# Evaluation of a Telemedicine System for the Transmission of Morpho/Immunological Data Aiming at the Inclusion of Patients in a Therapeutic Trial

Authors: Jean-François Lesesve; Richard Garand
Journal: International Journal of Telemedicine and Applications
 (2009)

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## Abstract

Due to their high levels of achievement and efficiency, image digitalization and teletransmission tools are more and more frequently used. Applied to cellular haematology, these tools often contribute to diagnosis confrontation, sometimes within the framework of therapeutic trials. We present one of the first approaches of the use of telehaematology for the inclusion of patients in the GOELAMS chronic lymphocytic leukaemia 98 trial. The advantages were (1) the creation of a unique, protected, stable data bank that could be remotely consulted, (2) the use of digitized pictures which made expertise on identical documents possible, (3) the facility of computer exchanges between experts, in terms of reception as well as replying time delays. We were able to set out new standards of image sampling for CLL, solve the semantic divergences, and point out interobserver variability as regards morphology. The limiting factors were the important need for expert investment, but they more importantly concerned the first line morphologists who should benefit from adequate tools, in terms of computer equipment as well as members of staff, so as to apprehend this second reading system as a quality control procedure.


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## Body

## 1. Introduction

“Expert” reviewing of
microscopic data is  a well-known procedure in medical practice, within  the
framework of cooperative studies  with therapeutic, epidemiological, or
scientific purposes. In the  current state of things, this notion, however,
mostly remains a theoretical one owing to persisting practical difficulties in
its implementation [1]. Telehaematology consists in sending pictures of camera-digitized
cells from one computer to another via the internet network. It appears as
something easy which is more and more resorted to. Teletransmission of
microscopic images
enables us to overcome the usual obstacles usually met with traditional
methods of smear reviewing (transporting
delays, glass slide breakages) and offers new theoretical advantages (above all
standardization of the observed cells) [2]. In practice, this teletransmission
system remains underused in multicentric studies. Three GOELAMS protocols
(Groupe Ouest-Est d’Etude des Leucémies Aiguës et autres Maladies du Sang—Western/Eastern
group for the study of acute leukaemias and other blood pathologies) have been
completed: our study on chronic lymphocytic leukaemia (CLL) and two other ones
on acute myeloid leukaemias. The GOELAMS CLL 98 protocol
is being achieved;
our goal  was to develop the advantages and drawbacks of telehaematology for
patient inclusion.


## 2. Materials and Methods

### 2.1. Patients

The GOELAMS CLL 98 study is
a randomized multicentric study that compared the effectiveness and tolerance of
an intensive treatment with autologous bone marrow transplantation versus CHOP Binet treatment as first-line
treatment in patients under 60 years of age, with stage B or C CLL [3]. 86
patients were included on the following criteria: blood lymphocytosis >15×109/L
or  >5×109/L for at least 3 months, cytologic and histologic
medullary infiltrate ≥ 30%, stage B and C, between 18 and 60 years of age, no
preliminary treatment or chlorambucil only for less than 6 months.


### 2.2. Methods

May Gründwald Giemsa stained
blood smears were sent to an haematological expert located either in Nancy
(JFL) or in Nantes (RG) according to the geographic location of the center
where the patients had been recruited, France having been for that purpose
arbitrarily divided into two parts (East and West). The first expert captured
the digital images of the cells and then sent those pictures to the second
expert via a teletransmission device. The experts were supposed to have at
their disposal the complete blood count and the immunophenotypes performed by
the recruiting center and sent to them either by post or via the internet
network (after having been scanned) in an attachment. The aim was to obtain a fast
second reading of the results and provide the first expert with feedback, the consensus
eventually being transmitted to the recruiting center. The morphologic
documents were saved in a digitized visual-data bank, the smears could thus
quickly be sent back to the labs they initially came from.The digital images were
captured using an optical photonic microscope at×1000 magnification, an analogic
tri CCD camera, a computer connected to the Internet network and to a secure
web site (where the digitized pictures could be collected by the first expert
and where the second one could receive the files) (TRIBVN and CRIHAN systems).
The pictures of the lymphoid cells frequently corresponded to an almost
continuous sampling, supposedly representative of the blood smears (ghost cells
and poor quality pictures having been removed). Each and every cell was
described, different percentages could thus be obtained (mature cells, cleaved
cells, lymphoplasmocytoid variants, etc.) and, following from this, morphologic
classification of the CLL (common or atypical).The recruiting center’s
opinion as well as that of the first and second experts as regards cytology and
the interpretation of the immunophenotypes by flow cytometry were codified
thanks to a thesaurus which enabled standardization of the vocabulary used by
the different specialists as well as improved interpretation of the results (additional
thesaurus for haematology of the ADICAP code; Association pour le
Développement de l’Informatique en Cytologie et en Anatomopathologie—Association for the Development of Computer science
in Cytology and Anatomopathology), regarding the morphology: typical CLL H400;
atypical CLL H 401 (mixed prolymphocytic), H402 (mixed pleomorphic), H403
(other cytology, plasmocytoid).


