The UK Interstitial Lung Disease Long-COVID19 Study (UKILD-Long COVID): Understanding the Burden of Interstitial Lung Disease in Long COVID.
Conditions: Interstitial Lung Disease, SARS-CoV-2 Infection
Sponsor: Imperial College London

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Study protocol 
 
UKILD – Long COVID 
 
The UK Interstitial Lung Disease Long-COVID19 study (UKILD-Long COVID): understanding the burden of 
Interstitial Lung Disease in Long COVID. 
 
V1.3 11/11/2021 
MAIN SPONSOR: Imperial College London 
 
FUNDERS: Research Grant, UKRI Grant Ref: MR/W006111/1 
 
STUDY COORDINATION CENTRE: NHLI 
 
IRAS Project ID: 297891 
REC reference: 
 
Protocol authorised by: 
 
Name & Role 
Date 
Signature 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Study Management Group 
Chief Investigator: Professor Gisli Jenkins 
NIHR Research Professor and Margaret Turner Warwick Chair of Thoracic Medicine  
Head of Margaret Turner Warwick Centre for Fibrosing Lung Disease, 
National Heart and Lung Institute, 
Imperial College London, 

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Guy Scadding Building, 
Cale Street,  
London, SW3 6LY 
Email: gisli.jenkins@imperial.ac.uk 
Co-investigator organizations:  
• 
University of Nottingham  
• 
University of Edinburgh  
• 
University College London  
• 
University of Sheffield  
• 
University of Oxford  
• 
University of Manchester  
• 
University of Leicester  
• 
University of Liverpool  
• 
University of Southampton  
• 
Royal Brompton Healthcare Trust  
 
Study Management: Dr Mark Weeks (Imperial) 
 
Study Coordination Centre 
Imperial College London 
Respiratory Hub Manager  
Room G39 
Emmanuel 
Kaye 
Building, 
1B Manresa Road, London, SW3 6LR  
 
For general queries, supply of study documentation, and collection of data, please contact: 
 
Study Coordinator: Dr M Weeks 
Address: Imperial College London 
 
 
 
 
 
Registration: 
Respiratory Hub Manager  
Room G39 
Emmanuel 
Kaye 
Building, 
1B Manresa Road, London, SW3 6LR 
Tel: +44 (0)20 7594 7972  
 
 
 
 
E-mail:  m.weeks@imperial.ac.uk 
Fax:        
 
 
 
 
 
 
Web address:       
 
Clinical Queries 
Not Applicable as study will only use anonymized data In the event that any clinical queries arise, these 
can be addressed to  
 Chief Investigator: Professor Gisli Jenkins 
NIHR Research Professor and Margaret Turner Warwick Chair of Thoracic Medicine  
Head of Margaret Turner Warwick Centre for Fibrosing Lung Disease, 
National Heart and Lung Institute, 
Imperial College London, 
Guy Scadding Building, 
Cale Street,  
London, SW3 6LY 
Email: gisli.jenkins@imperial.ac.uk. 
  
 
Sponsor 

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Imperial College London is the main research Sponsor for this study.  For further information regarding 
the sponsorship conditions, please contact the Head of Regulatory Compliance at: 
 
 
 
Research Governance and Integrity team 
Imperial College London and Imperial College Healthcare NHS Trust 
Room 215, Level 2, Medical School Building 
Norfolk Place 
London, W2 1PG 
Tel: 0207 594 9459/ 0207 594 1862 
http://www3.imperial.ac.uk/clinicalresearchgovernanceoffice  
Funder 
This study is funded by a research grant award from UKRI MRC Ref MR/W006111/1. 
 
This protocol describes the UKILD – Long COVID study and provides information for participating partner 
organizations.  Every care was taken in its drafting, but corrections or amendments may be necessary. 
These will be circulated to investigators in the study.  Problems relating to this study should be referred, 
in the first instance, to the Chief Investigator.  
 
This study will adhere to the principles outlined in the UK Policy Frame Work for Health and Social Care 
Research. It will be conducted in compliance with the protocol, the Data Protection Act and other 
regulatory requirements as appropriate.  
Record of Version changes 
 
Date of version 
Version 
Number 
Change 
15/07/21 to  
12/08/21 
V1.1 
Modification to V1.0 to V1.1 in response to REC review. Clarify 
withdrawal criteria on p12 study protocol and addition of REC 
committee 
26/08/21 
V1.2 
Adaption of inclusion criteria to allow patients who are receiving up 
to 10mg of prednisolone a day to be recruited, we have found we 
are having to exclude a lot of patients otherwise. 
11/11/21 
V1.3 
Adaption of protocol to include recruitment of data-only 
participants 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Table of Contents 
Page 
1.0 
INTRODUCTION 
5 
1.1 
Background 
5 
1.2 
Study Rationale 
5 - 6 
2.0  
STUDY OBJECTIVES 
6 
2.1  
Primary objective   
6 
2.2  
Secondary objectives 
6 
2.3  
The primary endpoint 
6 
2.4 
The secondary endpoints 
6 - 7 
3.0  
STUDY DESIGN 
7 
3.1  
Table of study procedures objectives and outcomes 
7 - 8 
3.2 
Description of study procedure(s) 
8 - 9 
3.2.1 
Baseline and follow up assessments Tier 1 and Tier 2  
9 - 10  
3.3  
Monitoring of clinical events and re-analysis of previous scans (clinically indicated) 
10 
3.4 
Sample Handling Tier 2  
10 
4.0 
PARTICIPANT RECRUITMENT 
10 
4.1 
Pre-recruitment evaluations 
10 - 11 
4.2 
Inclusion Criteria Tier 1 and Tier 2 
11  
4.3 
Exclusion Criteria 
11 
4.4 
Withdrawal Criteria 
11 - 12 
5.0 
ASSESMENT AND FOLLOW UP 
12 
5.1 
Optional follow up and assessment 
12 
6.0 
ADVERSE EVENTS 
13 
6.1 
Definitions 
13 
6.2 
Reporting Procedures  
13 
6.3 
Non serious AEs 
13 
6.4 
Serious AEs 
13 - 14 
7.0 
STATISTICS AND DATA ANALYSIS 
14 - 15 
8.0 
REGULATORY ISSUES 
15 
8.1 
Ethics approval 
15 
8.2 
Consent 
15 
8.3 
Confidentiality 
15 
8.4 
Indemnity 
15 
8.5 
Sponsor 
15 
8.6 
Funding 
15 
8.7 
Audits 
16 
9.0 
STUDY MANAGEMENT 
16 
10.0 
PUBLICATION POLICY 
16 
11.0  
References 
16 - 17 
 
Appendix 1 Image management protocol for the UKILD-Post COVID study 
18 - 43 
 
 
 
 
 
 
 
 

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1 
INTRODUCTION  
 
1.1 
Background 
The COVID-19 Pandemic has led to over 100 million cases worldwide. In the UK alone, there have been 
over 4 million cases, over 400 thousand hospital admissions and over 100 thousand deaths. A large 
number of people diagnosed with COVID-19 suffer from long-term symptoms, predominantly 
breathlessness and fatigue whether or not they were admitted to hospital. However, long-term symptoms 
following COVID-19 are more common in people who suffered more severe acute disease [1-4]. There are 
a number of potential causes of long-term breathlessness following COVID-19 including thromboembolic 
disease, myo- or pericarditis, and physical deconditioning. However, based on early data from the COVID-
19 pandemic, and from other viral infections, a common and potentially severe long-term consequence 
of COVID-19 is the development of Post COVID related Interstitial Lung Disease (PC-ILD) [5-7]. 
 
SARS-CoV-2 leads to pronounced inflammation within the lung and leads to the development of Acute 
Respiratory Distress Syndrome (ARDS) in a substantial proportion of those infected. Whilst data 
demonstrate that a short course of corticosteroids can improve survival in patients with hypoxia there is 
considerable evidence of longer-term inflammation even following short-term corticosteroid therapy [8]. 
Whilst the inflammatory potential of SARS-CoV-2 is well described, the fibrogenic potential of SARS-CoV-
2 is currently unknown but is predicted to be substantial  based on the experience of previous coronavirus 
outbreaks and emerging data from this pandemic [3, 7, 9]. Initial observations have identified substantial 
levels of post-COVID related ILD (PC-ILD) with up to 24% patients having fibrotic changes, on their initial 
CT scan, which do not appear to regress at longer time points. Similarly, between 18 - 34% of patients had 
lung function impairment following COVID-19, consistent with restrictive disease [7]. Risk factors for 
severe COVID-19 include increasing age, male sex and comorbidities including hypertension and type 2 
diabetes mellitus [10, 11], which are also associated with progressive lung fibrosis [10-12].  
Pilot data from our consortium indicate that novel functional imaging methods utilising 129Xe and 1H MRI 
are sensitive to gas transfer limitation, microstructural airway changes and alveolar perfusion deficit in 
both acute and long COVID patients. These methods also have some ability to dissect both inflammatory 
and fibrotic pathophysiology and are highly sensitive to disease progression in established ILDs [13-17]. 
 
