of the nuclei can vary, as well as the nuclear shape 
and the “tallness” of the cells. In some cases, therefore, some cells are more cuboidal than columnar. 
The nuclei are regular and show no atypia and only small or no nucleoli. Mitoses are very rare, as is 
apoptosis. 

2.3.2 

Columnar cell hyperplasia 

These lesions are like CCC, except that there is now a piling up of > 2 layers of epithelium, assuming 
that the stratification is real, as opposed to artefactual as a consequence of cross-cutting. This multi-
layered  epithelium  may  be  flat  or  “hilly”.  There  should  be  no  complex  cribriform  architecture  or 
micropapillary  structures  without  stroma,  as  these  favour  a  diagnosis  of  atypical  ductal  hyperplasia 
(ADH) or low-grade DCIS. 

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2.3.3 

Columnar cell change with atypia 

These lesions are like CCC, except that there is now “atypia”. Atypia may manifest in different ways. 
There may be relatively uniform rounded, evenly spaced nuclei with a similar cytomorphology to that 
displayed  by  the  cells  of  low-grade  DCIS  and  some  intermediate-grade  DCIS  with  larger,  more 
irregular nuclei and/or nuclei with clear nucleoli. Here, polarisation of the cells is usually lost and the 
nuclei are often more centrally placed. Alternatively, there may be disturbance of the regular nuclear 
arrangement  and/or  mild  to  moderate  nuclear  atypia  as  reflected  by  larger,  more  irregular  nuclei 
and/or nuclei with clear nucleoli. Mitoses are still very rare. Marked nuclear atypia favours a diagnosis 
of high-grade DCIS (e.g. cancerisation of lobules). 

2.3.4 

Columnar cell hyperplasia with atypia 

These lesions are like columnar cell hyperplasia without complex architecture, except that there is now 
“atypia”.  As  above,  there  may  be  relatively  uniform  rounded,  evenly  spaced  nuclei  with  a  similar 
cytomorphology to that displayed by the cells of low-grade DCIS and some intermediate-grade DCIS 
with  larger,  more  irregular  nuclei  and/or  nuclei  with  clear  nucleoli.  Polarisation  of  the  cells  is,  again 
usually  lost  and  the  nuclei  are  often  more  centrally  placed.  Again,  there  may  be  disturbance  of  the 
regular nuclear arrangement and/or mild to moderate nuclear atypia with larger, more irregular nuclei 
and/or nuclei with clear nucleoli. Mitoses are still very rare. Marked nuclear atypia favours a diagnosis 
of high-grade DCIS (e.g. cancerisation of lobules). 

2.4 

Differential diagnosis 

2.4.1 

Atypical ductal hyperplasia/low-grade ductal carcinoma in situ (DCIS) 

By definition, CCLs do not have a complex architecture. If micropapillary or cribriform structures are 
seen, a diagnosis of ADH or low-grade DCIS should be considered, depending on the size of the lesion 
and  how  extensive  the  architectural  complexity  and  regularity  are.  In  practice,  CCLs  are  often  seen 
merging with the more elaborate architecture of ADH and DCIS, demonstrating the close relationship 
of atypical CCLs to these lesions. ADH and low-grade DCIS may well derive from CCLs. (See Table 1) 

2.4.2 

Ductal carcinoma in situ (DCIS) 

Where  flat  proliferative  epithelium  within  a  TDLU  has  high  cytonuclear  grade  nuclei  (usually 
accompanied by more apoptosis and mitosis), the lesion should be categorised as high-grade DCIS. 

2.4.3 

Apocrine change 

Apocrine  epithelium  shares  with  CCC  the  presence  of  apical  snouts  and,  sometimes,  associated 
secretions. However, the cytoplasm of apocrine cells is typically copious, granular and more pink than 
the eosinophilic appearance of CCLs. Further, unlike in most columnar cells, nucleoli are readily seen. 
Apocrine  cells  are  usually  androgen  receptor  (AR)  positive  but  oestrogen  receptor  (ER)  and 
progesterone receptor (PR) negative. 

2.4.4 

Lactational change 

Another  lesion  that  may  be  mistaken  for  atypical  CCL  is  focal  lactational  change,  which  may  appear 
both single-layered and mildly cytologically atypical with enlarged hyperchromatic nuclei. Typically, the 
epithelial cells are “hobnail”, or more cuboidal than tall, and the foamy appearance of the cytoplasm 
produced by finely divided lipid should alert the pathologist to this diagnosis. 

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2.5 

Immunohistochemistry 

In  CCLs,  there  is  extensive,  and  uniform,  positivity  of  the  nuclei  for  ER  and  PR  in  all  lesional  cells 
(Oyama  et  al.,  1999;  Allred  &  Mohsin,  2000;  Vincent-Salomon,  2003;  Tremblay  et  al.,  2005).  Most 
cells  stain  positively  for  keratin  19  (Oyama  et  al.,  1999)  and  osteoprotegerin  (Van  Poznak  et  al., 
2006),  and a high proportion are positive with  cyclin  D1 (Oyama et al., 1999).  CCLs do not express 
basal markers such as CK5/6 and CK14 (Otterbach et al., 2000) and are not uniformly positive for AR. 
p53  accumulation  is  lacking  (Simpson  et  al.,  2005).  The  utility  of  GCDFP15  (BRST2)  to  discriminate 
CCLs  from  apocrine  change  where  it  is  extensively  expressed  has  yet  to  be  documented  in  the 
literature. High-grade DCIS with a flat morphology is positive for HER2, unlike CCC, which is uniformly 
negative for HER2 (Simpson et al., 2005). 

2.6 

Genetic aberrations 

There  is  increasing  evidence  that  there  is  progressive  chromosomal  damage  in  CCLs  (with  atypia) 
through  to  DCIS  and  invasive  carcinoma,  implying  a  molecular  continuum  from  some  lesions  with  a 
columnar  morphology.  This  is  not  the  case  for  ADH  and  carcinoma.  Most  importantly,  in  different 
studies a high concordance level of the genetic abnormalities was seen in CCLs with atypia as well as 
in  the  accompanying  infiltrating  and  in  situ  components.  With  comparative  genomic  hybridisation, 
chromosomal abnormalities were identified with loss on 16q, 17p and X and gain on 15q, 16p and 19 
(Simpson et al., 2005). Recently, with use of loss of heterozygosity (LOH), allelic losses were identified 
in CCL with atypia, low-grade DCIS and tubular carcinoma on the long arm of chromosome 16, as well 
as  at  chromosomes  8p21,  3p14,  1p36  and  11q14  (Aulmann  et  al.,  2009).  In  another  study,  LOH  at 
chromosomal loci 11q21-23.2, 16q23.1-24.2 and 3p14.2 was present in 50%, 45% and 41% of cases, 
respectively  (Moinfar  et  al.,  2000).  Dabbs  et  al.  have  similarly  shown  progressive  accumulation  of 
allelic damage at 9q, 10q, 17p and 17q with increasing severity of the lesion (Dabbs et al., 2006). 

This makes it very  likely that CCLs are among the earliest forms of neoplastic change in the breast. 
Therefore,  CCLs  need  to  be  seen  as  clonal  and  neoplastic  proliferations,  in  which  different 
chromosomes play a role, with loss on chromosome 16q seeming to be the most important. 

2.7 

Significance of columnar cell lesions 

The overall biological significance of CCLs is not yet fully understood (Tremblay et al., 2005). There is 
supporting evidence for a precursor role within the spectrum of the low nuclear grade family of breast 
cancers (Abdel-Fatah et al., 2008).  This includes an association with tubular  carcinoma (Goldstein & 
O'Malley,  1997;  Rosen,  1999;  Aulmann  et  al.,  2009)  and  the  findings  that  these  lesions  are  more 
commonly  present  in  cancerous  breasts  than  in  non-cancerous  breasts  (Wellings  et  al.,  1975),  are 
often continuous with cancerous lesions (Kusama et al., 2000), commonly co-exist with lobular in situ 
neoplasia  (Brogi  et  al.,  2001)  and  share  similar  cytological  characteristics  and  immunohistochemical 
profile and genetics with co-existent malignancies (Oyama et al., 1999; Moinfar et al., 2000; Tavassoli 
& Devilee, 2003; Simpson et al., 2005; Dabbs et al., 2006). 

Despite the above, the certainty and speed of progression of these lesions to malignancy is not well 
known.  A  follow-up  study  performed  by  Boulos  et  al.  showed  a  relative  risk  of  1.47  of  developing 
invasive  carcinoma  after  a  needle  core  biopsy  showing  CCL  (with  or  without  atypia)  (Boulos  et  al., 
2008). The study had a follow-up interval of 17 years, and 1154 CCLs were included. Shaaban et al. 
described that 8 cases of CCL with atypia had a relative risk of 2.32 of developing subsequent invasive 

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carcinoma,  compared  with  11  controls  with  CCL  without  atypia,  who  did  not  develop  cancer  in  the 
follow-up period (Shaaban et al., 2002). Verschuur-Maes et al. reported an 8-year progression risk for 
CCL  with  atypia  and  ADH  emerging  in  CCL  of  about  20%  (Verschuur-Maes  et  al.,  2011b).  However, 
other studies did not find evidence of the increased risk of breast cancer. Eusebi et al. discovered only 
1  recurrence  of  the  25  CCLs  with  atypia  (in  their  study,  called  low-grade  clinging  carcinoma  of  flat 
type)  after  3  years,  with  a  follow-up  interval  of  19  years  (Eusebi  et  al.,  1994).  Bijker  et  al.  and  De 
Mascarel et al. also found no invasive carcinoma or DCIS in 59 and 84 CCLs with atypia, respectively, 
with  a  mean  follow-up  of  5.4  and  13.3  years,  respectively  (Bijker  et  al.,  2001;  de  Mascarel  et  al., 
2007). 

It is worth noting that McLaren et al. found that patients with ER negative CCLs were at increased risk 
of malignancy compared with those whose lesions were ER positive (McLaren et al., 2005), but as yet 
there are no confirmatory studies. 

Table 1: Characteristics of columnar cell lesions and ADH/DCIS 

Diagnosis 

Feature 

Topography 

Columnar cell 
change 

Columnar cell 
hyperplasia 

Columnar cell lesion 
with atypia ** 

ADH/DCIS 

TDLU, acini may be 
mildly dilated or of 
normal size 

TDLU, acini may 
be mildly dilated or 
of normal size 

TDLU, often microcystically 
dilated acini 

TDLU +/– adjacent ducts 

Shape of acinar 
spaces 

Irregularly shaped 
luminal margin 

Irregularly shaped 
luminal margin 

Architecture 

Flat 

Tufts and mounds 

Often rounded acinar 
spaces, with smooth inner 
margin 

Often rounded acini, but 
with complex structures 
extending into lumen (see 
Architecture, below) 

Flat or tufted/mounds, not 
complex 

Complex with micropapillary 
or cribriform structures 

Not present 

Present 

May be present 

May be present 

Present 

Present 

Present 

May be present 

Stratification/ 
multi-layering 

Luminal 
secretions often 
with micro-
calcifications 

Nuclear size 

Small to medium 

Small to medium 

Small to medium 

Small to medium 

Nuclear shape 

Oval, elongated 

Oval, elongated 

Nuclear texture 

Bland 

Bland 

Often, but not always, 
rounded 

Rounded 

Speckled chromatin pattern 
may be present 

Speckled chromatin pattern 
is common 

Pleomorphism* 

Uniform 

Uniform 

Uniform to moderately 
pleomorphic 

Basally placed 

Basally placed 

Often central 

Uniform 

Central 

Position of 
nuclei within cell 

Nucleoli 

Mitoses 

Extent 

Not conspicuous 

Not conspicuous 

Evident 

Generally absent 

Generally absent 

Generally scarce 

May be focal or 
extensive 

May be focal or 
extensive 

May be a focal area within 
background of non-atypical 
CCL 

May be evident 

Generally scarce 

May be focal area within 
background of non-atypical 
CCL; by definition, ADH is 
small/microfocal 

  * If the cells display marked pleomorphism, then the lesion does not fall within the spectrum of CCLs but should 
be regarded as high-grade DCIS. 

** Also referred to as flat epithelial atypia (FEA). 

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2.8 

Reproducibility of current classification of columnar cell 
lesions 

The reproducibility of the diagnosis of CCLs varies in the published literature. One study looking at the 
assessment  of  images  by  a  mixed  group  of  assessors  showed  poor  agreement  (Tan  et  al.,  2005). 
Another  demonstrated  “excellent  agreement”  for  a  specified  task  within  the  CCL  group  after  a 
PowerPoint-directed training session undertaken by a group of pathologists with an interest in breast 
pathology (O'Malley et al., 2006). Agreement was slightly better for determining the absence of CCLs 
with  atypia  (in  their  study,  called  FEA)  (92.8%;  95%  CI,  84.1–97.4%)  than  for  determining  its 
presence  (90.4%;  95%  CI,  79.9–96.7%).  O’Malley  et  al.  concluded  that  the  diagnosis  of  CCLs  with 
atypia and its distinction from those without atypia was highly reproducible if the available diagnostic 
criteria were adhered to. This simplified classification in the study of O’Malley et al. forms the basis of 
the recommendations presented here. 

Issues  of  poor  reproducibility  can  confound  diagnosis  and  lead  to  inconsistent  patient  care.  This  is 
more likely when complex and diverse terminology with possible different interpretations exists. This is 
nowhere  more  apparent  than  in  the  case  of  lesions  with  columnar  epithelial  morphology  and  is  the 
strongest argument for the simplified classification of these lesions presented here. 

2.9 

Clinical management of columnar cell lesions in needle core 
biopsies 

Core  biopsies  bearing  CCLs  are  typically  sampled  for  the  histological  assessment  of  mammographic 
microcalcification. As with similar specimens, these should be examined at multiple (at least 3) levels. 
If CCC or columnar  cell hyperplasia only is found, without atypia, the lesions  should be regarded as 
benign, requiring only follow-up. Core biopsies with CCLs without atypia should be classified in the B2 
category. 

CCLs  with  atypia  (whether  CCC  or  columnar  cell  hyperplasia)  should  be  regarded  as  of  uncertain 
malignant  potential,  with  a  risk  similar  to  ADH  and  atypical  lobular  hyperplasia.  Atypical  CCLs  are 
associated  with  more  advanced  lesions  in  subsequent  excisional  biopsy  more  frequently  than  are 
those without atypia. (Guerra-Wallace et al., 2004; David et al., 2006; Kunju & Kleer, 2007; Martel et 
al., 2007; Chivukula et al., 2009; Senetta et al., 2009; Ingegnoli et al., 2010; Verschuur-Maes et al., 
2011a).  As  for  all  such  screen-detected  lesions,  multidisciplinary  discussion  should  be  undertaken  to 
correlate  radiological,  clinical  and  histopathological  findings  to  decide  on  surgical  excision  biopsy, 
vacuum-assisted  biopsy  or  a  wait-and-see  policy.  A  recent  systematic  review  concluded  that,  on  the 
basis  of  the  (in  situ)  carcinoma  underestimation  rates  of  patients  with  a  core  diagnosis  of  CCL  with 
atypia  and  ADH  associated  with  CCL,  surgical  excision  should  be  considered  (Verschuur-Maes  et  al., 
2012). Core biopsies with CCLs with atypia should be classified in the B3 category. 