## 2.1. Patients

The GOELAMS CLL 98 study is
a randomized multicentric study that compared the effectiveness and tolerance of
an intensive treatment with autologous bone marrow transplantation versus CHOP Binet treatment as first-line
treatment in patients under 60 years of age, with stage B or C CLL [3]. 86
patients were included on the following criteria: blood lymphocytosis >15×109/L
or  >5×109/L for at least 3 months, cytologic and histologic
medullary infiltrate ≥ 30%, stage B and C, between 18 and 60 years of age, no
preliminary treatment or chlorambucil only for less than 6 months.


## 2.2. Methods

May Gründwald Giemsa stained
blood smears were sent to an haematological expert located either in Nancy
(JFL) or in Nantes (RG) according to the geographic location of the center
where the patients had been recruited, France having been for that purpose
arbitrarily divided into two parts (East and West). The first expert captured
the digital images of the cells and then sent those pictures to the second
expert via a teletransmission device. The experts were supposed to have at
their disposal the complete blood count and the immunophenotypes performed by
the recruiting center and sent to them either by post or via the internet
network (after having been scanned) in an attachment. The aim was to obtain a fast
second reading of the results and provide the first expert with feedback, the consensus
eventually being transmitted to the recruiting center. The morphologic
documents were saved in a digitized visual-data bank, the smears could thus
quickly be sent back to the labs they initially came from.The digital images were
captured using an optical photonic microscope at×1000 magnification, an analogic
tri CCD camera, a computer connected to the Internet network and to a secure
web site (where the digitized pictures could be collected by the first expert
and where the second one could receive the files) (TRIBVN and CRIHAN systems).
The pictures of the lymphoid cells frequently corresponded to an almost
continuous sampling, supposedly representative of the blood smears (ghost cells
and poor quality pictures having been removed). Each and every cell was
described, different percentages could thus be obtained (mature cells, cleaved
cells, lymphoplasmocytoid variants, etc.) and, following from this, morphologic
classification of the CLL (common or atypical).The recruiting center’s
opinion as well as that of the first and second experts as regards cytology and
the interpretation of the immunophenotypes by flow cytometry were codified
thanks to a thesaurus which enabled standardization of the vocabulary used by
the different specialists as well as improved interpretation of the results (additional
thesaurus for haematology of the ADICAP code; Association pour le
Développement de l’Informatique en Cytologie et en Anatomopathologie—Association for the Development of Computer science
in Cytology and Anatomopathology), regarding the morphology: typical CLL H400;
atypical CLL H 401 (mixed prolymphocytic), H402 (mixed pleomorphic), H403
(other cytology, plasmocytoid).


## 3. Results

### 3.1. Workable Files

The duration of the protocol
was approximately 7 years (1st review: 29/November/1999; last review:
05/January/2006). 86 patients were
included but we could only work on 79-patient data. Some files were indeed not
provided by the laboratories, either because they had failed to send us the
requested documents (5 patients) or because data had been lost owing to laboratory
relocation (2 patients). 17 files were incomplete—with some
parameters missing such as the date of validation, the lymphocytosis, the cytologic/immunological
data. 56 files were digitized in Nancy and 23 in Nantes.


### 3.2. Agreements between Experts

#### 3.2.1. Morphology (Figure1)

Overall agreement was
obtained for 72% of the files (42 cases of typical CLL and 4 atypical). In one
case, the three morphologists agreed to exclude the patient (non-Hodgkin
lymphoma). Disagreements were reported in 28% of the cases. The diagnosis
itself was not challenged, only the exact morphologic classification being at
stake (CLL subtypes, “minor” disagreements). Disagreements between the opinions
of the recruiter and both experts mainly consisted of reclassification of
atypical towards typical CLL (five cases out of eight) or differences regarding
the morphologic subtype of atypical CLL (two cases). In one case, the experts
changed the CLL subclass from atypical to typical. Disagreements between the
experts themselves occurred in 14% of the cases, the first one having
classified 6 CLL out of 9 as typical whereas the second had identified them as
atypical. In 3 out of 9 CLLs, the two experts did not agree on the morphologic
subtype of atypical CLL. In another case, utter disagreement (three diverging
opinions) concerned a file that had initially been identified as typical CLL
and then changed to atypical, the two experts disagreeing on its morphologic
subtype.Figure 1
Cytologic concordance.As a conclusion, all three
agreed on a majority of files and disagreed on minor aspects of a minority of
cases. Morphologic agreement is thus possible to achieve. Cytologic
classification can consequently definitely be regarded as a reliable and
repeatable tool. Last but not least, as for “difficult” cytologies, the method
opened the door to discussion, which had not really been the case up to then
(the specialist being isolated in their centre and the expert difficult to
reach timely).