1.2 
Study Rationale 
Given the large number of patients infected with SARS-CoV-2, it is vital that the extent of PC-ILD is 
determined; its natural history defined particularly whether it is time-limited inflammation and reversible, 
or develops into persistent, or even progressive, fibrosis. Determining the natural history of PC-ILD, and 
risk factors as well as biomarkers related to outcome such as disease progression, will enable a precise 
approach to treatments such as immunomodulation or antifibrotic therapy [6], stratification into clinical 
trials, prognostication and appropriate service provision. This will facilitate assessment and prioritisation 
of both conventional and novel therapies used in the treatment of COVID-19 during the acute phase to 
mitigate the subsequent development of PC-ILD. By exploring the long-term implications of SARS-CoV-2 
infection across the full spectrum of COVID-19 disease ranging from non-hospitalised patients managed 
in the community with mild symptoms to those requiring mechanical ventilation, we will define the risk 
factors for PC-ILD including disease severity, host genetic factors and the effects of antiviral and 
immunomodulatory treatment administered during the acute phase of the illness. The UKILD Post COVID 
study is a prospective multicentre observational cohort study that will be managed through the Imperial 
College National Heart and Lung Institute and funded by the UKRI Medical Research Council and an NIHR 
professorship (RGJ). 

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The PHOSP COVID study (ISRCTN10980107) is a national consortium that provides a platform to study the 
long-term consequences of COVID19 hospitalisations [18]. An expected 10,000 individuals hospitalised by 
COVID-19 are to be included in baseline assessments after testing positive on PCR for SARS-C0V-2 and will  
be recruited through the PHOSP platform. The study described here will aim to recruit a further 2000 
individuals, with proven COVID-19,  who were not hospitalised but presented to Long-COVID clinics with 
persistent respiratory symptoms such as breathlessness or cough and are referred for cross-sectional 
imaging (computer tomography, CT) at baseline (3 months weeks after their first COVID-19 symptoms) 
[19]. A total of up to 12,000 people will be assessed for longitudinal follow up into the UKILD-Post COVID 
study. Following assessment of Post COVID patients at baseline (~3-6 months post infection as defined 
above), those with clinical and radiological features suggestive of ILD will be included into the UKILD-Post 
COVID study population. Where there are contraindications for CT and if clinically indicated, participants 
will be eligible for a research-guided 3D ultrashort echo time (UTE) proton MRI as a surrogate for 
CT.  Where individuals meet criteria for initial study inclusion (COVID-19 and clinical indication for CT 
scanning) but have no clinical, radiological or physiological features of ILD they will be invited to enroll as 
part of the control cohort for follow up.  
 
This protocol details the research partnership between Imperial (BREATHE Respiratory hub partner), and 
partner organizations.  
 
2 
STUDY OBJECTIVES  
 
2.1 Primary objective   
The primary objective of the study is to determine the prevalence of ILD at 12 months following SARS-
CoV-2 infection and whether clinical severity correlates with severity of ILD in survivors. 
 
2.2 Secondary objectives 
1. to further define the PC-ILD population, in particular, to describe the emerging phenotypes and 
risk factors of PC-ILD 
2. to determine the natural history of PC-ILD phenotypes longitudinally 
3. to explore pathomechanisms of PC-ILD for candidate prognostic and theranostic biomarkers. 
 
 
2.3 The primary endpoint  
 
1. The primary endpoint of the study is as radiologically confirmed diagnosis of fibrotic or non-
fibrotic ILD in the 12 months following COVID-19. Sub-studies will have a co-primary endpoint of 
change in the radiological extent of PC-ILD.  
 
2.4 The secondary endpoints 
1) progressive lung function impairment between 3 and 12 months, defined as  ≥10% relative decline 
in FVC, or ≥10% relative decline in DLco, or increasing radiological extent of PC-ILD using image 
analysis [20]. 
2) Resolution of ILD, as defined by ≥10% relative improvement in FVC, DLco, or reduction of 
radiological extent. 

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3) Persistence of ILD in those not meeting definition of progression or resolution 
4) Presence of interstitial lung abnormalities (ILA) on radiological images that do not meet definition 
of ILD. 
5) A comprehensive series of clinical, molecular, MRI and biochemical parameters will be assessed 
as biomarkers. 
 
3 
STUDY DESIGN 
Prospective observational study of hospitalised and non-hospitalised patients post- infection with 
SARS-CoV-2. The study aims to recruit 2000 individuals, with proven COVID-19,  who were not 
hospitalised but presented to Long-COVID clinics with persistent respiratory symptoms such as 
breathlessness or cough and are referred for cross-sectional imaging (computer tomography, CT) at 
baseline (3 months weeks after their first COVID-19 symptoms). The study will run for 18 months. 
 
3.1 Study procedures objectives and outcomes 
 
 
Objectives  
Outcome Measures  
Timepoint(s)  
Primary  
 
1) 
Examine 
and 
compare the prevalence 
of ILD in patients with 
varying 
severity 
of 
COVID-19. 
(Non-
hospitalised 
will 
be 
compared 
with 
hospitalised patients and 
COVID severity defined 
as varying levels of 
respiratory support)  
 
MDT diagnosis of ILD at 12 
months (+/- 3 months) after acute 
infection 
 
12 months (+/- 3 months) post 
SARS-CoV-2 
 
NB: Need 2 time points, 6 months 
apart, between 3 and 15 months 
post-acute SARS-CoV-2 
Secondary  
  
Determine 
progressive 
lung 
function 
impairment between 3 
and 12 months 
Lung function decline:                       
≥10% relative decline in FVC or 
DLco 
OR 
Imaging deterioration: 
increasing radiological extent of 
PC-ILD using image analysis or 
MDT discussion 
Need 2 time points, 6 months apart, 
between 3 and 15 months post-acute 
SARS-CoV-2  
 
Resolution of ILD 
Any of the following:          ≥10% 
relative improvement in FVC, 
DLco, or 
reduction of radiological extent.  
12 months (+/- 3 months) post 
SARS-CoV-2 
 
Need 2 time points, 6 months apart, 
between 3 and 15 months post-acute 
SARS-CoV-2 
 
Persistence of ILD in 
those 
not 
meeting 
definition of progression 
or resolution 
 
  
12 months (+/- 3 months) post 
SARS-CoV-2 
 
2 time points, 6 months apart, 
between 3 and 15 months post-acute 
SARS-CoV-2 
 
Persistence of ILAs  
  
12 months (+/- 3 months) post 
SARS-CoV-2 
 

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Need 2 time points, 6 months apart, 
between 3 and 15 months post-acute 
SARS-CoV-2   
 
In hospitalised patients 
only: 
Assess 
the 
relationship 
between 
initial severity of acute 
infection and ILD  
Markers of severity of acute 
infection (e.g. CRP)   
12 months (+/- 3 months) post 
SARS-CoV-2 
 
Need 2 time points, 6 months apart, 
between 3 and 15 months post-acute 
SARS-CoV-2   
 
In hospitalised patients 
only 
Assess the impact of 
specific medical therapy 
used in the acute setting 
and ILD  e.g. antivirals, 
immunomodulation 
Medical therapy used for acute 
infection  
12 months (+/- 3 months) post 
SARS-CoV-2 
 
Need 2 time points, 6 months apart, 
between 3 and 15 months post-acute 
SARS-CoV-2   
 
Evaluate breathlessness, 
fatigue and cognition  
Medical 
research 
council 
dyspnoea scale 
Dyspnoea 12 
FACIT-F  
Montreal 
Cognition 
Assessment (MOCA) 
3 month, 6 months (+/- 6 weeks) 
and 12 months (+/- 3 months) post 
SARS-CoV-2 infection  
 
Evaluate the quality of 
life of patients with 
COVID-19  
Short Form-36 (SF-36)  
EQ5D-5L 
 
 3 month, 6 months (+/- 6 weeks) 
and 12 months (+/- 3 months) post 
SARS-CoV-2 infection  
 
Assess 
impact 
of 
COVID19 on aerobic 
capacity and endurance.  
Incremental shuttle walk test or 
cardiopulmonary exercise test, 
if clinically indicated 
  3 month, 6 months (+/- 6 weeks) 
and 12 months (+/- 3 months) post 
SARS-CoV-2 infection  
 
Exploratory  
  
Exploratory circulating 
biomarkers 
will 
be 
correlated with ILA/ILD 
whole blood RNA sequencing 
(including 
peripheral 
blood 
mononuclear cells) and analysis of 
epigenetic 
modifications 
and 
proteomics 
  3 month, 6 months (+/- 6 weeks) 
and 12 months (+/- 3 months) post 
SARS-CoV-2 infection  
 
  
 
Compare serological and 
cellular 
measures 
of 
epithelial 
and 
endothelial injury and 
thrombosis 
Serum biomarkers of epithelial and 
endothelial injury, NETosis and 
thrombosis  
Cellular measurements in these 
same patients. 
Serum/ Plasma: Nordic biomarkers, 
LRG-1, MMP-7 etc; NETs  
  3 month, 6 months (+/- 6 weeks) 
and 12 months (+/- 3 months) post 
SARS-CoV-2 infection  
  
 
Compare genetic risk 
factors for lung fibrosis 
and 
radiological 
progression, 
continuously 
and 
dichotomised 
genome-wide 
array 
genotyping 
Genetic testing from blood/ saliva 
of putative candidate genes 
and use of GENOMIC data, and 
telomere length in a subset  
No sooner than 3 month visit 
 
Assess the relationship 
between 
routinely 
collected 
laboratory 
parameters markers  
Laboratory parameters (including 
CRP, FBC) and extent of ILD in 
patients  
  3 month, 6 months (+/- 6 weeks) 
and 12 months (+/- 3 months) post 
SARS-CoV-2 infection  
 
 
3.2 Description of study procedure(s) Tier 1 and Tier 2  
Initial patient approach  
Eligibility assessment by clinical team  
Study information and invitation letter provided to eligible patients for data only, Tier 1 participation. 