2.10  Columnar cell lesions in surgical excision specimens 

Thorough  sampling  and  histological  examination  of  surgical  specimens  bearing  CCLs  with  atypia 
should  be  performed  to  search  for  more  established  neoplasia  like  ADH,  DCIS,  lobular  neoplasia  or 
even  invasion.  In  association  with  some  DCIS  and/or  invasive  carcinoma,  CCLs  with  atypia  may  be 
present and may be extensive and/or may extend to the margins of the specimen. This is particularly 
problematic for lesions that are well recognised to be associated with CCL with atypia, such as tubular 
carcinoma  (Rosen,  1999).  There  is  a  very  limited  evidence  base  for  guidance  with  regard  to  re-

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excision or radiotherapy, but at present it is recommended that whole tumour size (DCIS plus invasive 
carcinoma)  and  margin  status  should  include  only  those  areas  regarded  as  established  DCIS  or 
invasive tumour using conventional criteria. It should be recognised that these lesions have a very low 
risk of development of life-threatening disease. 

2.11  Atypical ductal hyperplasia (ADH) 

The  distinction  between  low-grade  DCIS  and  ADH  is  based  on  evidence  derived  from  many  series, 
including studies by David Page and co-workers (Page & Dupont, 1993). These have been supported 
by other studies, such as the Nurses’ Health Study (Connolly & Schnitt, 1993; Marshall et al., 1997). 

The significance of the diagnosis of ADH lies in the increased risk of invasive breast carcinoma, which 
is about 4–5 times that of the general population (Page et al., 1985; Ma & Boyd, 1992; London et al., 
1992;  Dupont  et  al.,  1993;  Page  &  Jensen,  1994)  and  may  be  even  greater  for  pre-menopausal 
women (approaching 6 times increased risk) (London et al., 1992). This risk is further increased if the 
patient  has  a  first-degree  relative  with  breast  cancer  (10  times  increased  risk)  (Page  et  al.,  1985; 
Tavassoli & Norris, 1990; Page & Dupont, 1992). 

The  diagnostic  criteria  used  to  define  ADH  are  imperfect.  ADH  was  described  initially  based  on 
exclusion rather than positive criteria, i.e. the recognition of some but not all of the features of DCIS 
(as well as the lack of the characteristics of usual type epithelial hyperplasia) (Page et al., 1985). This 
definition  of  ADH  has  been  updated  and,  while  the  diagnosis  still  rests  on  an  absence  of  all  the 
features of DCIS, additional supporting features have been described (Page & Rogers, 1992; National 
Coordinating  Group  for  Breast  Screening  Pathology,  1995).  Page’s  view  that  the  cellular  changes  of 
DCIS are present but occupy < 2 separate duct spaces is widely accepted. Others use a 2 mm cut-off; 
a lesion < 2 mm in maximum dimension is  classified  as ADH and a larger lesion as DCIS (Tavassoli, 
1992). Others mention the involvement of a single TDLU. These criteria recognise essentially the same 
lesions.  In  essence,  ADH  is  usually  small  and  focal,  measuring  < 2–3 mm  in  maximum  dimension. 
Larger  foci  are  accepted  as  ADH  if  associated  with  a  radial  scar/complex  sclerosing  lesion  or  a 
papilloma. 

There are three components to the diagnosis of ADH: the architectural pattern, cytology and disease 
extent. Because disease extent cannot be optimally assessed in core biopsy samples, the diagnosis of 
ADH cannot be made from core biopsy specimens, and the term “atypical intraepithelial proliferation 
of ductal type” is used in this setting (see the appropriate section in the fourth edition). ADH is formed 
from  a  uniform  population  of  small  or  medium-sized  round,  cuboidal  or  polygonal  hyperchromatic 
cells,  which  are  regularly  arranged.  The  nuclei  are  evenly  distributed  and  may  form  a  rosette-like 
pattern. Single small nucleoli only are present. Mitoses, particularly abnormal forms, are infrequently 
seen. Geometric spaces are noted and, in the cribriform type, the cells are arranged at right angles to 
the  bridges  formed.  Micropapillary  ADH  is  also  recognised,  and  a  solid  pattern  may  very  rarely  be 
seen.  Small  foci  of  necrosis  may  rarely  be  identified  in  ADH  and  do  not  indicate  that  the  process 
should be classified as DCIS. 

At present, it is recommended that the diagnosis of ADH should be restricted to lesions that show the 
features described by Page et al. (Page et al., 1985; Page & Rogers, 1992), to  which the quantified 
risk of developing breast carcinoma is linked. Even then, the diagnosis of ADH should be made with 
caution and only if low-grade DCIS has been seriously considered in the differential diagnosis. Lesser 
changes for which the possible classification lies between florid usual type hyperplasia (UEH) and ADH 
are less relevant with regard to a risk of developing breast carcinoma and should not be classified as 
ADH. However, it should also always be borne in mind that a proliferation at the edge of a biopsy may 
represent  the  periphery  of  a  more  established  lesion  of  DCIS  and  further  excision  of  the  adjacent 
tissue may be warranted. 

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3 

Acceptable use of frozen sections 

3.1 

Palpable breast tumours 

Frozen section for intraoperative assessment of palpable breast tumours was invented several decades 
ago  and  has  been  widely  used  since  then.  It  is  a  reliable  method  for  palpable  lesions  > 1 cm  in 
diameter (Fessia et al., 1984; Niemann et al., 1996). Discrepancies between frozen section diagnosis 
and  subsequent  paraffin  section  diagnosis  consist  mainly  of  false-negative  results,  with  a  low 
frequency of 1–2%. False-positive frozen section diagnoses are very rare events, occurring in < 0.1% 
of  cases.  In  some  cases  the  definitive  diagnosis  in  frozen  section  has  to  be  deferred  to  paraffin 
section.  Overall  sensitivity  of  frozen  section  diagnosis  is  reported  to  be  > 90%  and  specificity  about 
97%.  The  main  reasons  for  failure  are  due  to  macroscopic  and  microscopic  sampling  errors, 
histological interpretative errors, poor technical quality of frozen sections and lack of  communication 
between  pathologist  and  surgeon  (Cserni,  1999;  Laucirica,  2005).  The  introduction  of  preoperative 
diagnosis on core biopsies has led to a marked reduction in the use of frozen sections for assessment 
of breast lesions (Laucirica, 2005). Frozen section diagnosis may still be performed rarely, e.g. when 
core biopsy results are equivocal. Tumours < 1 cm in maximum diameter should not be subjected to 
frozen section diagnosis. In general, it would be expected that extensive preoperative interdisciplinary 
discussion  between  radiologists,  surgeons  and  pathologists  would  decrease  the  need  for  frozen 
sections, which should be performed only where there is an immediate impact on surgical treatment. 

3.2 

Margin assessment 

No  consensus  exists  about  the  method  of  intraoperative  margin  assessment.  Frozen  sections  are 
considered  suitable  for  this  application.  The  accuracy  of  frozen  sections  for  margin  assessment  is 
described with a sensitivity and specificity of only 86% and 83%, respectively (Noguchi et al., 1995). 
This is mainly due to intraductal tumour components not included in frozen sections but detected on 
subsequent  examination  in  paraffin  sections.  The  fatty  nature  of  the  margins  is  often  a  technical 
hurdle  for  adequate  frozen  sections.  However,  frozen  sections  of  margins  for  breast  cancer  may  be 
unnecessary in cases where specimen radiology is performed and reported to an adequate standard. 

3.3 

Sentinel lymph node biopsy 

Frozen  sections  for  intraoperative  assessment  of  sentinel  lymph  nodes  (SLNs)  should  be  performed 
only  in  cases  with  impact  on  immediate  surgical  treatment.  The  main  purpose  is  to  spare  patients, 
with  a  positive  SLN,  2-step  surgery.  Not  all  metastases  will  be  identified  in  these  lymph  nodes  in 
frozen  sections  due  to  the  limited  number  of  sections  acceptable  intraoperatively  and  freezing 
artefacts.  The  risk  of  false-negative  results  is  reported  to  be  between  9%  and  52%  (Cserni  et  al., 
2003).  Rarely,  false  positivity  may  occur.  Overall,  the  accuracy  is  reported  to  be  between  79%  and 
98%. In addition, during frozen sectioning, tissue loss may occur, which must be kept to a minimum 
(Cserni, 2006; Varga et al., 2008; Fritzsche et al., 2010). Imprint cytology is an acceptable alternative 
in centres with cytological expertise (Van Diest et al., 1999). 

The  findings  of  the  ACOSOG  Z0011  trial,  suggesting  that  SLN  micrometastases  do  not  adversely 
impact  on  prognosis  and  challenging  the  view  that  all  patients  with  a  positive  SLN  require  complete 

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axillary  lymph  node  clearance,  has  led  to  a  reduction  in  the  need  for  intraoperative  SLN  evaluation 
(Giuliano et al., 2011). 

3.4 

Non-palpable breast tumours 

Frozen  section  diagnosis  is  not  recommended  for  non-palpable  breast  tumours.  They  are  usually 
screen-detected  and  < 1 cm  in  diameter.  Because  of  their  small  size,  significant  amounts  of  tissue 
may  be  lost  during  frozen  section  preparation,  and  definitive  diagnosis  in  paraffin  sections  may 
become impossible. 

3.5 

Needle core biopsy and vacuum-assisted needle core biopsy 

Core  biopsies  are  small-volume  specimens  and  are  often  used  for  screen-detected  breast  lesions, 
which may be complex lesions detected only by microcalcification in many cases and requiring special 
expertise  in  breast  pathology.  Overdiagnosis  and  underdiagnosis  in  this  type  of  specimen  are  well-
known phenomena, even in paraffin sections. For example, in cases of DCIS underdiagnosis is found 
in  up  to  20%  of  cases  when  compared  with  subsequent  open  biopsy  (Verkooijen,  2002).  Moreover, 
core  biopsies  are  very  small  in  volume  and  significant  amounts  of  tissue  may  be  lost  during  frozen 
sectioning,  rendering  paraffin  section  diagnosis  impossible.  Biomarkers,  e.g.  steroid  hormone 
receptors,  may  need  to  be  assessed  on  paraffin  sections  from  carcinoma  in  core  biopsies.  If  frozen 
sections are performed on core biopsies, reliable assessment cannot be guaranteed due to freeze and 
thaw  artefacts.  Therefore,  frozen  section  examination  of  core  biopsies  is  not  appropriate  under  any 
circumstances. 

4 

Classifying invasive carcinoma 

Typing  invasive  carcinomas  has  prognostic  value  and  provides  information  on  the  pattern  of 
metastatic spread and behaviour. Because (1) typing of breast carcinomas has been shown in external 
quality assurance EQA schemes to be relatively poorly reproducible, (2) the most frequent traditional 
type  (ductal)  can  be  correlated  to  prognosis  only  through  additional  grading  and  (3)  important 
progress has been made in classifying breast cancers in a more molecular way that predicts response 
to current adjuvant therapeutics, the system has been revised to include current molecular insights. 
Caution should be exercised in typing carcinomas in poorly fixed specimens or in specimens that have 
been removed from patients who have been treated by primary chemotherapy, hormonal therapy or 
radiotherapy before surgery. 

4.1 

Towards molecular classification of breast cancer 

Microarray gene expression studies have suggested that breast cancers cluster in 3 main groups: (1) 
luminal  cancers,  which  mainly  have  properties  of  glandular  cells  of  the  breast,  driven  by  high 
expression  of  steroid  receptors;  (2)  HER2-driven  cancers,  with  amplification  and  overexpression  of 
HER2/neu but lacking steroid receptor expression and (3) basal cancers, which have properties of the 
stem cells of the breast (Sorlie et al., 2001). Because these expression profiles reflect carcinogenetic 

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pathways  and  correlate  with  response  to  therapy,  incorporating  this  new  way  of  molecular  thinking 
into  breast  cancer  classification  is  becoming  increasingly  important.  Because  microarray  gene 
expression is not easily performed in routine practice and, for the time being, requires frozen material, 
attempts  have  been  made  to  translate  this  molecular  classification  into  an  immunohistochemical 
classification  based  on  the  expression  of  established  markers  such  as  ER,  PR,  HER2,  basal 
cytokeratins,  epidermal  growth  factor  receptor  (EGFR),  and  proliferation  rate.  This  surrogate 
molecular  classification  is  still  evolving,  and  no  real  consensus  has  been  reached.  We  nevertheless 
think  it  important  to  follow  this  trend  and  to  attempt  for  the  first  time  to  come  to  some  form  of 
integration  between  traditional  and  molecular  (“histomolecular”)  typing  using  our  current  state  of 
knowledge (Weigelt & Reis-Filho, 2009). 

Luminal cancers show expression of ER and/or PR, the luminal A subtype without and the luminal B 
subtype  with  overexpression  of  HER2  and/or  high  Ki67  score.  Most  tubular,  invasive  cribriform, 
mucinous, invasive micropapillary and lobular cancers fall into this group, as do most grade 1 and 2 
ductal  cancers.  Luminal  cancers  especially  metastasise  to  the  bone,  although  luminal  B  cancers 
metastasise also to the brain with increased frequency. 

The  HER2  group  shows  overexpression  of  HER2  and  lacks  expression  of  ER  and  PR.  This  group 
comprises mainly ductal and some apocrine cancers. Apocrine cancers usually show expression of AR. 

Basal cancers lack expression of ER, PR and HER2 (often denoted “triple negative”) and express basal 
cytokeratins like CK5/6 and/or CK14 or EGFR. Please note here that “triple negative” does not equal 
basal per se! Although basal cancers may also express other markers associated with stem cells, like 
p63 and vimentin, these markers are not routinely used. The group of basal cancers usually comprises 
well-circumscribed  cancers  with  high-grade  features  (atypical  nuclei,  many  mitoses,  geographic 
necrosis), lack of tubule formation with larger solid and often interconnecting islands, and abundant 
lymphocytoplasmic  infiltrate  around  the  lesion.  There  is  often  a  central  fibrotic/necrotic  area.  This 
group comprises high-grade cancers such as most medullary cancers and metaplastic cancers, BRCA1 
germline  mutation-associated  cancers  and  many  grade  3  ductal  cancers.  Low-grade  basal  cancers 
comprise  the  salivary  gland-like  cancers  (e.g.  adenoid  cystic  carcinoma)  (Foschini  &  Krausz,  2010). 
Some triple negative cancers may express AR and are possibly apocrine-derived. 

In  this  supplement,  we  have  attempted  to  relate  the  traditional  histological  types  to  this  molecular 
classification to arrive at a synthesis of traditional morphological and new molecular typing (see Table 
2). Inherently, this means that traditional histological typing has lost some of its importance because 
clinically it may no longer always be useful to discern some of the traditional WHO types that clinically 
behave  similarly  and,  in  fact,  always  overlapped  considerably  (Weigelt  et  al.,  2008;  Reis-Filho  & 
Lakhani, 2008). 

It  should  be  realised,  however,  that  invasive  breast  cancer  forms  a  morphological  and  also  a 
molecular  spectrum,  so  not  all  established  morphological  types  completely  fall  into  one  of  the 
molecular groups, nor will all individual cancers be easily classifiable into one of the molecular types. 

4.2 

Special type versus mixed type and “no special type” 

A special type cancer shows a classic morphology with all the hallmark histological features that will 
reproducibly be classified as such by different pathologists, requiring > 90% purity. 