#### 3.2.2. Immunophenotype (Figure2)

The results of the
immunophenotypes were sent to the first expert by the recruiting centre along with
the blood smears. Everything (the immunophenotypes and the digitized pictures)
was then transferred to the second expert, either by e-mail in an attachment or
by post, with a one-day time-lag. The histograms were re-interpreted, and
Matutes scores were calculated. All patients had a Matutes score of 4 or 5,
except for 2 cases with a score of 3 and one case with a score of 1 (not
considered as CLL). Overall agreement between the 3 observers was 86%,
including the 3 patients with a score ≤3. Disagreements dawned in 14% of the
files. In 4% of the cases, the recruiter’s opinion was different from the experts’
point of view whereas in 10% of cases, the experts disagreed, one of them
however concurring to the recruiter’s viewpoint. Disagreements were related to
the calculation of the score, between 4 (2 observers) and 5 (1 observer) or
vice-versa. The CLL diagnosis was thus never questioned, whatever the
morphology. There was no utter disagreement (three diverging opinions). We could
thus conclude that as far as immunophenotypical diagnosis is involved, global
consensus is not out of reach.Figure 2
Flow cytometry concordance (Matutes scores).


### 3.3. Methodology

We aimed  to assess its
feasibility (in terms of efficiency, practical side,
etc.).


#### 3.3.1. Number of Digitized Cells per Digitized Pictures and per Files (Figures3–5)

This criterium is essential
for the feasibility of this method (review is quicker when cell concentration
is higher) and quite a number of cells have to be analyzed before giving one’s
opinion. The total number of images acquired in this protocol was 1460,
consisting of 2938 lymphocytes, which (theoretically) represents an average of
2 cells per picture. The minimum number of lymphocytes captured per image was 1
and the maximum 17, which corresponded to a508×109/L lymphocytosis,
namely the highest concentration that could be found in our series (Figure 3).
The minimum number of pictures per file was 9 and the maximum 48 (Figure 4). The
minimum number of captured  lymphocytes for one file was 15 and the maximum 121
(corresponding to the 508 G/L lymphocytosis, Figure 5), the median being 38. 42
lymphocytes per file was the theoretical average (2938 photographed
lymphocytes/70 files).  Consequently, photographing around 40 lymphocytes per
patient seemed appropriate to us as regards this type of lymphoproliferative
syndrome. This figure enables the observer taking the pictures to provide the
others with a sampling representative of the blood smear and the expert can
thus reach a relevant diagnosis.Figure 3
Distribution of
the number of lymphocytes per image.Figure 4
Distribution of the number of images per file.Figure 5
Distribution of the number of lymphocytes per file.


#### 3.3.2. Number of Lymphocytes Photographed and Complexity of the Morphologic Diagnosis (Figure6)

The CLLs were classified
either as typical (code ADICAP H400) or atypical morphology (H401, H402, H403).
We chose to focus only on the cases where both experts had a similar cytologic
diagnosis (N=53). The average number of lymphocytes captured per file was 40 (±21, N=40) for typical CLL versus 46
(±13, N=13) for atypical CLL. The difference in averages between the typical
and atypical CLLs was not significant (P>.2, student’s t-test).
The number of digitized lymphocytes is thus not significantly higher when the
morphology is atypical.Figure 6
Average numbers of captured lymphocytes
functions of the morphologic type of CLL.


#### 3.3.3. Cytologic Agreement/Disagreement and Number of Lymphocytes Photographed (Figure7)

The average number of
lymphocytes captured per file was 41 (±19,N=53) when both experts were in
agreement and 42 (±10, N=10) when they disagreed. The difference between the
averages of captured lymphocytes was not relevant (P>0.2, student’s t-test).
The number of captured cells is consequently of no influence on cytologic
agreement.Figure 7
Average numbers of captured lymphocytes functions of cytological concordance.


#### 3.3.4. Lymphocytosis and Number of Photographed Images (Figure8)

A link between the
lymphocytosis and the number of digitized images could be established (linear
Pearson coefficient,−0.46). The higher the lymphocytosis, the less images were
taken. This is an important aspect as regards the practical side, since less
time was necessary to save and maybe review the documents.Figure 8
Number of pictures taken functions of the
lymphocytosis.


#### 3.3.5. Delays of File Reception (Figure9)

In most cases, the cytologic and immunological
documents were sent to one of the experts by post, who then looked after their
digitization. Two cases were transmitted directly by e-mail (contrary to what
was mentioned in the protocol). In 30% of the cases, the files were received
within one month. For the remaining 70%, the time delay was several months and
sometimes even reached years! The delay between the two experts using the
teletransmission device was less than two weeks in 70% of the cases and 84% of
the files were validated within one month of receipt. However, 16% of the files
were validated after more than one month (16 weeks being the maximum).
Telehaematology enables validation to be completed approximately 12 times
faster than the traditional way of review (by post).Figure 9
Time delay between initial diagnosis and first
review.