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 Description of study procedure(s) Tier 2 
 
History and Examination (10 mins) : Medical history, allergies, medications and anthropometric 
measurements including height, weight, and body mass index will be recorded during the study visit (or 
taken from the hospital notes. Or PHOPS data) 
Blood sample collection (10 mins) :  
Samples will be taken for plasma/ serum for epithelial and endothelial damage biomarkers, coagulation 
and  genetics  
Questionnaires (45 mins)  
Participants will be provided with seven questionnaires; 36 Short-Form Survey (SF-36), Clinical Frailty Scale 
(CFS), Patient Health Questionnaire 9 (PHQ9), Montreal Cognition Assessment (MOCA), Dyspnoea-12 
score, EQ5D-5L, FACIT-F at the end of each study visit.   
There are no investigations required for participants co-enrolled in the PHOSP-COVID study.  
 
3.2.1 Baseline and follow up assessments   
Initial patient approach  
Eligibility assessment by clinical team  
Study information and invitation letter provided to eligible patients 
   
Visit 1 (~3 months) (Post COVID-19 infection patients)   
1. Review of eligibility with participant  
2. Obtain written informed consent  
3. History and anthropometric measurements, e.g. height, weight, body mass index (BMI)  
4. Blood sample (6-10 ml) collection  
5. Pulmonary function test (20 minutes)  
6. Optional 6-minute walk test (6MWT) (10 minutes)  
7. Quality of Life questionnaire (SF-36) (10 minutes)  
8. Clinical Frailty Scale (CFS) (5 minutes)  
9. Personal health questionnaire (PHQ) (10 minutes)  
10. Montreal Cognitive Assessment MOCA (10 minutes)  
11. Dyspnea 12 score (10 minutes) 
12.  EQ5D-5L (10 minutes) 
13.  FACIT-F questionnaire (10 minutes) 
 
 
Optional Visit 2 (~6 months) (Post COVID-19 infection patients and matched controls)  
All visit 1 assessments will be repeated.   

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Visit 3 (~12 months) (Post COVID-19 infection patients)  
All visit 1 assessments will be repeated.    
Visits will be scheduled to take place over 1 day.   
Visit 2 is optional,  
Visits 1 and 3 are obligatory.  
 
3.3 Monitoring of clinical events and re-analysis of previous scans (clinically indicated)  
Clinical outcome data and images from clinical scans for all COVID-19 patients will also be collected from 
around the time of infection and hospitalisation and follow up. Laboratory analyses and chest imaging 
results undertaken for clinical reasons will also be collected. Access to participant medical records and 
any relevant hospital data that is recorded as part of routine standard of care; i.e., CT-Scans, blood results 
and disease progression data etc. will be obtained with patient consent from hospital electronic patient 
records and NHS digital    
 
3.4 Sample Handling Tier 2  
Blood samples for the analysis of serum inflammatory markers, serum biomarkers of endothelial and 
epithelial injury and coagulation studies, viral serology, viral PCR, and whole genome sequencing, 
ribonucleic acid sequencing and flow cytometry in blood will be collected. Analysis of venous blood 
samples will be performed in local NHS laboratories. If the Participant consents approximately 10 ml of 
blood will be stored in the Division of Cardiovascular Medicine for further analysis as part of collaborations 
with other groups. Samples will not be collected from participants who are also participating in PHOSP-
COVID  
 
4.0 PARTICIPANT RECRUITMENT 
 
4.1 
Pre-recruitment evaluations  
Screening and Eligibility Assessment  
Patients will be assessed by the clinical teams for eligibility against the inclusion or exclusion criteria for 
Tier 1 and/or Tier 2.   
 
The clinical teams at the recruiting sites will confirm that patients have been infected with SARS-CoV2 
before approaching them. Participants must satisfy all the approved inclusion and exclusion criteria of the 
protocol. If eligible for Tier 1, a ‘data only’ participation, once criteria is confirmed consent can be taken 
by phone. Participants will then be invited to join the study and informed consent will be obtained at the 
start of visit 1. For Tier 2, pre-screening for eligibility will take place prior to consent. It will be done by the 
direct care team using patient notes. There will be no access to patient identifiable data outside of the 
direct care team prior to consent.   
  
Screening and eligibility for PHOSP COVID/C-MORE participants   
For PHOSP-COVID participants, screening and eligibility assessment will occur as per the REC approved 
protocol (IRAS ID 285439).  

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All patients can be directed to other relevant post-COVID studies, including but not restricted to 
POSTCODE and XMAS. 
 
4.2 
Inclusion Criteria 
Tier 1 criteria ‘Data Only’ participation 
  
1) Age >18 years old -99 years old 
2) Evidence of SARS-CoV-2 infection confirmed by PCR or serology at any point during the 
duration of the pandemic 
3) Breathlessness and/or a clinical indication for a chest CT scan as per clinician judgment  
4)  Participants who have been identified and consented for tier 1 may not meet the inclusion 
criteria for tier 2 (below) but consent to researcher access to all clinical data relating to their 
health care during the pandemic and any subsequent follow up in relation to their COVID 
recovery. 
Tier 2 
1) Age >18 years old -99 years old 
2) Evidence of SARS-CoV-2 infection confirmed by PCR or serology 3 months (+/- 6 weeks) earlier 
3) Clinical indication for a chest CT scan as per clinician judgment  
4)  Participants who have been identified and consented for the main PHOS-PCOVID study are also 
eligible to join this study (if PHOSP-COVID is still open to recruit at that time). 
5) Allow inclusion of patient who are receiving up to 10mg of prednisolone a day 
4.3 
Exclusion Criteria 
 
1) Life-limiting illness within 12 months 
2) Significant pre-existing lung disease prior to March 2020, which in the investigator’s judgement 
could make the chest CT scans difficult to interpret 
 
4.4 
Withdrawal Criteria 
Early Discontinuation/Withdrawal of Participants : During the course of the study a participant may 
choose to withdraw early from the study treatment at any time. This may happen for several reasons, 
including but not limited to:  
 
• 
The occurrence of what the participant perceives as an intolerable AE.    
• 
Inability to comply with study procedures   
• 
Participant decision   
 
According to the design of the study, participants may have the following three options for withdrawal;   
1) Participants may withdraw from active follow-up and further communication but allow the study 
team to continue to access their medical records and any relevant hospital data that is recorded 
as part of routine standard of care; i.e., CT-Scans, blood results and disease progression data etc.  
2) Participants can withdraw from the study but data and samples obtained up until the point of 
withdrawal to be retained for use in the study analysis.  No further data or samples would be 
collected after withdrawal.   

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3) Participants can withdraw completely from the study and withdraw samples collected up until the 
point of withdrawal. The samples already collected would not be used in the final study analysis.   
4) In addition, the Investigator may discontinue a participant from the study at any time if the 
Investigator considers it necessary for any reason including, but not limited to:  
• 
Ineligibility (either arising during the study or retrospectively having been overlooked at 
screening)  
 
Participants that choose to withdraw from the study will not be replaced. The type of withdrawal and 
reason for withdrawal will be recorded in the CRF. If the participant is withdrawn due to an adverse event, 
the Investigator will arrange for follow-up visits or telephone calls until the adverse event has resolved or 
stabilised.  
 
5.0 ASSESMENT AND FOLLOW UP 
5.1 Optional follow up and assessment  
 
As previously detailed in section 3.3 above, Tier 2 participants may also agree to a final follow up 
assessment and an optional interim assessment 
 
Optional Visit 2 (~6 months) (Post COVID-19 infection patients and matched controls)  
All visit 1 assessments will be repeated.  All visit 1 assessments will be 
repeated.   
Visits will be scheduled to take place over 1 day.  Visit 2 is optional, visits 1 and 3 are obligatory. For 
research specific visits, participants will be offered reimbursement for travel expenses. This includes 
reimbursement for petrol, car parking, taxis.  
 
Clinical outcome data and images from clinical scans for all COVID-19 patients will also be collected from 
around the time of infection and hospitalisation and follow up. Laboratory analyses and chest imaging 
results undertaken for clinical reasons will also be collected. Access to participant medical records and 
any relevant hospital data that is recorded as part of routine standard of care; i.e., CT-Scans, blood results 
and disease progression data etc. will be obtained with patient consent from hospital electronic patient 
records and NHS digital. The end of the study will be the point at which the final patient follow-up and 
assessment have been completed.  
 