Mixed morphological differentiation with < 90% purity is relatively common, as is the mere absence of 
specific  differentiation  patterns,  which  mostly  leads  to  a  classification  as  “ductal  –  no  special  type” 
(ductal-NST). ER, PR and HER2 usually do not vary clearly between the histologically different parts of 

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these  tumours,  so  that  assessing  these  receptors  in  these  mixed  cancers  does  not  pose  specific 
problems. Prognosis, however, is dictated by the “worst” (least differentiated) part of the tumour. 

Table 2:  Molecular  typing  of  breast  cancer  based  on  common  immunohistochemical 

markers (Abd El-Rehim et al., 2005; Goldhirsch et al., 2011) 

Molecular 
intrinsic subtype 

Clinico-
pathological 
definition 

ER 

PR 

HER2 

Ki67 

Basal markers* 

Luminal A   

Luminal B 

Luminal B 

HER2 

Basal 

Luminal A 

Luminal B 
(HER2 
negative) 

Luminal B 
(HER2 
positive) 

HER2 positive 
(non-luminal) 

Triple 
negative 
(ductal) 

+ 

+ 

+ or – 

+ or – 

– 

– 

Low 

High 

+ 

+ or –  Overexpressed 

Low or 
high 

– 

– 

– 

– 

Overexpressed  Usually 

– 

high 

Usually 
high 

- 

- 

- 

+/- 

+ 

              * CK5/6 or CK14 

4.3 

Immunohistochemistry of breast cancer 

Besides  the  markers  used  for  molecular  classification,  we  describe  more  specific  markers  for  the 
different  morphological  types.  In  general,  breast  cancers  are  positive  for  AE1/3  (and  other  broad-
spectrum keratins), CAM5.2, CK7 and EMA, and for BRST2 (GCDFP-15), which is usually focal (except 
in the case of apocrine differentiation). 

4.4 

Assessing predictive and prognostic markers 

Proper assessment of prognostic and predictive factors requires adequate tissue processing in the first 
place. This includes freezing representative tissue when necessary (snap freezing in liquid nitrogen or 
isopentane,  followed  by  storage  in  a  –80°  freezer)  and  adequate  fixation  of  the  rest  in  neutral 
buffered  formaldehyde.  Freezing  or  formaldehyde  fixation  must  be  done  with  as  little  delay  as 
possible.  To  achieve  adequate  fixation,  tissue  must  be  sliced  at  4–5 mm  thickness,  which  should 
ensure full fixation in 24–48 hours. Longer fixation must be avoided to prevent false-negative or false-
positive results for prognostic or predictive tests. 

Prognostic  features  that  are  currently  widely  used  include  invasive  tumour  size  (as  measured  in  the 
fresh specimen, corrected when necessary on the microscopic sections), (sentinel) lymph node status, 
histological grade and proliferation rate (as measured by mitotic activity index or Ki67 labelling index). 
DNA  microarrays  are  promising  prognostic  tools  but  are  as  yet  insufficiently  validated  for  routine 
clinical use as predictors of response to therapy. The cost of these tests is also worrisome. 

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Predictive tests for hormonal treatment are expression of ER and PR, whereas overexpression of HER2 
predicts  response  to  anti-HER2  therapy.  The  negative  predictive  value  of  these  tests  is  generally 
higher  than  their  positive  predictive  value,  e.g.  ER  (and  PR)  negative  tumours  are  unresponsive  to 
hormonal  therapies,  but  ER  positive  tumours  are  not  necessarily  responsive.  For  HER2,  gene 
amplification tests (like fluorescence chromogenic, or silver in situ hybridisation, or PCR-based tests) 
are increasingly important, especially for equivocal cases or  on core biopsies. Participation in quality 
assessment programmes for different molecular and immunohistochemical tests is essential. 

Clearly, molecular assessments are the task of the pathologist within the regular framework of tumour 
workup. Pathologists should be and are ready to implement new molecular tests in their laboratory as 
soon as they are sufficiently clinically validated. 

4.5 

Infiltrating lobular carcinoma 

Consideration of both the cytological appearance and the infiltration pattern leads to the diagnosis of 
lobular carcinoma and, in particular, to relevant subclassification. Typical cytology (small regular cells 
with  clear  boundaries,  frequently  having  intracytoplasmic  mucous  vacuoles,  and  small  nuclei  with 
inconspicuous nucleoli) and a typical infiltration pattern (cells dissociated from each other or forming 
single files, often in targetoid patterns around uninvolved ducts) lead to the diagnosis of "classic type" 
lobular  carcinoma.  Mitotic  rate  is  low.  There  are  often  satellite  lesions  around  the  dominant  nodule, 
and infiltration is often multifocal. Several variants have been identified in addition to this classic form. 
At  least  90%  of  the  tumour  should  exhibit  one  or  more  of  the  classic  or  variant  patterns  to  be 
classified as infiltrating lobular. 

The alveolar variant exhibits small round aggregates of 20 or more cells with typical lobular cytology, 
and is better demarcated than the classic type. 

The  solid  variant  consists  of  more  solid  sheets  of  cells  with  little  intervening  stroma,  often  better 
demarcated  than  the  classic  type.  Mitoses  are  usually  also  more  frequent,  and  atypia  may  be  more 
prominent. 

The tubulolobular type exhibits microtubular formation as part of the classic pattern, thereby forming 
a spectrum with tubular cancer, and probably lies closer to tubular cancer in both morphological and 
immunohistochemical  aspects.  Tumours  that  show  mixtures  of  typical  tubular  and  classic  lobular 
carcinoma should be classified as mixed (see below). 

The pleomorphic variant is less common and exhibits the growth pattern of classic lobular carcinoma 
throughout, but the cells, although retaining lobular characteristics such as their discohesive character 
and intracytoplasmic vacuoles, have polygonal, eccentric pleomorphic nuclei. Mitoses are usually also 
more frequent, and expression of ER/PR is often less than in classic lobular carcinoma, reflected in a 
somewhat  worse  prognosis  than  classic  lobular  carcinoma  (Eusebi  et  al.,  1992;  Weidner  &  Semple, 
1992). 

Lobular  mixed  type  lesions  consist  of  mixtures  of  the  above  subtypes  of  lobular  carcinoma. 
Histiocytoid or myoid cellular differentiation may occur (Eusebi et al., 1995; Del Vecchio et al., 2005). 
It is currently insufficiently clear whether lymphoepithelioma-like cancer is a variant of lobular cancer. 
The  pleomorphic  variant  can  be  associated  with  a  prominent  inflammatory  infiltrate,  a  feature  that 
may  present  a  difficult  differential  diagnosis  with  lymphoepithelioma-like  carcinoma  (Dadmanesh  et 
al., 2001). 

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These  lesions  are  thought  to  derive  especially  from  lobular  neoplasia  (atypical  lobular  hyper-
plasia/lobular  carcinoma  in  situ  [LCIS])  but  may  also  be  related  to  CCLs  or  low-grade  DCIS  (Abdel-
Fatah et al., 2008). 

Infiltrating  lobular  carcinoma  is  frequently  non-palpable  and/or  mammographically  occult.  These 
lesions may also be difficult to visualise sonographically and are therefore over-represented in studies 
of interval cancer. Many of these are so-called “real” interval carcinomas without suspicious signs on 
the pre-diagnostic screening mammograms. For the same reasons, lobular carcinomas are also over-
represented in the group of occult carcinomas initially presenting with metastasis. 

Prognosis of lobular carcinoma as a group is intermediate, with a worse prognosis for pleomorphic and 
solid  types,  and  there  are  often 
lymph  node  metastases  that  may  require  cytokeratin 
immunohistochemistry  for  recognition.  Lobular  cancers  metastasise  to  the  bone  and  gastrointestinal 
tract  and  other  odd  sites,  like  ovaries,  bladder,  orbit,  serosal  surfaces  and  meninges,  in  a  higher 
frequency than other cancer types. Rare HER2-overexpressing lobular cancers may metastasise to the 
brain with increased frequency. 

Immunohistochemically,  typically  E-cadherin  and  p120  are  reduced,  either  aberrant  (cytoplasmic)  or 
negative;  ER/PR  are  positive;  HER2  is  negative;  low-molecular-weight  keratins  7,  8,  18  and  19  are 
positive  and  high-molecular-weight  keratins  CK5/6  and  CK14  are  negative,  with  the  exception  of 
34betaE12, which often shows positive staining. Most lobular cancers therefore fall into the luminal A 
molecular type, whereas a small minority will be luminal B when they overexpress HER2 or have high 
Ki67.  Metastatic  gastric  cancer  should  be  considered  as  a  differential  diagnosis  in  morphologically 
lobular cancers with no ER or PR expression. 

4.6 

Tubular carcinoma 

Tubular  carcinomas  are  composed  of  round,  ovoid,  teardrop-shaped  or  angulated  single-layered 
tubules  in  an  abundant  cellular  fibrous  or  fibro-elastotic  stroma.  The  neoplastic  cells  are  small  and 
uniform and may show cytoplasmic apical snouting. Nuclei should not show a high degree of atypia. 
At  least  90%  of  the  tumour  should  exhibit  the  classic  growth  pattern  to  be  classified  as  tubular. 
However, if the co-existent carcinoma is solely of invasive cribriform type then the tumour should be 
typed as tubular if the tubular pattern forms > 50% of the lesion. Some tubular differentiation may be 
seen in tubulolobular carcinomas (see above). Mitoses are rare. 

These  lesions  are  thought  to  derive  from  low-grade  DCIS  and  CCLs,  and  are  rarely  associated  with 
lobular neoplasia (Abdel-Fatah et al., 2008). 

The clinical presentation is usually as a palpable, mammographically and sonographically visible lesion. 
The  characteristic  radiological  appearance  is  that  of  a  stellate  abnormality,  which  can  resemble  a 
radial scar, or an asymmetric density. 

Prognosis is excellent, but lymph node metastases may occur. Rare metastases are found especially in 
bone. 

Immunohistochemically,  typically  E-cadherin  is  positive,  ER  is  positive  and  PR  usually  so,  HER2  is 
negative and CK5/6 and CK14 are negative. Almost all tubular cancers therefore fall into the luminal A 
molecular type. 

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4.7 

Invasive cribriform carcinoma 

This  tumour  is  composed  of  cribriform  islands  of  small,  uniform  neoplastic  cells,  with  cytoplasmic 
apical snouting. Nuclei should not show a high degree of atypia. More than 90% of the lesion should 
exhibit  a  cribriform  appearance,  except  in  cases  where  the  only  co-existent  pattern  is  tubular 
carcinoma  (see  above),  when  > 50%  must  be  of  a  cribriform  appearance  to  be  classified  as  of 
invasive cribriform type. There are usually very few mitoses. 

These  lesions  are  thought  to  derive  from  low-grade  DCIS  and  CCLs,  and  are  rarely  associated  with 
lobular neoplasia (Abdel-Fatah et al., 2008). 

The  clinical  presentation  is  usually  as  a  well-circumscribed,  palpable  and  mammographically  and 
sonographically visible lesion, generally not stellate as in tubular carcinoma. Prognosis is quite good, 
but lymph node metastases may occur. Rare metastases are found especially in bone. 

Immunohistochemically,  typically  E-cadherin  is  positive,  ER/PR  are  positive,  HER2  is  negative  and 
CK5/6 and CK14  are negative. Almost all invasive cribriform cancers therefore fall into the luminal A 
molecular type. 

4.8 

Mucinous carcinoma 

This type has also been known as mucoid, gelatinous or colloid carcinoma. These lesions are relatively 
well  circumscribed  and  show  cribriform  or  papillary  islands  of  uniform  cells  in  lakes  of  extracellular 
mucin. The degree of nuclear atypia and mitotic activity may vary. At least 90% of the tumour must 
exhibit a mucinous appearance to be so classified. 

Mucinous cancers can be divided into two groups: mucinous A (or paucicellular) and mucinous B (or 
hypercellular). Mucinous B  cancers display histological and genetic  features that  significantly overlap 
with those of endocrine carcinomas (Sapino et al., 2000) (see below). 

The  precursor  lesion  is  the  mucinous  form  of  DCIS  (for  both  types  A  and  B;  for  type  B,  there  will 
usually be endocrine features) or the mucinous variant of CCLs (for type A). 

The clinical presentation is usually as a palpable and well-circumscribed lesion on mammography and 
sonography, which can simulate a benign lesion. 

Prognosis is good for pure (generally low-grade) lesions, but lymph node metastases may occur. Rare 
metastases are especially found in bone. 

Immunohistochemically,  typically  ER/PR  are  positive,  HER2  is  negative  and  CK5/6  and  CK14  are 
negative. Almost all mucinous type (types A and B) cancers therefore fall into the luminal A molecular 
type. Rarely, type B mucinous cancers may be luminal B. 

4.9 

Invasive micropapillary carcinoma 

This  type  shows  an  infiltrative  growth  pattern  of  small  regular  micropapillary  groups,  not  showing 
further gland  formation (Zekioglu et al., 2004; Chen  et al., 2008). Due to fixation and expression of 
mucins on the outside of the groups, they tend to detach from the surrounding stroma and often form 
a “halo” around the groups. Microcalcification is common. Atypia and mitotic activity may vary. These 

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tumours often show prominent lymphovascular invasion, and there are in fact cases where tumour is 
only found in lymph vessels. 

The precursor lesion for this type of cancer is unclear. It is sometimes associated with micropapillary 
DCIS, but the common name does not imply a precursor relationship. 

The clinical presentation is usually as a palpable lesion visible on mammography and sonography. 

The  degree  of  lymph  node  involvement  is  high.  Prognosis  is  not  essentially  different  from  that  of 
invasive  ductal  carcinomas  of  similar  grade,  but  is  therefore  relatively  poor  because  many  are  high-
grade. There is a high rate of local recurrence. 

Immunohistochemically,  typically  E-cadherin  is  positive,  ER/PR  are  positive,  HER2  is  frequently 
positive  and  CK5/6  and  CK14  are  negative.  These  tumours  can  fall  into  the  luminal  A  or  luminal  B 
molecular  types,  depending  on  the  HER2  status  and  the  Ki67  index.  MUC1/EMA  are  present  on  the 
outer  surface  of  the  tumour  islands  (which  can  be  stained  by  EMA),  hence  the  original  “inside-out” 
carcinoma designation. 

4.10  Neuroendocrine breast cancer 

Neuroendocrine breast cancers share the peculiar architecture of solid sheets of cells with a tendency 
to  produce  peripheral  palisading  or  insular  structures  separated  by  a  delicate  fibro-vascular  stroma 
common  to  most  endocrine  tumours  in  general.  Even  more  specific  are  the  cytological  features: 
plasmacytoid, spindle or with signet ring appearance and with intracytoplasmic granules (in the apex 
of  plasmacytoid  cells  or  diffuse  in  the  cytoplasm  of  mucous  or  spindle  cells),  which  are  particularly 
evident  in  Giemsa  and  Diff-Quik-stained  smears.  There  is  also  a  variant  with  true  small-cell 
cytonuclear features like in other organs. The degree of nuclear atypia and mitotic activity varies, so 
that  these  cancers  can  be  grade  1,  2  or  3.  True  small-cell  neuroendocrine  carcinomas  should  be 
regarded  as  grade  3  by  definition.  There  may  be  some  mucinous  or  apocrine  differentiation  in  non-
small-cell types. 

The precursor lesion for this type of cancer is DCIS with similar morphological (sometimes mucinous) 
and neuroendocrine features. 