## 3.1. Workable Files

The duration of the protocol
was approximately 7 years (1st review: 29/November/1999; last review:
05/January/2006). 86 patients were
included but we could only work on 79-patient data. Some files were indeed not
provided by the laboratories, either because they had failed to send us the
requested documents (5 patients) or because data had been lost owing to laboratory
relocation (2 patients). 17 files were incomplete—with some
parameters missing such as the date of validation, the lymphocytosis, the cytologic/immunological
data. 56 files were digitized in Nancy and 23 in Nantes.


## 3.2. Agreements between Experts

### 3.2.1. Morphology (Figure1)

Overall agreement was
obtained for 72% of the files (42 cases of typical CLL and 4 atypical). In one
case, the three morphologists agreed to exclude the patient (non-Hodgkin
lymphoma). Disagreements were reported in 28% of the cases. The diagnosis
itself was not challenged, only the exact morphologic classification being at
stake (CLL subtypes, “minor” disagreements). Disagreements between the opinions
of the recruiter and both experts mainly consisted of reclassification of
atypical towards typical CLL (five cases out of eight) or differences regarding
the morphologic subtype of atypical CLL (two cases). In one case, the experts
changed the CLL subclass from atypical to typical. Disagreements between the
experts themselves occurred in 14% of the cases, the first one having
classified 6 CLL out of 9 as typical whereas the second had identified them as
atypical. In 3 out of 9 CLLs, the two experts did not agree on the morphologic
subtype of atypical CLL. In another case, utter disagreement (three diverging
opinions) concerned a file that had initially been identified as typical CLL
and then changed to atypical, the two experts disagreeing on its morphologic
subtype.Figure 1
Cytologic concordance.As a conclusion, all three
agreed on a majority of files and disagreed on minor aspects of a minority of
cases. Morphologic agreement is thus possible to achieve. Cytologic
classification can consequently definitely be regarded as a reliable and
repeatable tool. Last but not least, as for “difficult” cytologies, the method
opened the door to discussion, which had not really been the case up to then
(the specialist being isolated in their centre and the expert difficult to
reach timely).


### 3.2.2. Immunophenotype (Figure2)

The results of the
immunophenotypes were sent to the first expert by the recruiting centre along with
the blood smears. Everything (the immunophenotypes and the digitized pictures)
was then transferred to the second expert, either by e-mail in an attachment or
by post, with a one-day time-lag. The histograms were re-interpreted, and
Matutes scores were calculated. All patients had a Matutes score of 4 or 5,
except for 2 cases with a score of 3 and one case with a score of 1 (not
considered as CLL). Overall agreement between the 3 observers was 86%,
including the 3 patients with a score ≤3. Disagreements dawned in 14% of the
files. In 4% of the cases, the recruiter’s opinion was different from the experts’
point of view whereas in 10% of cases, the experts disagreed, one of them
however concurring to the recruiter’s viewpoint. Disagreements were related to
the calculation of the score, between 4 (2 observers) and 5 (1 observer) or
vice-versa. The CLL diagnosis was thus never questioned, whatever the
morphology. There was no utter disagreement (three diverging opinions). We could
thus conclude that as far as immunophenotypical diagnosis is involved, global
consensus is not out of reach.Figure 2
Flow cytometry concordance (Matutes scores).


## 3.2.1. Morphology (Figure1)

Overall agreement was
obtained for 72% of the files (42 cases of typical CLL and 4 atypical). In one
case, the three morphologists agreed to exclude the patient (non-Hodgkin
lymphoma). Disagreements were reported in 28% of the cases. The diagnosis
itself was not challenged, only the exact morphologic classification being at
stake (CLL subtypes, “minor” disagreements). Disagreements between the opinions
of the recruiter and both experts mainly consisted of reclassification of
atypical towards typical CLL (five cases out of eight) or differences regarding
the morphologic subtype of atypical CLL (two cases). In one case, the experts
changed the CLL subclass from atypical to typical. Disagreements between the
experts themselves occurred in 14% of the cases, the first one having
classified 6 CLL out of 9 as typical whereas the second had identified them as
atypical. In 3 out of 9 CLLs, the two experts did not agree on the morphologic
subtype of atypical CLL. In another case, utter disagreement (three diverging
opinions) concerned a file that had initially been identified as typical CLL
and then changed to atypical, the two experts disagreeing on its morphologic
subtype.Figure 1
Cytologic concordance.As a conclusion, all three
agreed on a majority of files and disagreed on minor aspects of a minority of
cases. Morphologic agreement is thus possible to achieve. Cytologic
classification can consequently definitely be regarded as a reliable and
repeatable tool. Last but not least, as for “difficult” cytologies, the method
opened the door to discussion, which had not really been the case up to then
(the specialist being isolated in their centre and the expert difficult to
reach timely).