A detailed Image Management protocol for the UKILD-Post COVID Study provides a comprehensive 
outline of the purpose, operation, methods, policies, and governance of Image collection for UKILD. It 
describes the procedures used to collect and store images. (appendix 1) 
   
6.0 ADVERSE EVENTS  
 
6.1 DEFINITIONS  
Adverse Event (AE): any untoward medical occurrence in a patient or clinical study subject.   
 
Serious Adverse Event (SAE): any untoward and unexpected medical occurrence or effect that: 

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• 
Results in death 
• 
Is life-threatening – refers to an event in which the subject was at risk of death at the time 
of the event; it does not refer to an event which hypothetically might have caused death if 
it were more severe 
 
• 
Requires hospitalisation, or prolongation of existing inpatients’ hospitalisation 
• 
Results in persistent or significant disability or incapacity 
• 
Is a congenital anomaly or birth defect 
 
Medical judgement should be exercised in deciding whether an AE is serious in other situations.  Important 
AEs that are not immediately life-threatening or do not result in death or hospitalisation but may 
jeopardise the subject or may require intervention to prevent one of the other outcomes listed in the 
definition above, should also be considered serious. 
 
6.2 REPORTING PROCEDURES  
All adverse events should be reported.  Depending on the nature of the event the reporting procedures 
below should be followed.  Any questions concerning adverse event reporting should be directed to the 
Chief Investigator in the first instance.   
 
 
6.3 Non serious AEs 
All such events, whether expected or not, should be recorded 
 
6.4 Serious AEs 
An SAE form should be completed and emailed to the Chief Investigator within 24 hours.  However, 
relapse and death due to COVID -19, and hospitalisations for elective treatment of a pre-existing condition 
do not need reporting as SAEs. 
 
All SAEs should be reported to the London Riverside REC where in the opinion of the Chief Investigator, 
the event was: 
 
• 
‘related’, ie resulted from the administration of any of the research procedures; and 
• 
‘unexpected’, ie an event that is not listed in the protocol as an expected occurrence 
 
Reports of related and unexpected SAEs should be submitted within 15 days of the Chief Investigator 
becoming aware of the event, using the NRES SAE form for non-IMP studies.  The Chief Investigator must 
also notify the Sponsor of all related and unexpected SAEs. 
 
Local investigators should report any SAEs as required by their Local Research Ethics Committee, Sponsor 
and/or Research & Development Office. 
 
 
 
 
 
 
 
 
 
 
 

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Contact details for reporting SAEs 
RGIT@imperial.ac.uk 
CI email (and contact details below) 
Fax: N/A, attention Professor Gisli Jenkins 
Please send SAE forms to: gisli.jenkins@imperial.ac.uk 
Tel: : +44 (0)20 7594 7972  (Mon to Fri 09.00 – 17.00) 
 
7.0 STATISTICS AND DATA ANALYSIS 
 
The prevalence of MDT-confirmed PC-ILD at both early (up to 6 months) and again at late (10-15 month) 
time-points and will be assessed within the total study population. The prevalence of broader radiological 
abnormalities and phenotypic patterns will also be assessed in a descriptive analysis, together with 
demographics, haematological and biochemical profiles, physiological performance, and patient-reported 
outcome measures. Analyses will be performed overall and stratified according to hospitalised and non-
hospitalised, as well as severity of infection in hospitalised patients defined above. 
 
Baseline and longitudinal changes in biomarkers reflecting PC-ILD evolution, including circulating factors 
and cell-types from detailed serological and cellular analysis, will be assessed in multilevel models for 
repeated measures to test associations according to the presence or absence of PC-ILD at late time points 
(10-15 months), and according to progression, resolution, or persistence of radiological patterns over 
follow up time points. 
 
Analyses will be performed using standard epidemiological and statistical genetics methodology. This will 
include cross-sectional and longitudinal studies, and analyses of disease prevalence and incidence.  
Analysis design and choice of controls will be dependent upon the precise nature of the research question. 
Identification of risk factors for a specific COVID-19 sequela would involve controls both from within 
UKILD-Long COVID (without the sequela) and serology-positive controls with prospective questionnaire 
and healthcare record linkage from Longitudinal Population Studies (for example, UK Biobank, 
Coronagenes, EXCEED) and pre-existing disease cohorts. Analyses aiming to characterise and understand 
the clinical features, subtypes and trajectories of sequelae (for example, sarcopaenia) would evaluate the 
cross-sectional and longitudinal clinical data and biomarkers of UKILD-Long COVID participants who are 
presenting with the sequelae being studied. 
The participant organisations making up the UKILD-long COVID study group have extensive experience of 
development of, and collaborative use of, disease-specific and general population cohort studies both 
nationally and internationally enabling access to control populations and alignment of research strategies 
for rapid validation and replication of findings.  
 
Statistical significance thresholds will be defined in advance of each analysis and will take into account 
issues of multiple testing and a priori evidence. 
 
Data and all appropriate documentation will be stored for a minimum of 10 years after the completion 
of the study, including the follow-up period.  
 
 
 

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Project statistician: Dr Iain Stewart  email:   
 
                                                               iain.stewart@imperial.ac.uk 
                                                               National Heart and Lung Institute 
                                                               Guy Scadding Building, Cale Street,   
                                                               London, SW3 6LY 
 
8.0 REGULATORY ISSUES 
8.1 
Ethics approval 
The Study Coordination Centre has obtained approval from the Riverside Research Ethics Committee (REC) 
and Health Regulator Authority (HRA). The study must also receive confirmation of capacity and capability 
from each participating NHS Trust before accepting participants into the study or any research activity is 
carried out. The study will be conducted in accordance with the recommendations for physicians involved 
in research on human subjects adopted by the 18th World Medical Assembly, Helsinki 1964 and later 
revisions. 
 
8.2 
Consent  
Consent to enter the study must be sought from each participant only after a full explanation has been 
given, an information leaflet offered and time allowed for consideration.  Signed participant consent 
should be obtained.  The right of the participant to refuse to participate without giving reasons must be 
respected.  After the participant has entered the study the clinician remains free to give alternative 
treatment to that specified in the protocol at any stage if he/she feels it is in the participant’s best interest, 
but the reasons for doing so should be recorded.  In these cases the participants remain within the study 
for the purposes of follow-up and data analysis.  All participants are free to withdraw at any time from 
the protocol treatment without giving reasons and without prejudicing further treatment. Participants 
who opt for Tier 1 can be consented by phone and provide a signed consent form by post/email. 
 
8.3 
Confidentiality 
The Chief Investigator will preserve the confidentiality of participants taking part in the study and is 
registered under the Data Protection Act. Data and all appropriate documentation will be stored for a 
minimum of 10 years after the completion of the study, including the follow-up period which falls within 
the defined end date .   
 
8.4 
Indemnity 
Imperial College London holds negligent harm insurance policies which apply to this study. 
 
8.5 
Sponsor 
Imperial College London will act as the main sponsor for this study. Delegated responsibilities will be 
assigned to the NHS trusts taking part in this study. 
 
8.6 
Funding 
This study is funded by a research grant award from UKRI MRC Ref MR/W006111/1. Individual researchers 
will not receive any personal payments or any other benefits for taking part in this research. 
 

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8.7 
Audits  
The study may be subject to inspection and audit by Imperial College London under their remit as sponsor 
and other regulatory bodies to ensure adherence to GCP and the UK Policy Frame Work for Health and 
Social Care Research.  
 
9.0 STUDY MANAGEMENT  
 
Professor Gisli Jenkins, Chief Investigator and has overall responsibility for the management of the study, 
the day-to-day management of the study will be co-ordinated through Imperial College National Heart 
and Lung Institute.   
 
 
10.0 PUBLICATION POLICY 
Final results of the study will be disseminated in the form of a manuscript/s in a peer-reviewed journal 
scientific journals, presented at national and international conferences and in local meetings. In addition, 
where relevant, data from potential interim analyses will be presented at (a) relevant congress (es). In 
addition, the study database will be made available for future research. 
 