The  clinical  presentation  is  usually  as  a  palpable  lesion  visible  on  mammography  and  sonography  in 
older patients. Serum levels of (neuro)endocrine markers may be increased. 

Immunohistochemically, neuroendocrine breast carcinomas are exclusively those expressing chromo-
granin  A,  or  chromogranin  B,  or  synaptophysin  in  > 50%  of  their  cells  (Abd  El-Rehim  et  al.,  2005). 
Cancers  that  do  not  reach  this  threshold  should  be  classified  as  “breast  carcinomas  with  focal 
neuroendocrine differentiation”, which also do not  show the typical morphology overall and have an 
older age range of patients. Expression of ER and PR is variable, and there is frequently expression of 
AR  and  GCDFP-15  (BRST2),  pointing  to  apocrine  differentiation.  These  tumours,  therefore,  can  fall 
into any of the HER2 negative subtypes. 

Axillary  lymph  nodes  may  be  involved.  Prognosis  is  not  essentially  different  from  that  of  invasive 
ductal  carcinomas  of  similar  grade.  Favourable  prognostic  features  in  these  cancers  are  mucinous 
differentiation and expression of ER and PR. 

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4.11  Apocrine carcinoma 

These tumours are architecturally much like (high-grade) ductal cancers with variable morphology, but 
cytologically the cancer cells have abundant granular  or homogeneously pink (“apocrine”) cytoplasm 
and big round nuclei with conspicuous nucleoli. Mitotic activity may vary. Apocrine differentiation may 
also be seen in endocrine cancers (see above). 

The  precursor  lesion  of  apocrine  carcinoma  is  the  apocrine  variant  of  DCIS  (which  also  may  show 
variable  architecture),  and  (atypical)  apocrine  hyperplasia  may  be  the  earliest  precursor.  To  what 
extent (atypical) apocrine adenosis is a precursor is still unknown. 

The clinical presentation is usually as a palpable lesion visible on mammography and sonography. 

Prognosis and degree of lymph node involvement are not essentially different from those of invasive 
ductal  carcinomas  of  similar  grade.  HER2  positive  apocrine  cancers  metastasise  to  the  brain  with 
increased frequency. 

Immunohistochemically,  typically  E-cadherin  is  positive,  usually  ER/PR  are  negative,  HER2  is  most 
often  positive,  CK5/6  and  CK14  are  negative  and  CEA,  BRST2  and  AR  are  positive.  Most  apocrine 
cancers therefore fall into the HER2 molecular class, whereas some expressing ER/PR as well as HER2 
are  classified  as  the  luminal  B  molecular  type.  Occasional  cases  may  be  triple negative.  It  has  been 
suggested that apocrine carcinoma may be a special molecular class driven by AR signalling (Weigelt 
et al., 2008). 

4.12  Medullary-like carcinoma 

Typical  medullary  carcinomas  are  well-circumscribed  cancers  composed  of  interconnecting  solid 
epithelial  islands,  with  a  syncytial  pattern  and  often  with  necrosis.  The  epithelium  shows  highly 
atypical  nuclei  and  many  mitoses,  and  there  is  abundant  lymphoplasmocytic  infiltrate  in  and  around 
the lesion. Some squamous metaplasia may occur. 

Cancers showing many but not all of these features are classified as medullary-like, and because there 
are  few  differences  in  molecular  make-up  and  clinical  behaviour  between  typical  medullary  and 
medullary-like  cancers,  they  are  placed  together  in  this  histomolecular  classification.  There  is  clearly 
overlap  here  with  metaplastic  cancers  as  well.  Also,  many  of  the BRCA1  germline  mutation-related 
cancers  fall  into  this  group,  as  well  as  cancers  with  sporadic  inactivation  of  BRCA1  (e.g.  due  to 
promoter hypermethylation). 

These cancers are thought to derive from a similar type of DCIS expressing basal cytokeratins/EGFR, 
which  are  likely  to  originate  from  the  stem  cells  of  the  breast.  In  typical  medullary  carcinoma,  the 
presence of DCIS is, however, rare. 

The  clinical  presentation  is  usually  as  a  rapidly  growing  palpable  and  well-circumscribed  lesion  on 
mammography and sonography, which can simulate a benign lesion, often at relatively young age. 

Prognosis  is  intermediate  (not  as  bad  as  for  usual  basal  cancers),  and  brain  metastases  occur 
commonly, but interestingly lymph node metastases are rare in typical medullary type cancers. 

Immunohistochemically,  typically  E-cadherin  is  positive,  ER/PR/HER2  are  negative  and  often  CK5/6 
and/or CK14 are positive; most medullary-like cancers therefore qualify as (high-grade) basal cancers 
(Jacquemier  et  al.,  2005).  There  is  no  consensus  on  the  required  level  of  CK5/6  and/or  CK14 

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expression, but probably any expression of these basal keratins would suffice. Further, there is often 
expression  of  EGFR,  c-kit,  p63,  vimentin,  smooth  muscle  actin,  p-cadherin  and  CD10,  and 
accumulation of p53 (usually related to a p53 mutation). 

4.13  Metaplastic carcinoma 

Metaplastic  carcinomas  often  have  the  features  of  medullary-like  carcinomas,  showing  metaplasia  of 
any  kind.  Squamous  metaplasia  is  most  often  found,  but  undifferentiated  mesenchymal  areas,  or 
areas showing (smooth or striated) muscle differentiation, cartilage or bone formation, or more rarely 
nerve type differentiation may also occur. The degree of metaplasia (especially that of mesenchymal 
metaplasia) may be so abundant that the primary epithelial nature of the cancer is morphologically no 
longer,  or  hardly,  recognised  and  the  diagnosis  of  carcinoma  is  primarily  based  on  cytokeratin 
expression. Of these, especially the basal and high-molecular-weight cytokeratins may be useful. 

These usually high-grade cancers clearly overlap with the medullary-like cancers, and thereby include 
cancers in BRCA1 germline mutation carriers, as well as cancers with a sporadic inactivation of BRCA1 
(e.g. due to promoter hypermethylation). 

These cancers are thought to derive from a similar type of DCIS expressing basal cytokeratins/EGFR, 
which are likely to originate from the stem cells of the breast, and are thereby basal (Weigelt et al., 
2009). 

The  clinical  presentation  is  usually  as  a  rapidly  growing  palpable  and  well-circumscribed  lesion  on 
mammography and sonography, which can simulate a benign lesion, often at relatively young age. 

Prognosis is among the worst, and lung and brain metastases occur commonly. 

Immunohistochemically,  typically  E-cadherin  is  positive,  ER/PR/HER2  are  negative  and  CK5/6  and/or 
CK14 are positive. Most metaplastic cancers therefore qualify as (high-grade) basal cancers. There is 
no consensus on the required level of CK5/6 and/or CK14 expression, but probably any expression of 
these  basal  keratins  would  suffice.  Further,  there  is  often  expression  of  EGFR,  c-kit,  p63,  vimentin, 
smooth muscle actin, p-cadherin and CD10, and accumulation of p53. 

4.14 

Salivary gland-like cancers 

This  group  of  low-grade  cancers  comprises  salivary  gland-like  cancers  such  as  adenoid  cystic 
carcinomas  and  rarer  forms  like  acinic  cell  and  oncocytic  carcinomas.  They  show  infiltrative  growth, 
are often multinodular, and morphology may vary. The typical adenoid cystic types grow in rounded-
off epithelial groups of varying size, with some showing a cribriform pattern. There are two types of 
lumina;  the  less  abundant  type  is  epithelial,  whereas  the  lumina  lined  by  myoepithelial  cells  contain 
greyish basement membrane substance. Apocrine snouts around the lumina are lacking, which helps 
to  distinguish  them  from  the  lumina  in  tubular/cribriform  carcinomas.  Nuclear  atypia  is  usually  low, 
and  mitoses  are  typically  not  frequent.  Other  cancers  in  this  group  may  show  morphologically 
prominent  myoepithelial  differentiation.  Perineural  invasion  (which  is  prominent  in  this  tumour  type 
within salivary glands) is rare in the breast. 

In situ precursors of similar (low-grade) morphology can be found in these cancers. 

The  clinical  presentation  is  usually  as  a  palpable  lesion  visible  on  mammography  and  sonography. 
Prognosis is very good, and lymph node metastases are rare. 

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Immunohistochemically, typically E-cadherin is positive, ER/PR/HER2 are negative, CK5/6 and/or CK14 
are  positive  and  there  is  expression  of  vimentin  and  myoepithelial  markers  such  as  smooth  muscle 
actin, p63, calponin and caldesmon. Most salivary gland-like cancers are therefore classified as (low-
grade)  basal  cancers  (Foschini  &  Krausz,  2010).  Most  adenoid  cystic  carcinomas  bear  a  t(6;9)(q22-
23;p23-24) translocation,  which leads to the formation of the MYB-NFIB fusion gene (Wetterskog et 
al., 2012). 

4.15 

Secretory carcinoma 

Secretory type cancers may be considered to be almost a genetic entity due to the high frequency of 
a  ETV6-NTRK3  fusion  gene,  which  encodes  a  chimeric  tyrosine  kinase  that  has  an  oncogenic  effect 
(Reis-Filho & Lakhani, 2008). Pathologically, these lesions are less well defined. Grossly, they usually 
form  a  circumscribed  mass,  architecturally  resembling  ductal  carcinomas  but  with  microcysts  and/or 
secretory  cytology  with  bubbly  cytoplasm,  signet  cells  and  low-grade  nuclei.  DCIS  precursors  with 
similar cytology have been described. 

The  clinical presentation is usually as a palpable lesion visible on mammography and sonography at 
exceptionally young age and fairly often in males. Prognosis is very good, but lymph node metastases 
may occur. 

Immunohistochemically, typically ER/PR are negative and HER2 is negative, but  CK5/6 or CK14  may 
be  positive,  so  that  secretory  cancers  partly  fall  into  the  basal  cancer  group  but  should  not  be 
regarded as high-grade (Lae et al., 2009). 

4.16  Ductal – no special type (ductal-NST) 

This group contains infiltrating carcinomas that cannot be assigned to any other category or classified 
as any of the less common variants of infiltrating breast carcinoma. The tumour shows < 90% special 
type  characteristics.  Consequently,  invasive  ductal  carcinomas  exhibit  great  variation  in  appearance 
and are the most common carcinomas, accounting for up to 75% in published series. 

These lesions are thought to derive from DCIS or CCLs, rarely from lobular neoplasia. 

The clinical presentation is usually as a palpable, mammographically and sonographically visible lesion. 
Prognosis  of  ductal-NST  carcinomas  as  a  group  is  worse  than  that  of  most  specific  types,  and  is 
largely  dependent  on  proliferation  rate  and  grade.  Lymph  node  metastases  often  occur.  Systemic 
spread may occur to any site, with a  preference  for  bone (especially ER positive/PR positive  cases), 
liver, lung and, to a lesser extent, brain (especially HER2 positive cases). 

Immunohistochemically, E-cadherin is usually positive and there is variable expression of ER/PR, HER2 
and  the  basal  cytokeratins  CK5/6  and  CK14.  Molecularly,  ductal  cancers  therefore  spread  over  all 
molecular groups. Cases with ER and/or PR positivity and HER2 negativity are luminal A,  cases with 
ER  and/or  PR  positivity  and  HER2  positivity  or  high  Ki67  are  luminal  B,  cases  with  ER/PR  negativity 
and  HER2  positivity  are  HER2,  and  triple  negative  cases  with  CK5/6  and/or  CK14  and/or  EGFR 
expression are classified as basal. 

Many  cancers  in  patients  with BRCA2  mutations  have  “no  special  type”  morphology,  and  most  are 
molecularly  classified  as  luminal  A  because  they  express  ER  and/or  PR  but  usually  lack  HER2 
expression. 

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Also, lymphoepithelioma-like cancers are included here as they are as yet difficult to group into any of 
the  above  categories,  and  are  too  rare  to  form  a  useful  separate  entity.  Lymphoepithelioma-like 
carcinoma  is  considered  by  some  to  be  a  variant  of  invasive  lobular  cancer.  It  is  usually  well 
demarcated, with scattered pale individual cells, sometimes also forming solid groups, with vesicular 
nuclei showing only slight/moderate atypia and a small single nucleolus, mixed within a very marked 
infiltrate of lymphocytes and plasma cells. This tumour type, therefore, resembles the undifferentiated 
form  of  nasopharyngeal  carcinoma,  and  has  to  be  differentiated  from  medullary  carcinoma.  Mitotic 
activity may vary. Immunohistochemically, there is also variable expression of E-cadherin and ER/PR, 
HER2  is  mostly  negative  and  CK5/6  and  CK14  are  negative.  Epstein-Barr  virus  (EBV)  has  not  been 
convincingly demonstrated. Lymph node metastases are rare. 

4.17  Other malignant tumours 

Non-epithelial  tumours  and  secondary  carcinomas  are  included  in  this  category.  For  purposes  of 
convenience,  malignant  phyllodes  tumours  and  malignant  adeno-myoepitheliomas  should  also  be 
recorded here. 

4.18  Not assessable 

This category should be used only if an invasive carcinoma cannot be assigned to any of the previous 
groups for technical reasons, e.g. the specimen is too small or poorly preserved. 

5 

Assessing the axilla 

Axillary  nodal  status  remains  the  single  most  important  prognostic  factor  in  patients  with  breast 
cancer. For many years, axillary dissection has been  the preferred method  for obtaining information 
about  nodal  status,  but  it  has  significant  morbidity  and  node  negative  patients  are  hence 
disadvantaged. Axillary status can be assessed by various methods: clinical, radiological, pathological 
and  surgical  techniques,  the  most  accurate  of  which  is  histological  examination  of  sentinel  lymph 
nodes  (SLNs)  or  axillary  dissection.  Although  imaging  techniques  (ultrasonography  [US],  colour 
Doppler,  scintimammography,  high-resolution  computed  tomography,  etc.)  have  improved,  no 
individual  patient  can  be  managed  based  exclusively  on  these  results.  Physical  examination  is 
inaccurate because node metastases are present in 15–60% of patients with non-palpable nodes and 
absent in up to one third of patients with palpable nodes. 

5.1 

Preoperative staging 

Preoperative  staging  of  axillary  lymph  nodes  (ALNs)  should  be  performed  to  support  specific 
therapeutic  decisions.  For  example,  in  patients  with  axillary  metastases,  the  surgeon  can  save  the 
expense and time needed to perform SLN biopsy (Boughey et al., 2010); more extensive staging can 
be  planned,  and  “tailored”  neoadjuvant  chemotherapy  can  be  instituted.  US-guided  biopsy  of 
suspicious ALNs can be performed by fine-needle aspiration (FNA) using a 25 gauge needle (Bonnema 
et al., 1997; Sapino et al., 2003; Bedrosian et al., 2003; van Rijk et al., 2006) and/or by core needle 

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biopsy (CNB) using a 14–18 gauge needle (Damera et al., 2003; Nori et al., 2005; Abe et al., 2007; 
Rao  et  al.,  2009);  the  choice  is  mainly  operator-  and  institution-dependent.  Specificity  for  both 
methods is high (95.7–100%), and sensitivity varies for both, depending on the selection criteria and 
number  of  passes.  According  to  some  authors  (Rao  et  al.,  2009),  as  far  as  diagnosis  is  concerned 
there  is  no  clear  advantage  for  either  technique.  Given  the  necessary  expertise,  FNA  may  allow 
equivalent sensitivity at a lower cost. FNA is also preferred by many units due to the proximity of large 
vessels  and  nerves.  US-guided  ALN  biopsy  can  detect  up  to  64%  of  node  positive  patients 
preoperatively (Damera et al., 2003; Rao et al., 2009). 