## 3.2.2. Immunophenotype (Figure2)

The results of the
immunophenotypes were sent to the first expert by the recruiting centre along with
the blood smears. Everything (the immunophenotypes and the digitized pictures)
was then transferred to the second expert, either by e-mail in an attachment or
by post, with a one-day time-lag. The histograms were re-interpreted, and
Matutes scores were calculated. All patients had a Matutes score of 4 or 5,
except for 2 cases with a score of 3 and one case with a score of 1 (not
considered as CLL). Overall agreement between the 3 observers was 86%,
including the 3 patients with a score ≤3. Disagreements dawned in 14% of the
files. In 4% of the cases, the recruiter’s opinion was different from the experts’
point of view whereas in 10% of cases, the experts disagreed, one of them
however concurring to the recruiter’s viewpoint. Disagreements were related to
the calculation of the score, between 4 (2 observers) and 5 (1 observer) or
vice-versa. The CLL diagnosis was thus never questioned, whatever the
morphology. There was no utter disagreement (three diverging opinions). We could
thus conclude that as far as immunophenotypical diagnosis is involved, global
consensus is not out of reach.Figure 2
Flow cytometry concordance (Matutes scores).


## 3.3. Methodology

We aimed  to assess its
feasibility (in terms of efficiency, practical side,
etc.).


### 3.3.1. Number of Digitized Cells per Digitized Pictures and per Files (Figures3–5)

This criterium is essential
for the feasibility of this method (review is quicker when cell concentration
is higher) and quite a number of cells have to be analyzed before giving one’s
opinion. The total number of images acquired in this protocol was 1460,
consisting of 2938 lymphocytes, which (theoretically) represents an average of
2 cells per picture. The minimum number of lymphocytes captured per image was 1
and the maximum 17, which corresponded to a508×109/L lymphocytosis,
namely the highest concentration that could be found in our series (Figure 3).
The minimum number of pictures per file was 9 and the maximum 48 (Figure 4). The
minimum number of captured  lymphocytes for one file was 15 and the maximum 121
(corresponding to the 508 G/L lymphocytosis, Figure 5), the median being 38. 42
lymphocytes per file was the theoretical average (2938 photographed
lymphocytes/70 files).  Consequently, photographing around 40 lymphocytes per
patient seemed appropriate to us as regards this type of lymphoproliferative
syndrome. This figure enables the observer taking the pictures to provide the
others with a sampling representative of the blood smear and the expert can
thus reach a relevant diagnosis.Figure 3
Distribution of
the number of lymphocytes per image.Figure 4
Distribution of the number of images per file.Figure 5
Distribution of the number of lymphocytes per file.


### 3.3.2. Number of Lymphocytes Photographed and Complexity of the Morphologic Diagnosis (Figure6)

The CLLs were classified
either as typical (code ADICAP H400) or atypical morphology (H401, H402, H403).
We chose to focus only on the cases where both experts had a similar cytologic
diagnosis (N=53). The average number of lymphocytes captured per file was 40 (±21, N=40) for typical CLL versus 46
(±13, N=13) for atypical CLL. The difference in averages between the typical
and atypical CLLs was not significant (P>.2, student’s t-test).
The number of digitized lymphocytes is thus not significantly higher when the
morphology is atypical.Figure 6
Average numbers of captured lymphocytes
functions of the morphologic type of CLL.


### 3.3.3. Cytologic Agreement/Disagreement and Number of Lymphocytes Photographed (Figure7)

The average number of
lymphocytes captured per file was 41 (±19,N=53) when both experts were in
agreement and 42 (±10, N=10) when they disagreed. The difference between the
averages of captured lymphocytes was not relevant (P>0.2, student’s t-test).
The number of captured cells is consequently of no influence on cytologic
agreement.Figure 7
Average numbers of captured lymphocytes functions of cytological concordance.


### 3.3.4. Lymphocytosis and Number of Photographed Images (Figure8)

A link between the
lymphocytosis and the number of digitized images could be established (linear
Pearson coefficient,−0.46). The higher the lymphocytosis, the less images were
taken. This is an important aspect as regards the practical side, since less
time was necessary to save and maybe review the documents.Figure 8
Number of pictures taken functions of the
lymphocytosis.


### 3.3.5. Delays of File Reception (Figure9)

In most cases, the cytologic and immunological
documents were sent to one of the experts by post, who then looked after their
digitization. Two cases were transmitted directly by e-mail (contrary to what
was mentioned in the protocol). In 30% of the cases, the files were received
within one month. For the remaining 70%, the time delay was several months and
sometimes even reached years! The delay between the two experts using the
teletransmission device was less than two weeks in 70% of the cases and 84% of
the files were validated within one month of receipt. However, 16% of the files
were validated after more than one month (16 weeks being the maximum).
Telehaematology enables validation to be completed approximately 12 times
faster than the traditional way of review (by post).Figure 9
Time delay between initial diagnosis and first
review.