 
11.0 REFERENCES 
 
1. 
Carfi, A., et al., Persistent Symptoms in Patients After Acute COVID-19. JAMA, 2020. 324(6): p. 603-
605. 
2. 
Huang, C., et al., 6-month consequences of COVID-19 in patients discharged from hospital: a cohort 
study. Lancet, 2021. 397(10270): p. 220-232. 
3. 
Myall, K.J., et al., Persistent Post-COVID-19 Inflammatory Interstitial Lung Disease: An 
Observational Study of Corticosteroid Treatment. Ann Am Thorac Soc, 2021. 
4. 
Evans, R.A., et al., Physical, cognitive and mental health impacts of COVID-19 following 
hospitalisation: a multi-centre prospective cohort study. medRxiv, 2021: p. 2021.03.22.21254057. 
5. 
George, P.M., et al., Respiratory follow-up of patients with COVID-19 pneumonia. Thorax, 2020. 
75(11): p. 1009-1016. 
6. 
George, P.M., A.U. Wells, and R.G. Jenkins, Pulmonary fibrosis and COVID-19: the potential role 
for antifibrotic therapy. Lancet Respir Med, 2020. 8(8): p. 807-815. 
7. 
Laura Fabbri, S.M., Fasihul Khan, Wenjie Chi, Jun Xia, Karen Robinson, Alan Smyth, Gisli Jenkins, 
Iain Stewart, Post-viral parenchymal lung disease of COVID-19 and viral pneumonitis: A systematic 
review and meta-analysis. medRxiv, 2021(PrePrint): p. 24. 
8. 
Singh, A.K., et al., Role of corticosteroid in the management of COVID-19: A systemic review and a 
Clinician's perspective. Diabetes Metab Syndr, 2020. 14(5): p. 971-978. 
9. 
Rendeiro, A.F., et al., The spatial landscape of lung pathology during COVID-19 progression. 
Nature, 2021. 
10. 
Hu, J. and Y. Wang, The Clinical Characteristics and Risk Factors of Severe COVID-19. Gerontology, 
2021: p. 1-12. 
11. 
Jordan, R.E., P. Adab, and K.K. Cheng, Covid-19: risk factors for severe disease and death. BMJ, 
2020. 368: p. m1198. 
12. 
Shah, A.S., et al., A prospective study of 12-week respiratory outcomes in COVID-19-related 
hospitalisations. Thorax, 2020. 

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13. 
Chan, H.F., et al., 3D diffusion-weighted (129) Xe MRI for whole lung morphometry. Magn Reson 
Med, 2018. 79(6): p. 2986-2995. 
14. 
Chan, H.F., et al., Airway Microstructure in Idiopathic Pulmonary Fibrosis: Assessment at 
Hyperpolarized (3)He Diffusion-weighted MRI. Radiology, 2019. 291(1): p. 223-229. 
15. 
Saunders, L.C., et al., Free breathing lung T1 mapping using image registration in patients with 
idiopathic pulmonary fibrosis. Magn Reson Med, 2020. 84(6): p. 3088-3102. 
16. 
Weatherley, N.D., et al., Quantification of pulmonary perfusion in idiopathic pulmonary fibrosis 
with first pass dynamic contrast-enhanced perfusion MRI. Thorax, 2020. 
17. 
Weatherley, N.D., et al., Hyperpolarised xenon magnetic resonance spectroscopy for the 
longitudinal assessment of changes in gas diffusion in IPF. Thorax, 2019. 74(5): p. 500-502. 
18. 
Dowling, R. New national study into the long-term health impacts of COVID-19 launched. [On-line] 
2020 05/06/2020; on line press release]. Available from: https://www.phosp.org/study-
news/phosp-covid-launching-press-release/. 
 
 
19. 
Greenhalgh, T., et al., Management of post-acute covid-19 in primary care. BMJ, 2020. 370: p. 
m3026. 
20. 
Jacob, J., et al., Predicting Outcomes in Idiopathic Pulmonary Fibrosis Using Automated Computed 
Tomographic Analysis. Am J Respir Crit Care Med, 2018. 198(6): p. 767-776. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Appendix 1: Image management Protocol for the UKILD-Post COVID study 
 
 
 
 
Image Management protocol for the 
UKILD-Post COVID Study  
 
 
 
 
 
VERSION 1.0 
28th June 2021 
 
 
 
 
 
 
 
 

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Record of Version changes 
 
Date of version 
Version 
Number 
Change 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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20 
 
 
CONTENTS 
1) Introduction 
21 
2) Image collection and storage procedures 
22 
Pseudonyms 
22 
Image Collection from Healthcare Institutes 
23 
2.2.3 Image Collection 
27 
2.2.4 Data Types 
28 
2.2.5 Data Flow 
28 
2.3 Transfer of De-Identified Images to NCIMI 
29 
2.4 Access to Patient Identifiable Information 
29 
2.5 Linking to External Datasets 
29 
2.5.1 Linking via encoded pseudonyms 
29 
2.5.2 Linking via encrypted NHS numbers 
29 
3) Appendix 1: Anonymisation details 
31 
Pseudonymisation of DICOM tags 
31 
Nulling of DICOM tags 
31 
4) Appendix 2: Guidelines for Linking to External Datasets 
36 
Pseudonyms 
36 
Creating a Link-able Dataset NHS Hashing Tool 
37 
 
 
 
 
 
 

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Introduction 
 
This document is intended to provide a comprehensive outline of the purpose, operation, methods, 
policies, and governance of Image collection for UKILD. It describes the procedures used to collect and 
store images.  
The main data collection involved in this protocol is the collection of CT’s from a number of healthcare 
institutes throughout the UK. The Scientific Computing team from the Royal Surrey NHS Foundation Trust 
(RSNFT) have developed and implemented processes to collect and store digital mammographic images, 
as part of the CR-UK funded “OPTIMAM” project (IRAS ID: 145706) and the Breast Cancer Now funded 
“MeDICI” project (IRAS ID: 260722), which have created a large repository of mammographic image for 
research and training purposes. In addition, the team have been involved with collecting Chest X-rays and 
CTs for the National Covid-19 Chest Imaging Database and for the PHOSP-Covid study. These projects 
involve various image and data collection processes which, given appropriate permissions, enables data 
managers to remotely centralise relevant images and data, remove identifiers, and produce 
pseudonymised data for use by study researchers. These automated image and data collection 
procedures, which are now well established, have recently been altered for image collection within the 
National Covid-19 Chest Imaging Database (NCCID) in a manner to ensure that there is as little as possible 
disruption to clinical care at the sites participating. These techniques have been redeployed for use in 
UKILD. 
The focus of this document is on how the images are being collected. Particular attention is given to how 
the data is de-identified at the point of collection by automated processes. The images collected for UKILD 
are effectively anonymised to researchers and they have no access to the original data or patient 
identifiers. The NHS/CHI number is encrypted using an AES encryption algorithm and a complex salt to 
allow checks with the NHS Opt-out service. This encrypted NHS number is stored at the Royal Surrey NHS 
Foundation Trust and access is maintained by named data managers only. The final location for the de-
identified images is infrastructure maintained by the NCIMI team at the university of Oxford. 
The collection processes, transfer and encrypted NHS/CHI numbers are managed and maintained by 
data managers in the Medical Physics Department at the Royal Surrey NHS Foundation Trust. The data 
managers are trained in information governance policies of the host Trust.  
 

 
 
 
 
 
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Image collection and storage procedures 
The first principle of the image collection system is that all data that is transferred from the clinical 
sites to the central image database is fully de-identified and that at no point do researchers have 
access to patient identifiable information. The NHS/CHI number is encrypted using an AES encryption 
algorithm and a complex salt to allow checks with the NHS Opt-out service (See Pseudonyms). This 
encrypted NHS number is stored at the Royal Surrey NHS Foundation Trust and access is maintained 
by named data managers only. The final location for the de-identified image and data is a is 
infrastructure maintained by the NCIMI team at the university of Oxford.  
 
Pseudonyms 
To prevent the need to store Patient Identifiable Data (PID), UKILD utilises a trial ID in the place of 
Patient IDs. In order to obtain the Trial ID a web portal will be utilised to allow sites to submit trial IDs 
linked to pseudonym hashes (See SMART Portal Trial ID Registration section). Secondary pseudonyms 
are created through a one-way encryption process known as ‘hashing’ which provides the ability to 
link the images with the Trial ID and link with other datasets that have generated these pseudonyms 
in the same manner using the same complex salt. The process is described below: 
 
1. The input string (e.g., NHS/CHI number) is combined with a fixed complex salt, and then fed 
into a hashing algorithm (See Figure 1). 
2. The hashing algorithm used is SHA-256 (256-bit Secure Hashing Algorithm), which was 
developed by the National Security Agency (NSA). 
3. The hashed patient IDs are stored within the database and are linked to the registered patient 
and any images received for that patient. 
 
Figure 1: Illustration of hashing algorithm with fixed salt to generate pseudonyms 
 
4. The fixed complex salt is stored on the database server and is applied to all NHS and hospital 
IDs. 

 
 
 
 
 
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5. It is important to understand that the hashing process is one-way only - it is not possible to 
reconstruct the original NHS or hospital ID from the hashed string, even if the salt is known. 
6. However, we can compare the hashed string to another hashed string which has gone through 
the same process described in the diagram and thus be able to match up patient identifiers 
without ever exposing their original data. 
 