Image-guided and fine-needle aspiration cytology (FNAC) or CNB of suspicious nodes can improve the 
preoperative axillary staging of patients with breast cancer, avoiding a 2-stage axillary procedure and 
sparing as many as 1–26% of patients open lymph node biopsies (Krishnamurthy et al., 2002; Ciatto 
et al., 2007). 

Handling of FNA and CNB material should follow the procedures in Chapters 6a and 6b of the fourth 
edition (Wells et al., 2006a). 

Diagnosis  is  usually  straightforward  when  representative  material  is  available  with  good  technical 
quality; most false-negative cases correspond to “small” metastases. 

All cases of primary invasive breast cancer with negative results for metastatic disease on FNA or CNB 
are candidates for a SLN biopsy or other axillary procedure for definitive staging. 

To  validate  the  diagnosis  of  metastasis  from  breast  cancer,  the  morphology  of  the  neoplastic  cells 
present in lymph node FNA or CNB material should be compared with that of the primary tumour by 
review of the preoperative FNA or CNB material of the primary breast carcinoma because metastases 
are usually similar to the primary tumour. 

5.2 

Problems and pitfalls 

Although the aim of preoperative study is the search for metastases, caution should be taken to avoid 
overlooking other causes of axillary lumps. 

5.2.1 

Epidermal cysts and skin appendage tumours 

Inflammatory  processes  can  occur  from  skin  appendages.  In  these  cases,  an  inflammatory 
background  and  the  presence  of  squamous  epithelial  cells  should  alert  the  pathologist  to  a  benign 
lesion. Apocrine cells may also be included from neighbouring apocrine sweat glands and may cause 
some  problems.  Skin  appendage  tumours  may  also  be  a  challenge  because  the  morphology  and 
immunohistochemical  profile  can  be  quite  similar  to  those  of  breast  tumours.  The  clinical  setting 
combined with US should allow a correct diagnosis. Axillary breast tissue may also give rise to benign 
epithelial clusters in smears. 

5.2.2 

Lymph node inclusions 

Benign  epithelial  or,  rarely,  mesothelial  inclusions  in  lymph  nodes  can  also  occur  in  approximately 
0.3%  of  cases  and  may  be  difficult  to  recognise  due  to  their  cytokeratin  positivity.  Naevus  cell 
inclusions also occur. 

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5.2.3 

Granulomatous inflammatory processes 

Epithelioid macrophages can mimic carcinoma cells. They are associated with other inflammatory cells 
in  the  smear,  and  the  presence  of  multinucleated  macrophages  should  prevent  a  false-positive 
diagnosis.  In  case  of  doubt,  cytokeratin  immunocytochemistry  may  solve  the  differential  diagnostic 
problem. Whenever necrosis is present, microbiological or serological studies must be done to rule out 
the possibility of a specific infection (tuberculosis, cat scratch disease, etc.). 

5.2.4 

Dermatopathic lymphadenopathy 

Melanophages can mimic carcinoma cells if the load of melanin is low. Usually the smears are not very 
rich in these cells and they are isolated or aggregated to vascular stroma. In case of doubt, immuno-
staining (CD68, etc.) easily confirms the histiocytic origin of these cells. 

5.2.5 

Lipoma 

Mature adipose tissue can originate from a lipoma or from an adipose lymph node; only the presence 
of lymphoid cells can indicate the origin of the lump. The absence of carcinoma cells does not rule out 
the possibility of metastases, although their occurrence in adipose lymph nodes is not frequent. 

5.2.6  Metastatic tumours 

Melanoma 

ALN metastasis of melanoma is a difficult  differential diagnosis. An amelanotic  melanoma can mimic 
breast cancer metastasis and this differential diagnosis can be particularly difficult in FNA. However, 
metastases  from  melanoma  frequently  contain  mono-,  bi-  and  multinucleated  malignant  cells.  The 
cells  also  are  polyhedric  and/or  fusiform  with  intranuclear  pseudo-inclusions  and  prominent  nucleoli. 
Before  looking  at  an  ALN  sample,  a  review  of  the  primary  breast  carcinoma  is  important  because 
metastases are usually similar to the primary tumour. Although melanoma can be a mimicker, it can 
be recognised and even in the absence of a clinical history, immunostaining (HMB45, pS100, etc.) is 
diagnostic. 

Carcinoma (other than breast) 

When  a  peculiar  pattern,  unusual  for  breast  cancer,  is  seen,  another  metastatic  tumour  should  be 
considered. A careful clinical history complemented by image study will resolve most problems. 

Lymphoma 

Hodgkin  cells  may  mimic  carcinoma  cells;  however,  the  comparison  with  the  primary  tumour,  the 
relative  paucity  of  malignant  cells  and  the  presence  of  eosinophils  may  alert  the  pathologist  to  the 
diagnosis of Hodgkin lymphoma. 

Whenever a non-Hodgkin lymphoma, especially small-cell lymphocytic lymphoma or lymphomas with 
plasmacytoid  differentiation,  is  considered,  haematological  assessment,  immunophenotyping  and/or 
open tissue biopsy is indicated. 

5.3 

Examination and interpretation of sentinel lymph node 

biopsy specimens 

Since  the  publication  of  the  fourth  edition  (Wells  et  al.,  2006a),  new  problems  and  techniques  have 
emerged in relation to nodal staging, reflected in the TNM classification, which is now in its seventh 
edition  (Sobin  et  al.,  2009).  Although  the  basic  principles  have  not  changed,  it  was  considered 

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necessary  to  update  the  pathology  chapter  (Chapter 6)  with  a  supplement  addressing  some  of  the 
difficulties experienced since the fourth edition was published. 

5.3.1 

Isolated tumour cells (ITCs) 

The aim  of pathological nodal staging is to make a statement about the  status  of the lymph  nodes, 
either node negative or node positive. The nodes are usually axillary, but very occasionally from other 
locations.  On  the  basis  of  the  SLN  theory,  the  SLNs  are  the  first  nodes  draining  lymph  from  the 
tumour site and are therefore the most likely site of nodal metastasis. With selective removal of these 
lymph nodes, there is an opportunity for more detailed pathological work-up of these, and indeed the 
SLNs  are  subjected  to  more  intensive  investigations.  However,  the  techniques  used  vary  from 
institution to institution, and this heterogeneity is partly responsible for  discrepancies in the rates of 
node positive breast cancer reported by different centres. 

The pTNM is the staging system generally used. In its sixth edition, this classification introduced the 
concept  of  a  type  of  nodal  involvement  (termed  isolated  tumour  cells;  ITCs)  that  should  not  be 
considered a metastasis from the point of view of staging and treatment. ITCs may be identified either 
by  morphological  methods  [pN0(i+)]  or  by  molecular  studies  [pN0(mol+)].  Whenever  the  lymph 
nodes  are  investigated  for  such  lesions  but  the  results  are  negative,  the  pN0(i-)  and  pN0(mol-) 
symbols are recommended by the TNM definitions. Although it is clear that pN0(i+) may reflect both 
ITCs  detected  by  the  standard  haematoxylin  and  eosin  (H&E)  staining  and  those  detected  by 
immunohistochemistry (IHC), the seventh edition of the TNM classification (Edge et al., 2009; Sobin et 
al., 2009) clarifies that pN0(i-) should be used only for negative IHC findings. 

It  was  found  to  be  common  practice  to  evaluate  SLNs  at  multiple  levels. Gross slicing of the SLNs 
(and, in some recommendations, any lymph node) larger than 5–6 mm and H&E staining of one level 
per such slice is recommended in nearly all protocols. When this investigation or step sections by H&E 
staining disclose no nodal involvement of any type, the pN0 category without any qualifiers should be 
used,  and  pN0(i-)  should  be  reserved  for  negative  investigations  beyond  this  limit,  i.e.  negative 
findings by IHC. Because this still allows several levels of precision in staging, it is considered optimal 
to report the method of SLN investigation. 

The definition of ITCs and their distinction from micrometastases was suboptimal and did not allow a 
reproducible segregation of low-volume nodal involvement into these two pTNM categories (Cserni et 
al., 2005; Cserni et al., 2006; de Mascarel et al., 2008). Although the classification of metastatic cells 
into the ITC category on the basis of the largest cluster not exceeding 0.2 mm in maximum diameter 
may have resulted in better reproducibility (Turner et al., 2008), this sometimes included rather large 
volume lesions, which were found to be associated with metastases beyond the SLNs more commonly 
than  ITCs  interpreted  with  a  more  restrictive  approach  (Cserni  et  al.,  2008;  Turner  et  al.,  2008; 
Cserni, 2009; van Deurzen et al., 2010). The seventh edition of the TNM classification has introduced 
an alternative upper limit of 200 cells for ITCs (Edge et al., 2009; Sobin et al., 2009), and this should 
reduce  the  diagnostic  discrepancies  between  different  centres  and  also  help  to  eliminate  the 
unacceptable  practice  of  labelling  relatively  extensive  metastatic  involvement  of  a  lymph  node  as 
pN0(i+).  Any  lymph  node  involvement  > 0.2 mm  but  < 2 mm  in  any  of  the  3  dimensions  is 
categorised as a micrometastasis. According to the current TNM classification (Edge et al., 2009), the 
0.2 mm size cut-off relates to the maximum diameter of the largest tumour cell cluster. There may be 
instances  of  nodal  involvement  with  the  largest  cluster  measuring  < 0.2 mm  in  diameter  but 
containing > 200 cells, and vice versa, clusters > 0.2 mm in diameter with < 200 cells. Size should be 
considered first, and the cell count only if the largest cluster is < 0.2 mm (Cserni et al., 2011). 

5.3.2  Methods of nodal assessment 

One  of  the  aims  of  the  European  guidelines  is  to  decrease  heterogeneity  in  staging.  These  should, 
therefore, concentrate on the reliability and accuracy of determining a node negative status. 

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The guidelines state that the minimum aim of SLN investigation is to find all metastases greater than 
2 mm  in  diameter  (hereafter  referred  to  as  macrometastasis).  It  therefore  follows  that  any  SLNs 
reported to be pN0 or pN0(i-) should be interpreted that the SLN contains no metastasis greater than 
2 mm in diameter (but may still contain micrometastasis or ITCs). Therefore, by devising a protocol to 
detect  all  macrometastases,  the  aim  is  to  promote  optimal  accuracy  for  identifying  node  negative 
status related to macrometastases as near to 100% as possible (100% negative predictive value). 

Similarly,  when  the  guidelines  state  that  the  optimum  aim  in  staging  is  to  find  (nearly)  all 
micrometastases in the SLNs, they are also designed to identify a pN0 or pN0(i-) node negative status 
as near to a 100% predictive value for the lack of micrometastases as possible. 

The identification of ITCs in the initial levels mandates a search for a larger metastasis in the same 
SLN, and levels should be cut to exclude the possibility of the ITC cluster being a smaller tangentially 
cut part of a larger metastasis. This would confirm the initial staging correctly as pN0(i+). 

The  pN0  or  pN0(i-)  category  reflects  that  no  ITCs  were  identified  by  the  histological  protocol  used, 
although they may be present, just as occult metastases of other size may be present, depending on 
the  sampling  of  the  lymph  node.  This  is  why  a  systematic  search  is  recommended  and  the  method 
used  should  be  reported,  as  stated  previously.  Optimally,  the  accuracy  of  staging  should  also  be 
mentioned, at least in unit protocols (e.g. pN0(i-) with the examination of levels separated by 500 µm 
devised  to  identify  metastases  not  smaller  than  500 µm  in  greatest  dimension;  or  pN0  with  the 
examination  of  4  levels  separated  by  250 µm  from  each  slice  approximately  2 mm  in  thickness, 
devised to identify metastases not smaller than 1 mm in greatest dimension). 

No reasonable histological method can aim to identify ITCs with 100% accuracy in the SLNs, but some 
reports  have  suggested  that  ITCs  identified  incidentally  with  protocols  devised  to  identify  larger 
metastases also have some impact on prognosis (Colleoni et al., 2005; de Boer et al., 2009). 

5.3.3 

Intraoperative assessment 

The sensitivity and positive predictive value of the intraoperative assessment of SLNs can be improved 
by specific techniques such as rapid immunohistochemistry and molecular testing of the lymph nodes. 

Immunohistochemistry is most useful in cases of lobular carcinomas with micrometastatic involvement 
of  the  SLN,  but  can  also  help  to  identify  larger  metastases,  and  facilitate  later  paraffin  section 
evaluation (Nahrig et al., 2003; Leikola et al., 2005; Choi et al., 2006). 

Molecular  (RT-PCR-based)  assays  may  detect  ITCs  in  greater  proportion  than  histological  methods, 
but cannot be optimally validated against the gold standard method of histology because of sampling 
biases. Validation can partially be made against other validated molecular assays. 

The  first  group  of  RT-PCR-based  nodal  staging  tests  looked  purely  at  the  presence  or  absence  of 
mammary epithelial (e.g. CK19, MUC-1, mammaglobin) or tumour cell markers (e.g. carcinoembryonic 
antigen, MAGE-3) and were confounded by many technical biases. Such tests should not be used for 
routine purposes (Cserni et al., 2003). 

The  second  generation  of  tests  are  based  on  quantitative  real-time  or  other  mRNA  amplification 
assays, and these, with a well-chosen cut-off value, may exclude false-positive cases with reasonable 
accuracy (Visser et al., 2008; Viale et al., 2008; Julian et al., 2008; Mansel et al., 2009; Castellano et 
al., 2012). Such assays, by means of being quantitative, can also be calibrated in a way to exclude the 
histological  category  of  ITC  (i.e.  the  pN0(i+)  category)  and  have  been  successfully  used  in  the 
intraoperative  setting.  They  also  allow  more  tissue  to  be  sampled  (and  homogenised).  The  main 
problem  remains  that  of  sampling  (Daniele  et  al.,  2009).  If  the  tissue  is  used  intraoperatively  for  a 
molecular assay, it can no longer be used for histology, and vice versa. While the staging categories 
remain defined by size, this should be measured and therefore histology will remain the gold standard 

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unless equivalence between a metastasis measuring a given size and a given amount of mRNA can be 
established in the future. 

It must be noted that a validated quantitative molecular assay is designed to detect nodal involvement 
greater than ITCs but the pN0(mol+) category recommended by both the sixth and seventh editions 
of the TNM classification does not take this into account. We therefore recommend that such cases be 
reported as “node positive (pN1) with ... (named) molecular assay”. Validation studies for some of the 
quantitative molecular assays have already been published (Cserni, 2012). 