## 3.3.1. Number of Digitized Cells per Digitized Pictures and per Files (Figures3–5)

This criterium is essential
for the feasibility of this method (review is quicker when cell concentration
is higher) and quite a number of cells have to be analyzed before giving one’s
opinion. The total number of images acquired in this protocol was 1460,
consisting of 2938 lymphocytes, which (theoretically) represents an average of
2 cells per picture. The minimum number of lymphocytes captured per image was 1
and the maximum 17, which corresponded to a508×109/L lymphocytosis,
namely the highest concentration that could be found in our series (Figure 3).
The minimum number of pictures per file was 9 and the maximum 48 (Figure 4). The
minimum number of captured  lymphocytes for one file was 15 and the maximum 121
(corresponding to the 508 G/L lymphocytosis, Figure 5), the median being 38. 42
lymphocytes per file was the theoretical average (2938 photographed
lymphocytes/70 files).  Consequently, photographing around 40 lymphocytes per
patient seemed appropriate to us as regards this type of lymphoproliferative
syndrome. This figure enables the observer taking the pictures to provide the
others with a sampling representative of the blood smear and the expert can
thus reach a relevant diagnosis.Figure 3
Distribution of
the number of lymphocytes per image.Figure 4
Distribution of the number of images per file.Figure 5
Distribution of the number of lymphocytes per file.


## 3.3.2. Number of Lymphocytes Photographed and Complexity of the Morphologic Diagnosis (Figure6)

The CLLs were classified
either as typical (code ADICAP H400) or atypical morphology (H401, H402, H403).
We chose to focus only on the cases where both experts had a similar cytologic
diagnosis (N=53). The average number of lymphocytes captured per file was 40 (±21, N=40) for typical CLL versus 46
(±13, N=13) for atypical CLL. The difference in averages between the typical
and atypical CLLs was not significant (P>.2, student’s t-test).
The number of digitized lymphocytes is thus not significantly higher when the
morphology is atypical.Figure 6
Average numbers of captured lymphocytes
functions of the morphologic type of CLL.


## 3.3.3. Cytologic Agreement/Disagreement and Number of Lymphocytes Photographed (Figure7)

The average number of
lymphocytes captured per file was 41 (±19,N=53) when both experts were in
agreement and 42 (±10, N=10) when they disagreed. The difference between the
averages of captured lymphocytes was not relevant (P>0.2, student’s t-test).
The number of captured cells is consequently of no influence on cytologic
agreement.Figure 7
Average numbers of captured lymphocytes functions of cytological concordance.


## 3.3.4. Lymphocytosis and Number of Photographed Images (Figure8)

A link between the
lymphocytosis and the number of digitized images could be established (linear
Pearson coefficient,−0.46). The higher the lymphocytosis, the less images were
taken. This is an important aspect as regards the practical side, since less
time was necessary to save and maybe review the documents.Figure 8
Number of pictures taken functions of the
lymphocytosis.


## 3.3.5. Delays of File Reception (Figure9)

In most cases, the cytologic and immunological
documents were sent to one of the experts by post, who then looked after their
digitization. Two cases were transmitted directly by e-mail (contrary to what
was mentioned in the protocol). In 30% of the cases, the files were received
within one month. For the remaining 70%, the time delay was several months and
sometimes even reached years! The delay between the two experts using the
teletransmission device was less than two weeks in 70% of the cases and 84% of
the files were validated within one month of receipt. However, 16% of the files
were validated after more than one month (16 weeks being the maximum).
Telehaematology enables validation to be completed approximately 12 times
faster than the traditional way of review (by post).Figure 9
Time delay between initial diagnosis and first
review.