The pseudonyms are generated during the image collection process which generates hashed 
identifiers from the DICOM tags. This process is undertaken before the images are received from IEP 
and on the client-side of the SMART portal web form. 
Image Collection from Healthcare Institutes  
The following section describes the image collection processes that are deployed at numerous 
healthcare institutes around the UK. Each site is provided with training and guidance documentation 
to inform the users on the collection processes. Sites are asked for the participating client’s identifiers 
to be registered on the SMART Portal and imaging to be sent to a dedicated Research Node on the 
Image Exchange Portal. The images and data are de-identified at the point of collection and 
transferred to NCIMI. 
Figure 2 provides a graphical overview of the image collection and storage procedures used 

 
 
 
 
 
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Figure 2: Overview of the image and data collection, transfer and storage processes. 
Communications are through HTTPS and data at rest is encrypted with DEKs using AES256. There are 
two tables in the database which store the data - the other tables are for support only. 
a) Clients - This table contains the required information about an individual client 
(patient).  The primary and secondary hashed IDs are stored in this table.  There is also 
an optional field for storing an AES encrypted primary ID (NHS number). 
b) Images - This table is populated each time a new image is received by the image 
receiver software.  Each image is written into a new row in the table, and it is linked 
to the Client, so that we can link images to clients. 
The full schema for the collector is shown below. 
 

 
 
 
 
 
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Figure 3: Database schema for the data receiver 
 
SMART Portal Trial ID Registration 
UKILD Study sites will register the participants on the SMART Portal in advance of sending the 
images. This step is required to ensure that the Image collection system is informed of the Trial ID of 
the participant before the image is received, allowing the image to be collecting identified as 
belonging to UKILD and providing the pseudonym to insert into the DICOM image. The Trial ID 
uploaded and the incoming image will be linked through the use of a common temporary 
pseudonym in the form of a hashed NHS number (see Pseudonyms Section).  
Patient identifiers are de-identified at the point of upload. This means that no patient identifiable 
information will leave the site. Upon upload, a pseudonym will be assigned to the patient. This will 
be created by a lossful encoding algorithm and complex salt which will produce an encoded 

 
 
 
 
 
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pseudonym that allows the linking of the patient’s trial ID with the images. In addition, the NHS/CHI 
number will also be encrypted using an AES encryption algorithm and a complex salt to allow linking 
with national datasets.  
 
When a client is registered on the SMART portal the central collection server is queried for an 
encoding salt, which is transmitted to the local computer.  This encoding salt is unique to the trial, 
and is used to hash the NHS number, as well as the secondary patient identifier (e.g., hospital 
number) before it is transmitted over the Internet to the central server.  The hashing technology 
used is SHA-256 and this hash cannot be reversed back to the original data.  No NHS or patient 
identifier is ever transmitted to the central server using the SMART portal. 
Each site is issued with a user account for the SMART Portal with an initial password from the Royal 
Surrey Scientific Computing team.  Sites will register a client by entering an NHS/CHI number, a 
secondary ID, which must be the ID used by radiology (unless radiology uses NHS/CHI), as well as the 
trial code which uniquely identifies the client (See Figure 4). 
 
Figure 4: Register Client page on SMART Portal 

 
 
 
 
 
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Image Collection 
UKILD collects images using the Image Exchange Portal (IEP). This is advantageous as the processes for 
transferring images via IEP are well known and robust. IEP is in use by almost all NHS sites and private 
hospitals in the UK and is in routine use to facilitate the transfer of medical images from one healthcare 
site to another. At most clinical sites, a large number of staff are trained in the use of IEP and indeed 
most sites have a robust image transfer request service in place (usually run by the PACS team). UKILD 
has a dedicated node on IEP available for use for receiving images that are to be de-identified. This 
node is provided by the RSNFT. The node has been set up such that the images are de-identified as 
they transition from IEP, meaning that no patient identifiable information is received outside the IEP 
network. A pseudonym is generated using the same technique as described in the section above 
(Pseudonyms). This results in a common pseudonym between the images and the linking with the 
UKILD Smart portal entry.  
Collection sites are requested to submit images through IEP when a new patient is enrolled into UKILD. 
Many sites have internal processes for requesting image transfers via IEP (often through the PACS 
office). Guidance is provided to utilise these processes where possible. Guidance is also provided 
showing a step-by-step guide on how to submit images through IEP. 
Once an image has been sent to the UKILD dedicated node, a transfer is initiated to the RSNFT node 
receiver. The node receiver is a DICOM router (DICOM XR) designed to receive images and route them 
to different study modules based on sets of rules. As part of the DICOM XR process the received 
DICOM image is written to a virtual "RAMDISK" to act as the temporary location.  The purpose of the 
RAMDISK is to provide a non-permanent file-storage location for the temporary storage of images, 
thus avoiding the need of ever writing patient identifiable information to permanent storage (e.g., 
hard disc).  Before progressing further, the incoming images are filtered using the following criteria: 
The incoming images are filtered (discarded) by a number of rules: 
1. The accepted ClassSOPUID is limited to a small set listed. This filter effectively removes any 
Secondary Capture Objects, Dose reports and anything that is not a primary image: 
[class_uid:00080016 :STRING: MATCH_ANY ]{'1.2.840.10008.5.1.4.1.1.1', 
'1.2.840.10008.5.1.4.1.1.1.1', '1.2.840.10008.5.1.4.1.1.1.1.1', '1.2.840.10008.5.1.4.1.1.2', 
'1.2.840.10008.5.1.4.1.1.2.1', '1.2.840.10008.5.1.4.1.1.4', '1.2.840.10008.5.1.4.1.1.4.1', 
'1.2.840.10008.5.1.4.1.1.4.2'} 
2. The accepted modality is limited to the following Modality tag 
[modality:00080060:STRING:MATCH_ANY]{'DX', 'CR', 'MR', 'CT'}. 
3. Any CT series that have ImageType (.*)DERIVED(.*) are removed 
4. As a final filter, the images are passed through a further filter provided by the MIRC-CTP tool 
set. This is a curated list of DICOM tags and modality/model specific rules that could 

 
 
 
 
 
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potentially indicate the presence of PID. This tool highlights (provides a log) any such cases 
found and either removes the images or blackouts known PID potential areas. Chest X-ray 
DERIVED data have to be added to the whitelist. Logs are reviewed on a daily basis to follow 
up on any cases indicated. 
Once filtered, the accepted images are de-identified. The de-identification of the image takes place in 
RAMDISK, including the replacement of the PatientID tag with the pseudonym (described above). 
Details of the DICOM tags that are anonymised and those that are pseudonymised are given in 
Appendix 1. The acceptability of our pseudonymisation procedures was extensively reviewed by staff 
at the clinical sites during the original OPTIMAM project (2008--2013) and subsequent OPTIMAM 
projects (2013-2020), MeDICI (Current), FastMRI (Current) and the NCCID project (Current). We took 
advice from our Information Governance Officer on the acceptability of our procedures. All de-
identification is in compliance with DICOM Supplement 142. 
 
2.2.4 Data Types 
UKILD collects CT images and DICOM header information (de-identified). We will be collecting all 
follow up images for patients enrolled in UKILD. The categories of image data collected are: 
● Chest X-ray imaging at one or multiple timepoints 
● CT imaging of the chest including High-resolution imaging, contrast and non-contrast 
enhanced imaging, CT pulmonary angiograms, inspiratory and expiratory phase imaging and 
prone CT imaging. The CT imaging will be at one or more timepoints in each patient. 
● The imaging will be acquired from hospitalised and non-hospitalised COVID-19 patients 
 
2.2.5 Data Flow 
Images transferred via IEP to the UKILD node (hosted at the RSNFT). RSNFT is providing the image 
collection services for UKILD. The RSNFT stores the incoming images on a fully redundant RAID 5+1 
Synology (http://www.synology.com/) NAS server, with 54 TB capacity. This storage is considered 
temporary storage as the data is only transitioned through the RSNFT to its final destination. While 
the images reside on the RSNFT storage, for added insurance in the case of hardware failure, the 
system is replicated each evening to a mirror located in a separate building within the Trust. Both the 
storage and backup systems are also replicated to redundant systems to ensure continuous 
availability. Regular database dumps of all databases are made every two hours and archived on the 
backup systems. Data is transferred from the RSNFT to NCIMI on a regular basis. Once confirmation is 
received that the data transfer is successful, the images and data are removed from the RSNFT 
temporary storage and backups.  

 
 
 
 
 
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2.3 Transfer of De-Identified Images to NCIMI 
On a regular basis, dictated by the frequency of the data uploads, a job running on a virtual 
environment at RSNFT will transfer images to a shared transient cloud storage. NCIMI will download 
and remove. All images will be encrypted in flight during the transfer using Secure HTTP (HTTPS) 
protocol. 
 
2.4 Access to Patient Identifiable Information 
Images and data are de-identified at the point they are transferred to UKILD. The staff transferring the 
images via IEP will require access to patient identifiable information. However, these staff will be 
employees of the collection site. The NHS numbers of the patients whose images are collected are 
pseudonymised as detailed above. The NHS/CHI number is also encrypted using an AES encryption 
algorithm and a complex salt in order to allow checking with the NHS Opt-out service.   This encrypted 
NHS number is stored at the Royal Surrey NHS Foundation Trust and access is maintained by named 
data managers only.  
 