When  testing  SLNs  in  the  intraoperative  setting,  a  compromise  should  be  made  between  the  use  of 
practically the whole lymph node for the molecular assay (aiming at the highest accuracy in staging) 
and the use of a part of the SLN for histology and using the residuum for the molecular assay (aiming 
at  increasing  the  accuracy  of  staging,  but  also  facilitating  a  more  complex  histological  evaluation  of 
the  lymph  node).  Many  pathologists  would  agree  that  no  molecular  assay  should  be  carried  out 
without a morphological examination of the nodal tissue because the molecular staging assay is simply 
a  test  for  the  presence  or  absence  of  metastases,  whereas  histology  is  a  more  complex  diagnostic 
method capable of identifying other nodal disorders too. Thus, should the first approach of using the 
whole  SLN  for  molecular  assay  be  favoured,  it  is  recommended  that  at  least  a  frozen  section  or  a 
(touch or scrape) cytology specimen be taken, examined and archived by pathologists for microscopic 
evaluation of the SLN tissue. 

In the non-intraoperative setting, histology is the method of choice for SLN assessment (Khaddage et 
al., 2011; Cserni, 2012; Castellano et al., 2012). 

The  findings  of  the  ACOSOG  Z0011  trial,  suggesting  that  SLN  micrometastases  do  not  adversely 
impact  on  prognosis  and  challenging  the  view  that  all  patients  with  a  positive  SLN  require  complete 
ALN  clearance,  has  led  to  a  reduction  in  the  need  for  intraoperative  SLN  evaluation  (Giuliano  et  al., 
2011). 

6 

Microinvasive carcinoma 

A  frequently  encountered  problem  in  the  histological  examination  of  in  situ  carcinoma  is  identifying 
the  smallest  focus  or  foci  of  invasive  carcinoma  (Boecker  et  al.,  2006),  so-called  microinvasive 
carcinoma (MIC). 

Although  microinvasion  is  virtually  almost  exclusively  associated  with  high  nuclear  grade  comedo 
DCIS, it may also be associated with other types of DCIS and with LCIS. Microinvasion is reported to 
be  related  to  the  size/extension  of  associated  in  situ  carcinoma.  The  incidence  rate  of  MIC  ranges 
from 0.68% to 2.4%. 

The  current  prevailing  view  is  that  MIC  appears  to  have  an  excellent  prognosis  with  a  low  risk  of 
associated  ALN  metastasis,  but  the  reported  incidence  of  ALN  metastasis  ranges  from  0%  to  20% 
(Bianchi & Vezzosi, 2008). 

By  general  agreement,  SLN  biopsy  is  the  standard  procedure  in  the  treatment  of  patients  with  this 
type of lesion due to the possibility of ALN metastasis in MIC. Because most MICs with a positive SLN 
have low-volume metastases and consequently a low risk of additional metastases in ALNs, the role of 
complete ALN dissection is still debated. 

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From  a  practical  point  of  view,  as  mammographically  detected  microcalcifications  considered  to  be 
associated  with  in  situ  breast  carcinoma  are  preoperatively  assessed  by  percutaneous  core  biopsy 
(NCB) or vacuum-assisted needle core biopsy (VANCB), an accurate histological diagnosis identifying 
microinvasion  on  core  biopsy  enables  a  SLN  biopsy  and  excision  of  the  primary  tumour  to  be 
performed in a single surgical session (Bianchi & Vezzosi, 2008). 

6.1 

Definition 

MIC is defined as a tumour in which the dominant lesion is in situ carcinoma (usually extensive high 
nuclear grade DCIS,  but rarely other types of DCIS  or LCIS) in which there are one  or more clearly 
separate  foci  of  infiltration,  usually  into  non-specialised  interlobular  (Tavassoli  &  Eusebi,  2009)  or 
interductal  fibrous  or  adipose  tissue,  none  measuring  > 1 mm  (about  2  high-power  fields)  in 
maximum diameter. When there are multiple foci of MIC, only the size of the largest focus is used to 
classify  the  microinvasion;  the  presence  of  multiple  foci  of  microinvasion  should,  however,  be  noted 
and/or quantified. This definition is very restrictive, and tumours fulfilling the criteria are consequently 
rare (Sloane, 1991). 

A  focus  of  invasive  carcinoma  1 mm  or  smaller  without  associated  in  situ  carcinoma  is  not  MIC  but 
should  be  classified  as  invasive  carcinoma  and  the  maximum  diameter  measured,  in  contrast  to  the 
statement  in  the  seventh  edition  of  the AJCC Cancer Staging Manual/Handbook  (Edge  et al.,  2009). 
The  AJCC  include  small  invasive  tumours  not  exceeding  1 mm  without  in  situ  carcinoma  in  the 
microinvasive category. 

The  fifth  edition  of  the  TNM Classification of Malignant Tumours,  published  in  1997  (Sobin  & 
Wittekind,  1997),  was  the  first  one  that  recognised  a  specific  T  substage  for  MIC,  defined  as  “the 
extension  of  cancer  cells  beyond  the  basement  membrane  into  the  adjacent  tissues  with  no  focus 
more than 0.1 cm in greatest dimension” and formally reported it as pT1mic. 

In  the  2003  edition  of WHO Classification of Tumours, Pathology and Genetics of Tumours of the 
Breast and Female Genital Organs  (Sobin  &  Wittekind,  1997;  Tavassoli  &  Devilee,  2003),  it  is 
reported,  in  spite  of  the  pT1mic  category  officially  being  recognised  by  the  fifth  edition  of  the TNM 
Classification of Malignant Tumours (Sobin  &  Wittekind,  1997),  that  there  is  no  generally  accepted 
agreement  on  the  definition  of  MIC,  particularly  about  the  maximum  diameter  compatible  with  a 
diagnosis  of  microinvasion.  On  this  basis,  MIC  is  still  considered  an  evolving  concept  that  has  not 
reached the status of a WHO-endorsed disease entity. In the seventh edition of the TNM classification, 
this is referred to as pT1mi. 

6.2 

Pathological diagnosis 

The tumour focus/foci must usually invade into non-specialised interlobular or interductal stroma. The 
cells deemed to be invasive should be distributed in a non-organoid pattern that does not represent 
tangential  sectioning  of  a  duct  or  lobular  structure  involved  by  in  situ  carcinoma.  Tangentially 
sectioned foci of in situ carcinoma that simulate microinvasion are within the specialised intralobular 
and periductal stroma and usually occur as compact groups of tumour cells that have a smooth border 
surrounded  by  a  circumferential  layer  of  myoepithelial  cells  and  stroma  or  a  thickened  basement 
membrane (Rosen, 2009). 

At  the  sites  of  microinvasive  foci,  tumour  cells  are  distributed  singly  or  as  small  groups  that  have 
irregular shapes reminiscent of conventional invasive carcinoma with no particular orientation (Rosen, 
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The  absence  of  basement  membrane  material  around  nests  of  tumour  cells  defines  the  process  as 
being invasive. IHC for basement membrane components (laminin and type IV collagen) is helpful in 
demonstrating the presence or absence of basement membrane (Schnitt, 1998) even though IHC for 
laminin  and  type  IV  collagen  is  reported  to  be  technically  problematic  in  formalin-fixed,  paraffin-
embedded  tissue  (Schnitt,  1998).  Unfortunately,  cells  of  invasive  cancer  can  still  synthesise  some 
components  of  basement  membrane  around  invasive  nests;  therefore,  the  use  of  basement 
membrane  markers  for  the  detection  of  stromal  invasion  is  not  formally  recommended  and,  when 
performed, should be interpreted with caution (Yaziji et al., 2000). 

The  presence  of  myoepithelial  cells  around  nests  of  carcinoma  cells  defines  the  process  as  being  in 
situ. IHC for myoepithelial cells has been used to help to determine whether a process represents in 
situ  carcinoma  or  stromal  invasion  (Schnitt,  1998).  A  variety  of  markers  have  been  used  to  detect 
myoepithelial cells. At present, the most commonly used antibodies are smooth-muscle myosin heavy 
chain  (SMM-HC)  and  calponin;  these  are  more  specific  for  myoepithelial  cells  than  actin  antibodies 
(such  as  1A4  and  HHF-35  clones)  and  react  less  commonly  with  myofibroblasts.  SMM-HC  is  not  a 
perfect  marker  of  myoepithelial  cells  because  it  manifests  slightly  lower  sensitivity  than  calponin. 
Therefore, the optimal sensitivity and specificity of myoepithelial cell markers  can be achieved when 
the SMM-HC marker is used in conjunction with the  more sensitive but less specific marker calponin 
(Yaziji et al., 2000). 

In a more recent study (Werling et al., 2003), antibodies to p63, a member of the p53 gene family, 
have  been  reported  to  offer  excellent  sensitivity  and  increased  specificity  for  myoepithelial  cells 
relative  to  antibodies  to  calponin  and  SMM-HC.  p63  antibodies  have  the  following  diagnostic 
limitations: (1) they occasionally demonstrate an apparently discontinuous myoepithelial layer around 
nests  of  in  situ  lesions  and  (2)  they  react  with  a  small  but  significant  subset  of  breast  carcinoma 
tumour  cells,  especially  in  tumours  with  a  basal  phenotype;  however,  this  aberrant  reactivity  rarely 
causes diagnostic difficulty. p63 can complement or replace SMM-HC and/or calponin in the analysis of 
microinvasion  because  of  its  near-perfect  sensitivity  and  near-absolute  specificity  in  distinguishing 
myoepithelial cells from myofibroblasts. Detecting microinvasion can be difficult when there is marked 
periductal fibrosis or inflammation; in these cases,  IHC for cytokeratin may be useful to  confirm the 
presence of separate foci of neoplastic cells embedded in periductal fibrosis or inflammation. 

The diagnosis of microinvasion still remains problematic, even with the use of ancillary techniques. If 
there  is  sufficient  doubt  about  the  presence  of  microinvasion  (i.e.  in  cases  with  marked  fibrosis  or 
inflammation), the case should be classified as in situ carcinoma with possible microinvasion. 

The  diagnosis  of  MIC  depends  principally  on  the  tissue  sampling.  MIC  cannot  be  reliably  excluded 
unless  all  tumour  tissue  is  completely  embedded  and  submitted  for  histological  examination.  This 
method  is  now  recommended  in  clinical  guidelines  (Olivotto  &  Levine,  2001)  as  well  as  in  breast 
screening programmes (National Coordinating Group for Breast Screening Pathology, 2005). However, 
it is well known that even with a large number of paraffin blocks, only a part of the tissue is examined 
microscopically and pathologists can never be absolutely certain that microinvasion is really absent. 

Serial sections supported by IHC usually provide the  best evidence of microinvasion. Care should be 
taken to perform IHC early in the evaluation of suspected microinvasion, before the blocks have been 
sectioned  excessively  (Rosen,  2009),  first  to  confirm  microinvasion  and  second  to  exclude  the 
possibility of larger invasive foci. 

6.3 

Differential diagnosis 

Microinvasion  is  one  of  the  most  commonly  overdiagnosed  events  (if  not  the  most  commonly 
overdiagnosed event) in the pathology of breast carcinoma. 

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A  variety  of  patterns  in  DCIS  and,  more  rarely,  in  LCIS  may  be  misinterpreted  as  stromal  invasion. 
Schnitt has summarised lesions and artefacts commonly mistaken for microinvasion (Schnitt, 1998): 

•  DCIS involving lobules (“lobular cancerisation”); 

•  chronic inflammatory reaction present in association with, and obscuring, involved ducts and acini; 

•  branching of ducts; 

•  distortion or entrapment of involved ducts or acini by fibrosis (due to a prior needling procedure); 

•  crush artefacts; 

•  cautery effects; 

•  artefactual displacement of DCIS or LCIS cells into the surrounding stroma or adipose tissue due to 
tissue  manipulation  or  a  prior  needling  procedure.  In  cases  with  a  history  of  a  prior  needling 
procedure  (FNA,  NCB  or  VANCB),  the  diagnosis  of  MIC  should  be  made  with  caution  because 
artefactual  disruption  of  the  epithelial-stromal  junction  of  glandular  structures  involved  by  in  situ 
carcinoma  is  not  infrequently  encountered  in  the  subsequent  excision  biopsy  or  therapeutic 
specimen.  Granulation  tissue,  old  or  recent  haemorrhage  (iron-laden  macrophages,  cholesterol 
crystals),  tissue  tears  and  a  degenerative  appearance  of  the  dislodged  tumour  cells  can  help  in 
distinguishing pseudo-invasion from true invasion (Tavassoli, 1999); 

•  DCIS or LCIS involving benign complex sclerosing lesions such as radial scars, sclerosing adenosis, 

sclerosing papilloma, ductal adenoma. 

7 

Pathological reporting of post-
chemotherapy specimens 

Pathological  assessment  of  resections  after  primary  or  neoadjuvant  chemotherapy  can  be  difficult  if 
there has been a complete response, if there is insufficient information about the site of the original 
tumour  and  whether  the  lesion  is  uni-  or  multi-focal.  When  neoadjuvant  chemotherapy  is  contem-
plated, the clinician who performs the core biopsy may insert a permanent marking device such as a 
metallic  marker  or  tattoo  (Dash  et  al.,  1999),  which  can  be  identified  in  the  specimen  (see  below). 
The  pathologist  should  also  have  access  to  radiological  information  such  that,  where  a  marker  may 
not  have  been  placed,  the  original  quadrant  and  site  of  the  tumour  can  be  assessed  to  accurately 
identify any residual tumour. In this respect, MRI findings are generally preferred because these are 
often  more  detailed  than  US  or  mammographic  examination  (Londero  et  al.,  2004).  It  is,  however, 
recommended that all cases undergoing preoperative chemotherapy should have some form of marker 
inserted  to  avoid  problems  with  the  subsequent  localisation  of  the  tumour.  This  is  particularly 
important in cases with complete response having wide local excision because it can be impossible to 
be  certain  that  the  site  of  the  tumour  nidus  has  been  removed  with  a  conservation  procedure.  To 
ensure  that  the  tumour  site  is  completely  removed,  some  units  tattoo  the  skin  with  4  tattoos  to 
delineate the maximum tumour size. It is recommended that some form of marking of the extent of 
the tumour pre-chemotherapy be performed either by this method or an equivalent system. The pre-
chemotherapy core biopsy should always be reviewed in parallel to assess response. Some units give 
an assessment of the number of cores involved. 

Specimens  from  cases after primary or neoadjuvant chemotherapy should be orientated and sent to 
the laboratory in a similar way to the specimen delivery of other specimens and as described in the 
fourth  edition  (Wells  et  al.,  2006b).  Adequate  prompt  fixation  is  as  important  here  as  in  any  other 
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7.1 

Macroscopic examination 

Macroscopic  examination  of  post-chemotherapy  specimens  should  be  performed  in  a  similar  manner 
to wide local excision or mastectomy specimens as recommended in the fourth  edition (Wells  et al., 
2006a) and the margins painted according to the standard local protocol in place. Post-chemotherapy 
tumours may be obvious if there has been little response, and these specimens are really no different 
to handle from any primary resection specimen. In this case, reference to the protocol in the fourth 
edition (Wells et al., 2006a) or a local protocol based on these will suffice. If there has been a good 
response, however, the tumour may be soft, pale and/or ill-defined and identification and sizing of the 
residuum may be impossible. Often, an oedematous area of fibrosis may be all that can be seen or if 
there is associated calcification, radiographic examination of the specimen and/or radiography of the 
subsequent slices may be  helpful (Pinder et al., 2007). If a clip or wire coil has been used, this can 
also be identified by specimen radiography and attention directed to this area. The clip or coil should 
be macroscopically visible and should be removed before taking blocks of the area. If a tattoo method 
has  been  used  to  identify  the  site  of  the  tumour  then  this  area  should  be  easily  identified 
macroscopically.  If  there  has  been  no  pre-chemotherapy  marking  and  there  has  been  a  good 
response, it may be very difficult to identify the tumour. In this case, the original site of the tumour 
should  be  identified  based  on  the  MRI  or  radiology  as  above,  and  this  area  should  be  extensively 
sampled. 