## 4. Discussion

This study aimed at putting
forward one of the first approaches of the use of telehaematology for the
quality control of diagnosis [4]. The GOELAMS CLL 98 trial was chosen to assess
this second reading system (blood smears and immunophenotypes). Above all, we
wanted to question the efficiency of the method in use since second reading
through resort to digitized pictures is,
contrary to what might be assumed, a technique which remains largely underused
[5].As
regards the morphologic classification, we noticed unanimous agreement in more
than 2/3 of the cases. When the morphology was typical, agreement on the cytologic
conclusion was almost systematic. 8 cases of disagreement have been reported—the experts
having an opinion diverging from the recruiting centre. This can be due to the
limited experience of the latter in the field, which justifies the request for
a second expert opinion for the inclusion of patients. Furthermore, the experts
themselves disagreed on 9 cases. This might seem weird in so far as each digitized
cell was analyzed by both experts to classify the CLL. It proves that the same
cell can be classified differently by two different specialists. Cytology is
above all a matter of interpretation, thus implying a potentially important
bias. On the whole, the three specialists agreed on most cases; and the experts
disagreed on minor aspects of a minority of cases (the CLL diagnosis was never
challenged). Immunophenotypical profile of the CLLs is the second important
means to classify the illness. Matutes scores were really helpful for the
diagnosis. In our study, almost all the patients scored 4 or 5, as expected.
One patient scored 1, which enabled us to leave CLL aside, since it
corresponded to the morphology of a leukaemic phase of lymphoma. The experts’
conclusions had no impact on the score which had been predefined by the
recruiting centre. Indeed, despite global disagreement in 13% of the cases, the
only evolution of Matutes scores was between 4 and 5, both indicating CLL.
These differences could be accounted for by the different threshold levels used
for the isotypic controls, which modified the percentage of cells considered
positive as well as the fluorescence intensity, thus affecting data
interpretation. On the whole, global agreement between the three specialists
prevailed. The differences of interpretation were not significant. We can thus
conclude on the reliability of the laboratories where the immunophenotypes had
been performed and say that they are the most capable of interpreting their
histograms. Agreement was more frequent with the immunophenotypes than with
cytology, which can be explained by the fact that immunophenotypical
interpretation is more objective (charts are provided) compared to the
relatively subjective dimension of cytologic analysis (“individual” morphologic
interpretation).So as to increase the
feasibility of this type of inclusion protocol, we suggest sending the
digitized pictures only accompanied with the data related to the Matutes scores
as sufficient to validate patient inclusion.Although no minimal standards
of sampling had been pre-established, we found around 40 lymphocytes per file
to be appropriate for this type of lymphoproliferative syndrome. This figure is
in agreement with the minimum threshold of 30 lymphocytes previously
established in another study, which consisted in requesting for specific
opinion on various haematological disorders [1]. That figure can be used for
both typical and atypical CLL since we have shown that there is no significant
difference between the average numbers of captured cells in relation to the
complexity of the diagnosis. Moreover, (dis)agreement about the CLL codification
between the two experts was not related to the number of captured lymphocytes. Time
is another parameter that has to be taken into account in the evaluation of the
feasibility of the method. 60 to 90 minutes were necessary to digitize,
classify and send the file. We wanted to find out whether there was a
connection between the number of pictures taken (and thus the time spent on
each smear) and the lymphocytosis. This indeed appears to be true to some
extent, and although the tendency was not very clear (“visual” analysis of the
slope of the trendline), a statistical link could yet be established. The
number of images taken and the lymphocytosis were inversely correlated.
Nevertheless, the specialist had to use the maximal magnification available (×100)
since analysis of the cellular detail (shape and structure of the cell and its
nucleus) is crucial for morphologic subclassification. However, with such a
magnification, finding more than one cell in each image proved unfrequent, most
images containing only one cell, whatever the cellular density on the smear may
have been (high lymphoytoses >100×109/L being included). What is important was to manage to get a
sampling which was representative of the smear’s morphologic variability
(diagnostic criterium). An average of around 40 lymphocytes, whatever the
lymphocytosis, seemed to make this possible (practical criterium). A line
sampling enabled us to meet these two requirements in most cases.The time delay between the
recruiting centre and the first expert for files sent by post was around one
month for one third of the files, which can arbitrarily be defined as
“acceptable”. But for the remaining 2/3, the delay was tantamount to several
months and even years. One of the causes that could be put forward is that the
centres which are requested to participate in cooperative studies are often
reluctant to part from their records and archives. The delays and uncertainties
caused by sending fragile documents by post indeed represent a serious
drawback: the archive materials are frequently deteriorated (broken blood
smears) and are not available for quite long periods of time. It was precisely
one of the aims of the second reading protocol—namely to avoid
parcel sending (at least from an expert to the other) after having certified that
the original documents would be returned to the recruiting center once the
digitized file was ready. Teletransmission clearly improved the second reading
system. However, it is not yet completely satisfying since 16% of the files had
still not been validated after a month. That can be explained by a two-week
maintenance of the CRIHAN secure website and by the expert’s unavailability or
material incapability, and so forth. However, electronic data interchange has proved
much faster than traditional mail (by post). This is obviously due to a greater
speed of transmission (a few seconds instead of several days, or even more). We,
however, believe that “motivation” plays a key role and is even more crucial. A
direct email enclosing a request for a second reading is probably a greater
incentive than more anonymous form letters. The time taken for the expert to
reply was, for the most part, compatible with that of clinical decision-making.
The expert’s role was mainly to give a second opinion (validation). As for