2.5 Linking to External Datasets 
The ability to link to other data sources is essential. In order to facilitate this there are two options 
available. The first is linking via the encoded pseudonym and the second is through the use of two-
way encrypted NHS numbers. 
2.5.1 Linking via encoded pseudonyms 
It is possible to link UKILD with external datasets via a shared encoded pseudonym. This is relevant for 
linking to other studies which have access to the original NHS number. RSNFT tools can be utilised by 
the data managers of the other studies that can be applied to a list of NHS numbers. This would result 
in a list of encoded pseudonyms that would enable the two datasets to be linked. This process is 
detailed in Appendix 2 
2.5.2 Linking via encrypted NHS numbers 
The NHS/CHI number is encrypted using an AES encryption algorithm and a complex salt and stored 
at the RSNFT. This is in order to facilitate linking with national datasets that require a list NHS numbers 
to be submitted. No researchers will ever have access to this encrypted NHS number, and it is stored 
physically separate to the central data warehouse. If a data access request for linked data was 
approved, then the RSNFT staff would be able to utilise automated software tools to decrypt the NHS 
numbers and submit them to the national dataset retrieval processes. 

 
 
 
 
 
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Appendix 1: Anonymisation details 
 
Each medical image is stored in a standard DICOM format. In addition to the actual image there is a 
DICOM header with information stored in fields that are known as “tags” which contain a very large 
amount of information including patient identifiable information. In order to preserve the 
confidentiality of the patients the following changes are made to each DICOM header at the clinical 
site before it is transferred to the central warehouse. 
All the tags not mentioned below are retained as specified in the DICOM supplement 142 standards 
for anonymisation as they do not contain patient data or data likely to permit patient data to be 
accessed. 
Pseudonymisation of DICOM tags 
The following tags are pseudonymised: 
 
0010,0010: PatientName: This is replaced with the pseudonym 
0010,0020: PatientID: This is replaced with the pseudonym 
0010,0030: PatientBirthDate: This is altered, so that the year remains the same, but the day and 
month are set to “01” 
Study and Series Description are retained 
Private Tags are removed 
Nulling of DICOM tags 
The following tags are either removed or nulled: 
 
4008,0111 - Interpretation Approver Sequence 
0018,9424 - Acquisition Protocol Description 
0040,2010 - Order Callback Phone Number 
4008,0300 - Impressions 
4008,0118 - Results Distribution List Sequence 
0400,0100 - Digital Signature UID 
4008,0119 - Distribution Name 
0012,0031 - Clinical Trial Site Name 
0040,0253 - Performed Procedure Step ID 
0012,0030 - Clinical Trial Site ID 
0040,0254 - Performed Procedure Step Description 
4008,0114 - Physician Approving Interpretation 
60XX,4000 
4008,0115 - Interpretation Diagnosis Description 
0040,2016 - Placer Order Number / Imaging Service Request 
6000,4000 - Overlay Comments 
0012,0021 - Clinical Trial Protocol Name 
0040,2009 - Order Enterer’s Location 
4008,011A - Distribution Address 

 
 
 
 
 
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0040,2008 - Order Entered By 
0040,0248 - ? 
0028,4000 - Image Presentation Comments 
0040,A027 - Verifying Organization 
4008,0202 - Interpretation ID Issuer 
4008,0102 - Interpretation Recorder 
0012,0062 - Patient Identity Removed 
0012,0060 - Clinical Trial Coordinating Center Name 
0012,0020 - Clinical Trial Protocol ID 
0012,0010 - Clinical Trial Sponsor Name 
0010,0010 - Patient’s Name 
0010,2299 - Responsible Organization 
4008,010B - Interpretation Text 
0040,2017 - Filler Order Number / Imaging Service Request 
4008,010A - Interpretation Transcriber 
0010,2297 - Responsible Person 
4008,010C - Interpretation Author 
0008,010D - Context Group Extension Creator UID 
0040,1400 - Requested Procedure Comments 
0070,0001 - Graphic Annotation Sequence 
300A,0013 - Dose Reference UID 
0040,0275 - Request Attributes Sequence 
0012,0051 - Clinical Trial Time Point Description 
0012,0050 - Clinical Trial Time Point ID 
0010,0020 - Patient ID 
0040,1004 - Patient Transport Arrangements 
0040,1001 - Requested Procedure ID 
0010,0021 - Issuer of Patient ID 
0010,2180 - Occupation 
0032,0012 - Study ID Issuer 
0040,2400 - Imaging Service Request Comments 
0040,0280 - Comments on the Performed Procedure Step 
0040,000B - Scheduled Performing Physician Identification Sequence 
0010,1000 - Other Patient IDs 
0010,1001 - Other Patient Names 
0020,9161 - Concatenation UID 
0020,9164 - Dimension Organization UID 
0040,1005 - Requested Procedure Location 
0038,1234 - ? 
0012,0040 - Clinical Trial Subject ID 
0040,0006 - Scheduled Performing Physician’s Name 
0040,0007 - Scheduled Procedure Step Description 
0040,2001 - Reason for the Imaging Service Request 
0012,0042 - Clinical Trial Subject Reading ID 
0040,0004 - Scheduled Procedure Step End Date 
0040,0005 - Scheduled Procedure Step End Time 
0032,1021 - Scheduled Study Location AE Title 
0040,0012 - Pre-Medication 
0040,1010 - Names of Intended Recipients of Results 
0040,0011 - Scheduled Procedure Step Location 
0032,1020 - Scheduled Study Location 
0040,1011 - Intended Recipients of Results Identification Sequence 
0010,0032 - Patient’s Birth Time 
0040,0010 - Scheduled Station Name 
0010,0030 - Patient’s Birth Date 
0020,0052 - Frame of Reference UID 
0040,A07C - Custodial Organization Sequence 
0040,A07A - Participant Sequence 
0008,2112 - Source Image Sequence 
0040,A075 - Verifying Observer Name 
0008,0096 - Referring Physician Identification Sequence 
0008,0094 - Referring Physician’s Telephone Numbers 
0088,0910 - Topic Author 

 
 
 
 
 
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0040,A078 - Author Observer Sequence 
0008,0092 - Referring Physician’s Address 
0088,0912 - Topic Keywords 
0008,1060 - Name of Physician(s) Reading Study 
0008,1062 - Physician(s) Reading Study Identification Sequence 
0032,1030 - Reason for Study 
0040,0001 - Scheduled Station AE Title 
0008,2111 - Derivation Description 
0032,1032 - Requesting Physician 
0040,A073 - Verifying Observer Sequence 
0032,1033 - Requesting Service 
0040,0002 - Scheduled Procedure Step Start Date 
0040,0003 - Scheduled Procedure Step Start Time 
0010,1090 - Medical Record Locator 
2030,0020 - Text String 
0010,0102 - Patient’s Primary Language Modifier Code Sequence 
0008,0090 - Referring Physician’s Name 
0010,0101 - Patient’s Primary Language Code Sequence 
0020,4000 - Image Comments 
0038,0400 - Patient’s Institution Residence 
0088,0906 - Topic Subject 
0008,1195 - Transaction UID 
0008,0080 - Institution Name 
3006,00C2 - Related Frame of Reference UID 
0008,0081 - Institution Address 
0008,0082 - Institution Code Sequence 
0008,1050 - Performing Physician’s Name 
0008,1052 - Performing Physician Identification Sequence 
0020,0200 - Synchronization Frame of Reference UID 
0008,0201 - Timezone Offset From UTC 
4008,4000 - Results Comments 
3006,0024 - Referenced Frame of Reference UID 
0020,3406 - Modified Image Description 
0020,3404 - Modifying Device Manufacturer 
0008,1084 - Admitting Diagnoses Code Sequence 
0020,3401 - Modifying Device ID 
0040,0245 - Performed Procedure Step Start Time 
0008,1080 - Admitting Diagnoses Description 
0040,0244 - Performed Procedure Step Start Date 
0040,0243 - Performed Location 
0040,0242 - Performed Station Name 
0040,0241 - Performed Station AE Title 
0040,3001 - Confidentiality Constraint on Patient Data Description 
0020,0010 - Study ID 
0032,4000 - Study Comments 
0020,0012 - Acquisition Number 
0040,A088 - Verifying Observer Identification Code Sequence 
0020,000D - Study Instance UID 
0020,000E - Series Instance UID 
0008,1072 - Operator Identification Sequence 
0032,1060 - Requested Procedure Description 
0008,1070 - Operators’ Name 
FFFA,FFFA - Digital Signatures Sequence 
0008,0058 - Failed SOP Instance UID List 
0038,0010 - Admission ID 
0038,0011 - Issuer of Admission ID 
0040,A730 - Content Sequence 
0008,0050 - Accession Number 
0010,1050 - Insurance Plan Identification 
0038,0500 - Patient State 
0038,001E - Scheduled Patient Institution Residence 
0010,21B0 - Additional Patient History 
0018,4000 - Acquisition Comments 

 
 
 
 