Post-chemotherapy  specimens  should  be  sliced  at  regular  intervals  (not  more  than  1 cm  for 
mastectomy  and  0.5 cm  for  wide  local  excision  specimens)  such  that  reconstruction  of  the  residual 
tumour size can be performed accurately in the third dimension by multiplying the number of slices in 
which tumour is seen by the thickness of the slices (Apple & Suthar, 2006). Any multicentricity should 
be  sought  by  reference  to  the  radiology  and  by  careful  macroscopic  examination.  Large  blocks  may 
also be useful in this regard. 

Lymph nodes should be blocked in the routine manner recommended in the fourth edition, depending 
on the procedure (see Section 6b.3 in the fourth edition). Often preoperative nodal staging will have 
been  attempted,  sometimes  by  preoperative  US-guided  FNA  or  biopsy  or  by  a  pre-treatment  SLN 
procedure.  The  latter  may  make  the  axillary  assessment  more  difficult  due  to  fibrosis.  There  is  a 
suggestion that a decreased yield of nodes may be found (Baslaim et al., 2002). 

7.2 

Microscopic examination 

If residual tumour is identified then there is no problem, but if there has been a complete response, 
there may be difficulty in confirming the original tumour site. As noted above, this can be critical to 
ensure  that  the  nidus  has  been  removed  in  those  tumours  being  treated  by  wide  local  excision. 
Microscopy  of  the  original  tumour  site  often  shows  a  scarred  area  with  distortion  of  the  normal 
architecture. Normal breast structures are effaced in this area, and there is often a macrophage and 
chronic  inflammatory  response,  with  the  macrophages  often  containing  iron  pigment,  haemosiderin 
and  debris.  Oedema  or  necrosis  may  be  present,  and  the  stroma  is  also  frequently  altered  from 
normal  breast  stroma  (Pinder  et  al.,  2007).  It  is  also  important  to  assess  both  the  cellularity  and 
extent  of  the  residual  tumour.  An  indication  of  the  extent  can  be  assessed  by  documenting  the 
number of involved blocks or slices per total number examined from the abnormal area. 

Preoperative  chemotherapy  can  extensively  alter  tumours  such  that  identifying  isolated  residual 
tumour cells can be difficult. Immunocytochemical staining with a broad-spectrum cytokeratin such as 
AE1/AE3 can be helpful in this respect. 

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Chemotherapy may effectively sterilise the invasive tumour but may leave in situ changes or lymphatic 
vessel emboli relatively unchanged (Honkoop et al., 1997). It should be also noted that normal lobules 
may show apocrine changes and severe nuclear atypia post-chemotherapy. 

7.3 

Reporting of prognostic and predictive factors 

Tumour  size,  grade,  typing  and  predictive  factors  (ER,  PR  and  HER2)  are  extensively  altered  by 
chemotherapy, and in general the pre-treatment core biopsy is recommended for assessment of these 
prognostic factors. One should, however, realise that IHC for HER2 may yield both false-negative and 
false-positive  results  on  core  biopsy  and  that  grading  is  a  little  less  reliable  on  core  biopsy  alone 
(Harris et al., 2003; Rakha & Ellis, 2007). Chemotherapy should not be given without a representative 
core biopsy of the tumour  before treatment, and trial or research protocols also recognise this (e.g. 
NEOTANGO).  Although  grading  may  retain  prognostic  value,  in  general  these  prognostic  factors  are 
best  assessed  on  the  preoperative  core  biopsy  until  large  amounts  of  data  become  available  from 
neoadjuvant trials to contradict this advice. As regards ER, PR and HER2 status, there are conflicting 
results  in  the  literature  and  because  of  this  and  the  possibility  of  complete  response,  it  is 
recommended to assess these parameters on the pre-treatment core biopsy. 

7.4 

Microscopic reporting of lymph nodes 

Assessment of lymph nodes should take into account the number of nodes containing residual tumour, 
the  number  showing  fibrosis  with  other  associated  features  of  tumour  regression,  such  as 
haemosiderin-containing  macrophages,  and  alteration  of  nodal  architecture.  All  nodes  identified 
macroscopically should be submitted for histology, and a careful search for occasional residual cells in 
fibrotic  nodes  should  be  undertaken,  including  the  use  of  IHC  for  broad-spectrum  cytokeratins,  e.g 
AE1/AE3  or  MNF116,  where  necessary.  There  is  some  evidence  that  patients  with  evidence  of 
response  of  nodal  metastases  and  regression  of  metastases  have  better  disease-free  survival  than 
those  with  persistent  metastases  (Newman  et  al.,  2003).  Because  of  this,  the  number  of  nodes 
assessed to have evidence of tumour regression should also be recorded. 

7.5 

Reporting of tumour response 

There  are  several  histopathological  classifications  of  response  to  chemotherapy,  but  there  is  no 
current  consensus  favouring  any  particular  system.  This  hampers  the  comparison  of  response 
between  different  studies.  Systems  evaluating  both  the  response  of  the  primary  tumour  and  the 
response  in  nodes  are  conceptually  most  likely  to  be  more  accurate  in  predicting  the  outcome,  but 
hard evidence for this is lacking. Most systems acknowledge that complete histopathological response 
is an excellent prognostic sign, and this was the basis for Feldman’s classification in 1986 (Feldman et 
al.,  1986).  This  has  been  largely  superseded  by  classifications  such  as  those  of  Chevallier  et  al. 
(Chevallier et al., 1993) and Sataloff et al. (Sataloff et al., 1995). In some countries, the Miller-Payne 
system is used (Ogston et al., 2001). 

Pinder  et  al.  (Pinder  et  al.,  2007)  proposed  a  classification  of  response  along  the  lines  of  that 
proposed by Sataloff et al. (Sataloff et al., 1995) (see Table 3). An approach such as this is logical and 
includes both nodal and tumour response. This would seem to be sensible especially in cases where 
there is total or almost total tumour response in the breast but little effect on nodal disease. Where 

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there is a mixture of categories, e.g. one node with a metastasis showing no response and one node 
showing fibrosis, the worst category should be used (e.g. category 4). 

Table 3: Recommended classification of response to chemotherapy 

Tumour response 

1.   Complete pathological response, either (i) no residual carcinoma or (ii) no residual invasive 

tumour but DCIS present. 

2.   Partial response to therapy, either (i) minimal residual disease/near total effect (e.g. < 10% 

of tumour remaining) or (ii) evidence of response to therapy but with 10–50% of tumour 

remaining or (iii) > 50% of tumour cellularity remains evident, when compared with the 

previous core biopsy sample, although some features of response to therapy present. Points 

(ii) and (iii) are somewhat subjective, especially when the core biopsy cannot be reviewed. 

3.   No evidence of response to therapy. 

Nodal response 

1.   No evidence of metastatic disease and no evidence of changes in the lymph nodes. 

2.   Metastatic tumour not detected but evidence of response/down-staging, e.g. fibrosis. 

3.   Metastatic disease present but also evidence of response, such as nodal fibrosis. 

4.   Metastatic disease present with no evidence of response to therapy. 

In  summary,  it  is  recommended  that  pathologists  report  the  following  factors  in  post-chemotherapy 
specimens: 

•  Presence or absence of invasive and/or in situ carcinoma 

•  Histological type of residual invasive tumour (as in the fourth edition) 

•  Residual tumour size and size of fibrotic nidus where possible 

•  Margin status 

•  Extent of nodal involvement (number of nodes, number of involved nodes and number of nodes 

with evidence of tumour regression) 

•  Percentage of fibrosis, necrosis and inflammatory response 

•  Presence or absence of multi-focality 

•  Presence or absence of chemotherapy effect on both invasive and in situ carcinoma 

•  Reporting of response to chemotherapy by an accepted system. The Working Group recommends 

the use of the system in Table 3 

• 

ypTNM. 

Features that should be reported on the original core biopsy: 

•  Type 

•  Grade 

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•  Presence of vascular invasion 

•  Presence of in situ disease 

•  ER, PR and HER2 status. 

Ki-67 may be requested and used to inform therapy by some oncologists. IHC may be repeated after 
neoadjuvant  treatment,  and  also  in  all  relapses  or  metastases,  because  some  changes  in  IHC 
expression may be found. 

A formula for the estimation of residual cancer burden has recently been published (Symmans et al., 
2007).  This  uses an algorithm that can be found online on the MD Anderson Cancer Center website 
(www.mdanderson.org/breastcancer_rcb). 

8 

Vacuum-assisted needle core biopsy 
(VANCB) 

For  certain  types  of  mammographic  abnormality,  particularly  microcalcification  with  a  moderate  or 
low-level suspicion of malignancy, a larger volume of tissue is required for accurate diagnosis (Meyer 
et  al.,  1997).  This  is  possible  with  VANCB.  The  biopsy  probe  incorporates  a  vacuum  channel,  which 
applies negative pressure to the biopsy port and thereby sucks the adjacent breast tissue into the port 
for  sampling.  The  biopsy  probe  is  introduced  into  the  breast  and  positioned  using  image  guidance. 
The vacuum is activated and sucks breast tissue into the biopsy port; a cutting cylinder then passes 
down  within  the  probe  and  separates  the  biopsy  material  from  the  surrounding  tissue.  The  biopsy 
specimen is then delivered by applying negative pressure and while the main probe remains within the 
breast.  Multiple  specimens  are  obtained  by  rotating  the  biopsy  probe  within  the  breast  so  that  the 
biopsy port is applied to different areas of breast tissue. 

The  potential  advantages  of  this  system  are  the  ability  to  obtain  a  larger  volume  of  tissue  for 
histological  examination  and  the  rapid  evacuation  of  any  haematoma  that  collects  at  the  site  of 
biopsy. This ensures that the specimens obtained are of good quality and are not compromised by the 
presence of haematoma (Liberman et al., 1998a). 

Under local anaesthetic, after a cutaneous incision of 5 mm, VANCB allows the radiologist to obtain 5–
25 cores with needles usually 8–11 gauge. In cases where the whole lesion or a high proportion of the 
lesion has been removed,  a small metal marker should be introduced through the biopsy probe and 
deployed at the biopsy site (Liberman et al., 1998b; Kettritz et al., 2004). 

In  cases  of  microcalcification,  the  cores  obtained  must  undergo  specimen  radiography  to  identify 
those  that  contain  representative  microcalcifications.  Afterwards,  they  should  be  put  into  a  separate 
container  with  a  fixative  and  labelled  “with  microcalcification”.  The  other  cores  should  be  put  into 
another  container  with  fixative  and  labelled  “without  microcalcification”.  The  cores  should  be 
embedded  in  separate  cassettes  (those  with  microcalcification  separate  from  those  without 
microcalcification),  the  number  of  cassettes  depending  on  the  number  of  samples.  In  each  cassette 
the cores should be put in parallel and embedded in the same way. If significant calcification is not 
identified in the initial levels, the paraffin blocks can be X-rayed and the microcalcification identified. 
More levels of the block or blocks containing calcifications should be made until the calcified lesion is 
identified.  The  pathologist  should  identify  the  microcalcification  biopsied  by  the  radiologist  in  the 
respective  slides  and  compare  the  microscopic  morphology  with  the  X-ray  pattern.  The 
multidisciplinary meeting is an ideal forum to correlate this. Specimen radiography using a dedicated 

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microfocus device with magnification at low kilovoltage (14–16 kV) improves the accuracy of specimen 
radiography. 

In the histological report, B categories should be used and it should be clearly stated whether or not 
microcalcification is present (Heywang-Kobrunner et al., 2003; Kettritz et al., 2005). 

As in US-guided core biopsies, cases where significant microcalcification is not identified in histological 
slides after several levels should be discussed by a multidisciplinary team (radiologist, pathologist and 
surgeon) (Heywang-Kobrunner et al., 2003; Kettritz et al., 2005; Tot, 2005; Tot & Gere, 2008). 

Consumables are expensive, and this technique is often reserved for non-palpable lesions, in particular 
for microcalcification. It is usually performed under stereotaxis, on digital dedicated tables, but it can 
also be US-guided (Liberman et al., 1998a). 

Published results on VANCB have demonstrated a lower equivocal sample rate and increased accuracy 
in  the  detection  of  small  invasive  tumours  associated  with  an  area  of  DCIS.  The  accuracy  of 
histological diagnosis is 3% higher with 10 gauge needles than with 14 gauge needles (Salem et al., 
2009).  Consideration  of  the  likely  underlying  histological  nature  of  the  lesion  from  the  imaging 
features  should  therefore  be  taken  into  account  when  deciding  on  the  sampling  method  to  be  used 
(Tot, 2005). 

8.1 

Multidisciplinary correlation 

A  simple  imaging  classification  should  be  used  to  indicate  the  radiologist's  degree  of  suspicion  (see 
Section 4.4.2  in  the  fourth  edition).  This  is  useful  for  multidisciplinary  management  and  audit 
purposes. The indication and the preferred method for non-operative biopsy can be decided according 
to the degree of suspicion and the nature of the lesion.   

To  optimise  treatment  planning,  non-operative  histological  diagnosis  should  be  the  goal,  replacing 
diagnostic open surgical biopsy. Management decisions for excision biopsy after needle biopsy (CNB or 
VANCB)  should  made  based  on  radiological-pathological  correlation,  the  presence  of  a  detectable 
residual lesion in imaging after NB and the character of the lesion. 

When dealing with radiological-pathological correlation in the multidisciplinary conference, B3 results 
other than atypical epithelial proliferations of ductal type are not always an indication for an excision 
biopsy.  Reliable  decisions  on  regular  follow-up  without  further  diagnostic  intervention  include:  (a) 
findings of lobular neoplasia (except the pleomorphic type or those with necrosis, categorised as B5a) 
or  (b)  flat  epithelial  atypia,  but  only  if  they  are  associated  with  a  benign  histological  lesion  that 
correlates  with  the  biopsy  target  (e.g.  fibroadenoma,  etc.),  (c)  papillary  lesions  without  atypical 
findings that were completely removed by the diagnostic intervention and (d) radial scars detected as 
an additional microscopic finding to a benign lesion  considered to be the biopsy target, provided  no 
additional  architectural  distortion  is  present.  The  implementation  of  vacuum-assisted  biopsy  devices 
generally used for the assessment of calcification increases the chance that small lesions are removed 
completely.  Consequently,  the  number  of  B3  lesions  for  which  no  further  surgical  procedure  is 
necessary  increases  and  therefore  the  positive  predictive  value  for  malignancy  on  surgical  excision 
improves. 

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1a  Stockholm statement on successful implementation 

of population-based cancer screening programmes 

1b  Determinants of successful implementation of 

population-based cancer screening programmes 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
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Stockholm statement on successful 
implementation of population-based 
cancer screening programmes 

Authors 
L. von Karsa 
A. Anttila 
M. Primic Žakelj 
C. de Wolf 
M. Bielska-Lasota 
S. Törnberg 
N. Segnan 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Authors 
L. von Karsa, IARC 
A. Anttila, Finland 
M. Primic Žakelj, Slovenia 
C. de Wolf, Switzerland 
M. Bielska-Lasota, Poland 
S. Törnberg, Sweden 
N. Segnan, Italy 

Declarations of interest 
Interests of C. de Wolf and N. Segnan are reported on pages V and VII respectively. 