traditional second reading (slides sent by post or seminars such as “Forum
Workshop”), the slowness of the whole thing prevented the results from being
returned on time and, as such, they often came too late to influence in any way
the therapeutic options that had already been chosen (for CLLs, a one-month
time delay remains acceptable). Thanks to telehaematology, we can thus move on
from a hypothetical and dubious retroactive assessment to an upstream quality
control of the therapeutic decisions. The notion of time delay could even be
eliminated thanks to software that enable two users to establish a direct
connection and thus to hold a real-time dialogue and comment upon an image
simultaneously thanks to a mobile pointer [5]. For example, that system allowed
an expert to guide a nonspecialist technician and thus confirm the diagnosis.
But however tempting this solution may appear, it should definitely not be
privileged for financial reasons, since this equipment is far more expensive
[1, 6]. Indeed, the expert (from where he is) is supposed to perform the tasks
that the local morphologist would normally be doing; the expert thus replaces
the morphologist instead of merely assisting them. The experts’ availability
being one of the major parameters accounting for the slowness of
telepathology’s development, asking them to become substitutes, does not seem
very realistic to us [1].Last but not least, one of
the major gains was the creation of an objective database that was available
for remote consultation (geographically and temporally). Indeed, one of the
aims of the biological protocol was to set up a morphologic database. All the
digitized pictures were saved in the CRIHAN secure website and were thus freely
available to users, especially in case of dispute over the conclusions. A first
step has been taken to solve the semantic inconsistencies related to the use of
classifications [7]. The diversity of interpretations now remains to be tackled
since, as our study showed, two experts do not necessarily classify the same
cell in the same category, even though the differences are almost negligible.
The creation of this database also enabled us to keep track of the initial
blood smear (which is at present not mandatory in the majority of therapeutic
protocols) and thus to keep an eye on disease evolution. As every time
information is exchanged, respect of medical secrecy has to be ensured. Using a
specifically dedicated talk-back secure website enabled us to guarantee the
safety of sent and received messages since passwords were required. All
messages posted through the secure website were saved (including the content
and the replies) and both document history and traceability were preserved.
Consequently, it is essential for good practice to use a dedicated secure
website, as we did, rather than traditional emails and the protocol did not
call this into question.We sometimes noticed the difficulties
encountered by some recruiting centres to provide us with the files. The time
delays sometimes reached months, and even years. Several hypotheses can be put
forward: (1) the lack of experience of small-size laboratories in taking part
in protocols and the fact that they also keep less track of patient files, (2) the
innovative dimension of our protocol, which consisted in assessing the validity
of the initial diagnosis, (3) the main (therapeutic) objective of the protocol
involved that the specialist was supposed
to hand over data to “their” expert so that transmission of the biological files
could be properly achieved (the need for which might have been overlooked by
the specialist, especially for such a common pathology as CLL). We thus once
again would like to stress the importance of establishing a dialogue between the
specialists and the experts, from which transmission of the information about
the biological and therapeutic protocols would follow. What can also (especially) be called into
question is the current chronic underequipment of the laboratories, both in
terms of specific hardware and members of staff. The current implementation of
teletransmission devices will allow on the premises digitization of the files,
which will consequently simplify the procedure and lead to better compliance
and efficiency of such types of second reading. Moreover, the conditions
regulating resort to “experts” and to “telehaematology expert networks” remain
vague in so far as this activity has not yet been officially taken into account
by the healthcare authorities and consequently does not benefit from any
specific status or any guidelines as far as the financial aspect is involved
[8]. There are unfortunately very few documented experiments that we know of dealing
with that kind of cytologic activities [4, 9]. We could thus hardly find  any
data to compare our conclusions with. However, several initiatives implying
telehaematology have recently been or are currently being implemented in France
(Table 1). Moreover, databases
associated with second reading protocols via teletransmission devices have been
set up. However, the conclusions of such second readings are not awaited to
introduce treatment. City/hospital networks have been created [10].  To finish,
there are a few websites, such as Médecin’images or the one of the Collège de Hôpitaux Généraux thanks to
which high quality exercises can be performed via teletransmission [11].Table 1PathologyProtocolChair(wo)manStarting dateFrench protocols using telemedecine for mandatory morphological consensus whorkshop
(needed for inclusion)Chronic
lymphocytic leukemiasGOELAMS
LLC 98JF
Lesesve (Nancy) and R Garand (Nantes)Sept-1999
(achieved)Acute
myeloblastic leukemias (adults)GOELAMS 3S Daliphard (Reims) and V Leymarie (Strasbourg)March-2002 (achieved)Acute myeloblastic leukemias (adults)LAM-SA 2002P Mossuz (Grenoble)April-2004 (in progress)Acute myeloblastic leukemias (pediatric)ELAM02O Fenneteau (Paris Robert Debré)March-2005 (in progress)French morphological data banks using telemedecineMyelomasIFMM Zandecki (Angers)2000 (achieved)Acute myeloblastic leukemiasMatchslideG Flandrin (Paris Necker)01/11/2001 (achieved)Red blood cellsTeleslideG Flandrin (Paris Necker), JF Lesesve (Nancy),01/09/2003 (achieved)O Fenneteau (Paris R Debré), T Cynober (Kremlin Bicêtre)Myelodysplastic syndromesGFMDSF Picard (Paris Cochin)Dec-04 (in progress)French
morphological quality-control testsAll topicsMedecin'imageJX Corberand (Toulouse)All
topicsCollège
des Hopitaux Généraux/teleslideD Lusina,
JM Martelli (Aulnay sous bois)January-2003
(in progress)Forum
whorkshops (congresses of the “Groupe Français d'Hématologie
Cellulaire”) open to discussionMyeloproliferative
diseasesCongress GFHC SMP2005, NantesR Garand (Nantes)2005.05.17B-cell lymphoproliferative syndromesCongress GFHC SLP2007, LyonR Garand (Nantes)2007.05.22Acute leukemias and myelodysplastic syndromesMeeting GFHC, ParisS Daliphard (Reims)2006.11.09Thrombopenia et thombopathies (excluding malignancies)Meeting GFHC, ParisS Daliphard (Reims)2007.11.28



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