 
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0018,1030 - Protocol Name 
0008,1155 - Referenced SOP Instance UID 
0008,1010 - Station Name 
0032,1070 - Requested Contrast Agent 
0038,0021 - Admitting Time 
0038,0020 - Admitting Date 
0400,0403 - Referenced SOP Instance MAC Sequence 
0008,4000 - Identifying Comments 
0400,0402 - Referenced Digital Signature Sequence 
0010,21C0 - Pregnancy Status 
0010,1060 - Patient’s Mother’s Birth Name 
0040,A124 - UID 
0038,0300 - Current Patient Location 
0040,A123 - Person Name 
0010,2203 - Patient’s Sex Neutered 
0010,2110 - Allergies 
0008,1040 - Institutional Department Name 
0018,1000 - Device Serial Number 
0018,1002 - Device UID 
0008,1049 - Physician(s) of Record Identification Sequence 
0018,1005 - Generator ID 
0018,1004 - Plate ID 
0018,1007 - Cassette ID 
0008,1048 - Physician(s) of Record 
0008,1140 - Referenced Image Sequence 
0018,1008 - Gantry ID 
FFFC,FFFC - Data Set Trailing Padding 
4008,0042 - Results ID Issuer 
0018,0010 - Contrast/Bolus Agent 
0070,0086 - Content Creator’s Identification Code Sequence 
0070,0084 - Content Creator’s Name 
0008,1030 - Study Description 
0040,DB0D - Template Extension Creator UID 
0040,DB0C - Template Extension Organization UID 
0038,0040 - Discharge Diagnosis Description 
0010,2000 - Medical Alerts 
0088,0200 - Icon Image Sequence 
0018,700A - Detector ID 
0400,0561 - Original Attributes Sequence 
0010,21A0 - Smoking Status 
0088,0140 - Storage Media File-set UID 
0038,4000 - Visit Comments 
0010,1080 - Military Rank 
0018,1400 - Acquisition Device Processing Description 
0010,1081 - Branch of Service 
4000,0010 - Arbitrary 
0070,031A - Fiducial UID 
0008,103E - Series Description 
0010,1002 - Other Patient IDs Sequence 
300E,0008 - Reviewer Name 
0400,0550 - Modified Attributes Sequence 
0008,1120 - Referenced Patient Sequence 
0010,1005 - Patient’s Birth Name 
0038,0050 - Special Needs 
50XX,XXXX 
0008,0018 - SOP Instance UID 
0000,1001 - Requested SOP Instance UID 
0008,0012 - Instance Creation Date 
0008,0013 - Instance Creation Time 
0008,0014 - Instance Creator UID 
0008,2112 - Source Image Sequence 
0020,9158 - Frame Comments 
0040,0555 - Acquisition Context Sequence 

 
 
 
 
 
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0010,21F0 - Patient’s Religious Preference 
0038,0060 - Service Episode ID 
0010,1010 - Patient’s Age 
0008,3010 - Irradiation Event UID 
4000,4000 - Text Comments 
0008,1110 - Referenced Study Sequence 
0028,1199 - Palette Color Lookup Table UID 
0038,0062 - Service Episode Description 
0002,0003 - Media Storage SOP Instance UID 
0038,0061 - Issuer of Service Episode ID 
0008,1111 - Referenced Performed Procedure Step Sequence 
0010,0050 - Patient’s Insurance Plan Code Sequence 
0010,2160 - Ethnic Group 
0040,4027 - Scheduled Station Geographic Location Code Sequence 
0040,4028 - Performed Station Name Code Sequence 
0040,0404 - ? 
0040,4023 - Referenced General Purpose Scheduled Procedure Step Transaction UID 
0040,4025 - Scheduled Station Name Code Sequence 
0000,0021 - ? 
0010,1020 - Patient’s Size 
0008,0030 - Study Time 
0008,0031 - Series Time 
0018,A003 - Contribution Description 
0010,2150 - Country of Residence 
0008,0033 - Content Time 
0008,0034 - Overlay Time 
0008,9123 - Creator-Version UID 
0010,2152 - Region of Residence 
0008,0035 - Curve Time 
0010,2154 - Patient’s Telephone Numbers 
0040,4036 - Human Performer’s Organization 
0040,4035 - Actual Human Performers Sequence 
0040,4034 - Scheduled Human Performers Sequence 
0040,4037 - Human Performer’s Name 
0010,21D0 - Last Menstrual Date 
0040,4030 - Performed Station Geographic Location Code Sequence 
0010,1030 - Patient’s Weight 
60XX,3000 
0008,0021 - Series Date 
0040,1103 - Person’s Telephone Numbers 
0008,0024 - Overlay Date 
0008,0025 - Curve Date 
0040,1102 - Person’s Address 
0040,1101 - Person Identification Code Sequence 
0008,0023 - Content Date 
0008,1511 - ? 
0010,1040 - Patient’s Address 
 
 
 
 
 

 
 
 
 
 
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Appendix 2: Guidelines for Linking to External Datasets 
Guidelines on using NHS Hasher tool to link data sources 
 
This document outlines the use of the NHS Hasher tool to create link-able pseudonyms which would 
allow disparate datasets to be linked. 
 
Pseudonyms 
1. Pseudonyms are created through a one-way encryption process known as ‘hashing’. 
2. The input string (e.g. NHS number) is combined with a fixed complex salt, and then fed into a 
hashing algorithm. 
3. The hashing algorithm used is SHA-256 (256-bit Secure Hashing Algorithm), which was 
developed by the National Security Agency (NSA). 
4. The hashed patient IDs are stored and are linked to the registered patient and any images 
received for that patient. 
 
A simple diagram to explain this hashing process is shown below (these are just example values); 
 
5. The fixed complex salt is stored on the database server and is applied to all NHS and hospital 
IDs. 
6. It is important to understand that the hashing process is one-way only - it is not possible to 
reconstruct the original NHS or hospital ID from the hashed string, even if the salt is known. 
7. However, we can compare the hashed string to another hashed string which has gone through 
the same process described in the diagram and thus be able to match up patient identifiers 
without ever exposing their original data. 
 
 
In either case the process is entirely automated, and the original NHS or hospital identifier is never 
retained. 
 

 
 
 
 
 
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Creating a Link-able Dataset NHS Hashing Tool 
A tool created by the Royal Surrey NHS Foundation Trust called the “NHS Hashing Tool” allows users 
to quickly generate a list of hashed patient identifiers and assign unique trial identifiers to each 
patient. 
 
The hashing tool works with Comma Separated Value (CSV) files.  These are easily obtained from Excel 
files by using “Save As…” and selecting CSV as the save type. 
 
See the appendix 2 for a step-by-step guide to using the hashing tool. 
 
It is important to note that most of these steps can be automated in the case that a regular feed of 
data is required. 
 
Step 1. Prepare your list of NHS numbers to ‘hash’.  This can be a simple Excel file with a single column; 
 
 
 
Step 2. The hashing tool only works with “CSV” files.  These are easily obtained from Excel, simple 
select File->Save As… and then select “CSV UTF-8 (Comma Separated)” from the list of options.  Save 
the file to a location you can easily find (e.g. Desktop); 
 
 
 
Step 3. Launch the NHS hasher tool.  This will be provided in an easy to open format that will not 
require any special privileges.  Simple double-click the “run.bat” file (on Windows) or double-click the 
“HashingTool.jar” file (on macOS).  The program will launch; 
 

 
 
 
 
 
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Step 4.  It is necessary to change the default options.  Click “Options” and make sure that “Enforce 
Secure Salts” and “Check NHS Numbers” are both turned off.  The default hashing algorithm should 
be set to “SHA-256”.  Do not change this; 
 
 
 
 

 
 
 
 
 
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Step 5. First you need to set the “Starting Row” in the “Data Import” section of the program.  This is 
the row number where the first NHS/CHI number is located.  In the example given in Step 1 this is row 
2.  Once you have set this, select “File” from the menu and choose “Import CSV File”.  This will give 
you a file selection window where you can choose a file to import into the program.  Please choose 
the CSV file you just saved from Excel.  In the example file given in Step 1 this would look as follows; 
 
 

 
 
 
 
 
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Step 6.  The NHS Hashing tool was designed to be used with research trials, therefore it expects a “trial 
code” to be generated against every NHS number before hashing can proceed.  This trial code is used 
as a way to link back to the original NHS numbers should they ever be required.  You can simply enter 
“trial” or something similar in the “Prefix” box, and then click “Generate Trial Codes”.  The result will 
look like this; 
 
 
 
 

 
 
 
 
 
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Step 7.  The next step is to generate the hashed values for the NHS numbers.  You will be given a “Salt” 
to enter into the “Salt String” box.  This must be copied exactly as given, otherwise the hashes will be 
wrong.  You can use the “Ctrl-V” command in Windows to paste the salt into this box.  You then click 
“Generate Hashes” and the program will create the hashed NHS numbers for you; 
 
 

 
 
 
 
 
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Step 8.  The final step is to select “File” and choose “Export CSV File”.  Select a suitable name, and then 
save the output file somewhere.  As a confirmation that the file has been saved you can double-click 
it and view the contents in Excel. 
 
 
Step 9. You can now use the lookup between the NHS number and the Hashed number to provide the 
Hashed number in any data transfers between datasets allowing linking on the matching Hashed 
numbers.