Disclaimer 
The views expressed in this document are those of the authors and do not necessarily reflect the offi-
cial  position  of  the  European  Commission.  Neither  the  European  Commission  nor  any  other 
organization  or  any  individual  may  be  held  responsible  for  any  use  that  may  be  made  of  the 
information contained herein. 

Acknowledgements 
The present statement is based on the results of a workshop held by the European Science Advisory 
Network  for  Health  (EuSANH)  on  implementation  and  quality  assurance  of  cancer  screening  pro-
grammes in Stockholm on 7–9 February 2011. A more detailed report has been published elsewhere 
and is reproduced in the second part of this annex with permission of Elsevier. 

Members  of  the  workshop  expert  committee  were:  Ahti  Anttila,  Finland;  Magdalena  Bielska-Lasota, 
Poland; Thomas Davidson, Sweden; Johannes JM van Delden, The Netherlands; Lawrence von Karsa, 
International Agency for Research on Cancer; Elsebeth Lynge, Denmark; Sue Moss, United Kingdom; 
Maja Primic Žakelj, Slovenia; Leo van Rossum, The Netherlands; Nereo Segnan, Italy; Sven Törnberg, 
Sweden; Chris de Wolf, Switzerland. 

The  workshop  was  also  attended  by  the  following  observers:  Euzebiusz  Dziwinski,  European  Cancer 
Patient Coalition; Karl Freese, European Commission; Gunta Lazdane, World Health Organization; and 
by  the  following  EuSANH  representatives:  Susanne  V  Allander,  Sweden;  Dorine  Coenen,  The 
Netherlands; Louise Gunning, The Netherlands; Monica Hultcrantz, Sweden; Måns Rosén, Sweden. 

Comments were received from Jose Manuel Baena, Luc Bleyen, Mireille Broeders, Luis Bujanda, José 
Expósito, Roger Pla Farnós, Xandra Gravenstein, Rosella Hermans, Roland Holland, Harry de Koning, 
Chris Meijer, Nieves Ascunce Elizaga, Xavier Castells Oliveres, Julietta Patnick, Marina Pollán, Dolores 
Salas, Hélène Sancho-Garnier, and Jaroslav Volf. 

The  research  leading  to  these  results  has  received  funding  from  the  European  Union’s  Seventh 
Framework  Programme  [FP7/2007-2013]  under  agreement  number  229716  for  the  EuSANH  project 
Improving Science Advice for Health in Europe (EuSANH-ISA) (www.eusanh.eu). 

Preparation of this report has also been supported by the European Union Public Health Programme 
(Project  no.  2006322,  European  Cooperation  on  Development  and  Implementation  of  Cancer 
Screening and Prevention Guidelines [ECCG]). 

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Please cite this publication as follows 
von Karsa L, Anttila A, Primic  Žakelj M, de Wolf  C, Bielska-Lasota  M,  Törnberg  S,  Segnan N (2013). 
Stockholm  statement  on  successful 
implementation  of  population-based  cancer  screening 
programmes. Annex 1a. In: European guidelines for quality assurance in breast cancer screening and 
diagnosis. Fourth edition, Supplements. Perry N, Broeders M, de Wolf C, Törnberg S, Holland R, von 
Karsa  L  (eds.).  European  Commission,  Office  for  Official  Publications  of  the  European  Union, 
Luxembourg, pp. 123–128. 

Corresponding author 
L. von Karsa 
Quality Assurance Group 
Early Detection and Prevention Section 
International Agency for Research on Cancer 
150, cours Albert Thomas 
69372 Lyon Cedex 08 
France 
Karsal@iarc.fr 

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125 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
SSUUPPPPLLEEMMEENNTTSS  ––  AANNNNEEXX  11AA  

Stockholm statement on 

successful implementation of 

population-based 

cancer screening programmes 

A  multidisciplinary  group  of  scientists  and  professionals  experienced  in  implementation  and  quality 
assurance  of  cancer  screening  programmes  and  in  development  of  scientific  advice  on  health  policy 
met  at  a  pan-European  workshop  in  Stockholm  from  7  to  9  February  2011.  The  workshop  was 
organized by the European Science Advisory Network for Health (EuSANH, www.EuSANH.eu). The list 
of  experts  attending  the  workshop  is  provided  in  this  annex.  The  experts  reviewed  the  available 
evidence on implementation and quality assurance of cancer screening programmes with a focus on 
organization  and  reduction  of  barriers  to  participation.  After  comprehensive  discussion,  the  experts 
reached the following, mutually agreed conclusions: 1 

Any policy decision in Europe to implement a cancer screening programme should take into account 
European  Union  (EU)  recommendations  and  guidelines  based  on  the  available  evidence  and  the 
experience in Europe in implementing population-based cancer screening programmes. Key references 
in  this  regard  are  the  Council  Recommendation  of  2  December  2003  on  cancer  screening  of  the 
Council  of  the  European  Union  [1],  the  European  guidelines  for  quality  assurance  in  breast,  cervical 
and  colorectal  cancer  screening  [2–4]  and  recent  reports  dealing  with  the  implementation  of  cancer 
screening programmes in the EU [5–7]. These references recognize that societal values in addition to 
professional, technical and scientific standards are of prime importance in any decision to implement 
cancer screening programmes. Furthermore, there is no doubt that the population-based approach to 
programme implementation as recommended by the Council of the EU and the European guidelines is 
more  equitable,  more  effective  and  more  cost-effective  than  an  opportunistic  approach.  The  latter 
usually leads to overuse of health resources by a portion of the target population with lower cancer 
risk, and underuse by less advantaged groups with higher cancer risk. 

The experience in Europe shows that successful implementation of population-based cancer screening 
programmes  requires  long-term  political  commitment,  a  comprehensive  quality  management 
programme  and  sustainable  resources.  In  a  fully  established  programme,  the  proportion  of  the 
expenditure devoted to quality assurance should be no less than 10–20%, depending on the scale of 
the programme. In the initial years, this proportion may be substantially higher due to the low volume 
of  screening  examinations  compared  with  the  situation  after  complete  rollout  of  a  nationwide 
programme. This investment is cost-effective and will save lives. 

Once  the  political  decision  has  been  taken  to  establish  a  population-based  cancer  screening  pro-
gramme,  a  competent  programme  coordinator  should  receive  the  mandate  to  manage  the  entire 
process  of  programme  implementation,  beginning  with  a  planning  phase  and  followed  by  feasibility 
testing,  piloting  and,  depending  on  the  interim  results,  subsequent  gradual  rollout  of  a  programme 
fulfilling  the  principles  and  standards  recommended  in  the  Council  Recommendation  [1]  and  the 
European guidelines [2–4] and relevant national standards and guidelines. The coordinator should be 
provided  with  sufficient  organizational  and  financial  resources  to  effectively  manage  the  screening 
programme  and  take  further  decisions  as  necessary.  These  decisions  should  enable  the  coordinator 

1  The  present  statement  summarizes  key  results  of  the  workshop.  A  more  detailed  report  has  been  published 

elsewhere [8] and is reproduced with permission of Elsevier in the second part of this annex. 

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and  the  coordination  team  to  establish  the  screening  programme  in  the  respective  health  services 
context, taking into account the need for the professional and organizational management to control 
the  quality  of  the  entire  screening  process,  including  informing  and  inviting  the  target  population, 
performance of the screening test, diagnosis, therapy and subsequent care. The existing expertise in 
Europe in implementation  of population-based cancer screening programmes should be available for 
exchange  of  information  and  experience,  such  as  through  the  European  cancer  screening  networks 
and  the  European  guidelines  development  activities  coordinated  by  the  International  Agency  for 
Research on Cancer (IARC, www.iarc.fr), and related initiatives such as the European Partnership for 
Action Against Cancer (EPAAC, www.epaac.eu). 

Additional tools, including  computerized information systems and accessible registries, are necessary 
for the management of effective and efficient screening services (e.g. for call and re-call systems and 
fail-safe procedures in follow-up of participants with abnormal test results). They are also needed to 
monitor  and  evaluate  the  performance  and  the  outcome  of  the  screening  programme,  e.g.  through 
linkage  of  individual  data  on  cancer  occurrence  and  morbidity,  screening  history,  diagnosis  and 
treatment. 

Furthermore, key performance and quality indicators of the screening process must be recorded and 
monitored and the results must be analysed and used for quality management processes. Monitoring 
and evaluation reports must be published regularly to inform the public and decision makers and to 
permit timely modification of programme policy, if necessary. The experience of EuSANH in developing 
advice  for  health  policy  making,  taking  into  account  not  only  scientific  and  professional  but  also 
societal aspects, could play an important role in this regard in the future. 

References 

1.  Council of the European Union (2003). Council Recommendation of 2 December 2003 on cancer 

screening (2003/878/EC). Off. J. Eur. Union., L 327:34–38. 
http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2003:327:0034:0038:EN:PDF 

2.  Segnan  N,  Patnick  J,  von  Karsa  L  (eds.)  (2010).  European guidelines for quality assurance in 
colorectal cancer screening and diagnosis. First edition.  European  Commission,  Office  for  Official 
Publications of the European Union, Luxembourg. 
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/EUR/ViewPublication-Start?PublicationKey=ND3210390 

3.  Arbyn M, Anttila A, Jordan J, Schenck U, Ronco G, Segnan N, Wiener H, Herbert A, Daniel J, von 
Karsa  L  (eds.)  (2008).  European guidelines for quality assurance in cervical cancer screening. 
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4.  Perry  N,  Broeders  M,  de  Wolf  C,  Törnberg  S,  Holland  R,  von  Karsa  L,  Puthaar  E  (eds.)  (2006). 
European guidelines for quality assurance in breast cancer screening and diagnosis. Fourth 
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Luxembourg. 
http://bookshop.europa.eu/is-bin/INTERSHOP.enfinity/WFS/EU-Bookshop-Site/en_GB/-
/EUR/ViewPublication-Start?PublicationKey=ND7306954 

5.  Anttila  A,  Ronco  G,  Working  Group  on  the  Registration  and  Monitoring  of  Cervical  Cancer 
Screening Programmes in the European Union; within the European Network for Information on 
Cancer (EUNICE) (2009). Description of the national situation of cervical cancer screening in the 
member states of the European Union. Eur. J. Cancer, 45:2685–2708. 
 http://www.ejcancer.info/article/S0959-8049(09)00576-0/abstract 

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6.  von Karsa L, Anttila A, Ronco G, Ponti A, Malila N, Arbyn M, Segnan N, Castillo-Beltran M, Boniol 
M, Ferlay J, Hery C, Sauvaget C, Voti L, Autier P (2008). Cancer screening in the European Union, 
Report on the implementation of the Council Recommendation on cancer screening – First Report. 
European Commission, Office for Official Publications of the European Communities, Luxembourg. 
http://ec.europa.eu/health/ph_determinants/genetics/documents/cancer_screening.pdf 

7.  Commission  of  the  European  Communities  (2008).  Report  from  the  Commission  to  the  Council, 
the  European  Parliament,  the  European  Economic  and  Social  Committee  and  the  Committee  of 
the  Regions  –  Implementation  of  the  Council  Recommendation  of  2  December  2003  on  cancer 
screening (2003/878/EC) Brussels, Report no. COM(2008) 882 final. 
 http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2008:0882:FIN:EN:PDF 

8.  Lynge E, Törnberg S, von Karsa L, Segnan N, van Delden JJM (2012). Determinants of successful 

implementation of population-based cancer screening programmes. Eur. J. Cancer, 48:743–748. 
http://www.sciencedirect.com/science/article/pii/S0959804911004898 

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Determinants of successful 

implementation of population-based 
cancer screening programmes 

Authors 
E. Lynge 
S. Törnberg 
L. von Karsa 
N. Segnan 
J.J.M. van Delden 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
        
Authors 
E. Lynge, Denmark 
S. Törnberg, Sweden 
L. von Karsa, IARC 
N. Segnan, Italy 
J.J.M. van Delden, The Netherlands 

Declarations of interest 
Interests of E. Lynge and N. Segnan are reported on page VII. 

Disclaimer 
The views expressed in this document are those of the authors and do not necessarily reflect the offi-
cial  position  of  the  European  Commission.  Neither  the  European  Commission  nor  any  other 
organization  or  any  individual  may  be  held  responsible  for  any  use  that  may  be  made  of  the 
information contained herein. 

Elsebeth Lynge is undertaking a comparative study of new-generation HPV tests, involving collabora-
tion with Roche Diagnostics A/S, Genomica S.A.U., Qiagen Gaithersburg Ltd., and Gen-Probe Inc., and 
has  served  as  unpaid  adviser  for  Gen-Probe  and  Norchip.  Nereo  Segnan  participated  at  an  advisory 
board meeting for Colorectal Cancer Screening in January 2011, as a paid expert, on colorectal cancer 
blood screening assay, organized by Roche Diagnostics Ltd. 

Acknowledgements 
This  part  of  Annex  1  (Determinants of successful implementation of population-based cancer 
screening programmes) has been previously published in the European Journal of Cancer (volume 48, 
pp 743-748) and is reproduced here with permission of Elsevier. The content of the article is based on 
the  results  of  a  workshop  held  by  the  European  Science  Advisory  Network  for  Health  (EuSANH)  on 
implementation and quality assurance of cancer screening programmes in Stockholm on 7-9 February 
2011. A brief statement summarizing the results of the workshop and a detailed list of the participants 
and other contributors is published in the first part of this annex. 

The  research  leading  to  these  results  has  received  funding  from  the  European  Union’s  Seventh 
Framework  Programme  [FP7/2007-2013]  under  agreement  number  229716  for  the  EuSANH  project 
Improving Science Advice for Health in Europe (EuSANH-ISA) (www.eusanh.eu). 

Preparation  of  this  document  has  also  been  supported  by  the  European  Union  Public  Health 
Programme  (Project  no.  2006322,  European  Cooperation  on  Development  and  Implementation  of 
Cancer Screening and Prevention Guidelines [ECCG]). 

Please cite this publication as follows 
Lynge  E,  Törnberg  S,  von  Karsa  L,  Segnan  N,  van  Delden  JJM  (2012).  Determinants  of  successful 
implementation of population-based cancer screening programmes. Eur. J. Cancer, 48:743–748. 

Corresponding author 
E. Lynge 
Department of Public Health 
University of Copenhagen 
Øster Farimagsgade 5 
DK-1014 Copenhagen K 
Denmark 
Tel: + 45 35 32 76 35, Fax: + 45 35 32 73 83 
elsebeth@pubhealth.ku.dk 

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(cid:135)(cid:3) (cid:80)(cid:82)(cid:85)(cid:72)(cid:3)(cid:87)(cid:75)(cid:68)(cid:81)(cid:3)(cid:82)(cid:81)(cid:72)(cid:3)(cid:70)(cid:82)(cid:83)(cid:92)(cid:3)(cid:82)(cid:85)(cid:3)(cid:83)(cid:82)(cid:86)(cid:87)(cid:72)(cid:85)(cid:86)(cid:18)(cid:80)(cid:68)(cid:83)(cid:86)(cid:29)(cid:3)

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(cid:3)
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Priced publications: 

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Priced subscriptions: 

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(cid:3)

N
D
-
0
2
-
1
3
-
3
8
6
-
E
N
-
C