Digital pathology evaluation of complement C4d component deposition in the kidney allograft biopsies is a useful tool to improve reproducibility of the scoring

Abstract

Abstract Complement C4d component deposition in kidney allograft biopsies is an established marker of antibody-mediated rejection. In the Banff 07 classification of renal allograft pathology, semi-quantitative evaluation of the proportion of C4d-positive peritubular capilaries (PTC) is used. We aimed to explore the potential of digital pathology tools to obtain quantitative and reproducible measure of C4d deposition in the renal allograft tissue. 34 routine kidney allograft biopsies immunohistochemically stained for C4d were included in the study and were evaluated by a qualified pathologist twice, recording an approximate percentage of positive PTC and glomerular area. The same slides were scanned by Aperio ScanScope scanner. Two layers of annotations were created: layer of glomeruli and the remaining non-glomerular area. Image analysis was performed with Aperio Positive Pixel Count algorithm to quantify the proportion of C4d-positive pixels in the area analysed. The percentage of positive (defined as 2+ and 3+) pixels in glomeruli and non-glomerular area was obtained and compared to the percentage of C4d-positive PTC and C4d-positive area of glomeruli recorded by the pathologist. The correlation of digital and manual C4d-positive area scoring in glomeruli was very high (r= 0.89, p

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PROCEEDINGS Open Access
Digital pathology evaluation of complement C4d
component deposition in the kidney allograft
biopsies is a useful tool to improve
reproducibility of the scoring
Ernesta Brazdziute, Arvydas Laurinavicius
*
From The 10th European Congress on Telepathology and 4th International Congress on Virtual Microscopy
Vilnius, Lithuania. 1-3 July 2010
Abstract
Complement C4d component deposition in kidney allograft biopsies is an established marker of antibody-
mediated rejection. In the Banff 07 classification of renal allograft pathology, semi-quantitative evaluation of the
proportion of C4d-positive peritubular capilaries (PTC) is used. We aimed to explore the potential of digital
pathology tools to obtain quantitative and reproducible measure of C4d deposition in the renal allograft tissue.
34 routine kidney allograft biopsies immunohistochemically stained for C4d were included in the study and were
evaluated by a qualified pathologist twice, recording an approximate percentage of positive PTC and glomerular
area. The same slides were scanned by Aperio ScanScope scanner. Two layers of annotations were created: layer of
glomeruli and the remaining non-glomerular area. Image analysis was performed with Aperio Positive Pixel Count
algorithm to quantify the proportion of C4d-positive pixels in the area analysed. The percentage of positive
(defined as 2+ and 3+) pixels in glomeruli and non-glomerular area was obtained and compared to the
percentage of C4d-positive PTC and C4d-positive area of glomeruli recorded by the pathologist.
The correlation of digital and manual C4d-positive area scoring in glomeruli was very high (r= 0.89, p<0.0001),
while the correlation for non-glomerular (digital) and PTC (manual) area was moderate (r=0.60, p<0.001). The
correlation between digital and manual evaulation of C4d in non-glomerular area after exclusion of C4d-positive
arterioles from analysis did not improve substantially (r = 0.59, p < 0.001). Reproducibility of digital and manual
results was evaluated. For C4d deposition in PTC, agreement between the first and the second digital C4d
evaluation (after re-drawing annotations) was perfect (=0.96, CI 0.91÷1.00) while agreement between two
subsequent manual C4d scorings was substantial (= 0.67, CI 0.47 ÷ 0.88). Similarly, for C4d deposition in the
glomeruli, agreement of digital evaluation was perfect (=1) while for manual scorings it was substantial (= 0.76,
CI 0.64 ÷ 0.88).
Digital evaluation of C4d deposition in allograft kidney correlates with pathologist‘s scoring and exceeds the latter
in reproducibilty. Therefore, it provides a useful tool to control for intraobserver and interobserver variability and
may serve as quality assurance measure for allograft pathology diagnosis and research.
* Correspondence: arvydas.laurinavicius@vpc.lt
National Centre of Pathology and Vilnius University Faculty of Medicine,
Vilnius, Lithuania
Brazdziute and Laurinavicius Diagnostic Pathology 2011, 6(Suppl 1):S5
http://www.diagnosticpathology.org/content/6/S1/S5
© 2011 Brazdziute and Laurinavicius; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the
Creative Commons Attribution License (http://cre ativecommons.org/lic enses/by/2.0), which permits unrestricted use, distribution, and
reproductio n in any medium, provided the original work is properly cited.

Background
Renal biopsy is the gold standard for acute rejection in
renal transplant recipients where both humoral and cel-
lular rejection mechanisms play the role. Acute humoral
rejection may be associated with the appearance of anti-
donor specific antibodies. In renal biopsy, complement
split product C4d deposition in the peritubular capil-
laries (PTC) is considered to be a marker of antibody-
mediated anti-donor humoral response [1,2].
In 2007, Banff classification of renal allograft pathol-
ogy was updated with C4d deposition scoring scheme
thus increasing the importance of robust and reproduci-
ble measurement of C4d deposition [3]. Several studies
have demonstrated a remarkable inter-observer variabil-
ity of histological grading of the kidney allograft pathol-
ogy [4,5]. Interobserver reproducibility for the score of
C4d expression in PTC was moderate (k=0.57-0.63)
while intraobserver reproducibility was substantial
(k=0.68–0.83) [6]. Furthermore, Furness et al. have
shown that reproducibility of Banff classification
throughout Europe was low, revealing that international
variation is even greater than inter-observer variation
within small groups of pathologists working in the same
institution or country.
Digital pathology is an emerging technology that pro-
vides quantitative tools to improve measurement and
reproducibility of grading, including that of renal allo-
graft rejection. Successful application of digital techni-
ques has been shown in renal allografts for interstitial
fibrosis [7] and tubulitis [8] scoring.
To our knowledge, the potential of digital technologies
to evaluate C4d deposition in renal allograft has not
been explored. Therefore, we aimed to investigate con-
cordance and reproducibility of the measurements pro-
duced by a pathologist and Aperio Positive Pixel Count
algorithm.
Materials and methods
This study included 34 kidney allograft core needle
biopsies from 32 patients.
Sections (3 micrometer-thick) of formalin-fixed paraf-
fin-embedded renal tissue were stained with rabbit anti-
human C4d polyclonal antibody (polyclonal antibody,
Spring Biosience). Glass slides with biopsy tissue were
viewed and evaluated twice by pathologist (AL) scoring
the percentage of C4d-positive peritubular capillaries
(PTC) and the percentage of C4d-positive area of the
glomeruli. The same 34 glass slides were scanned with
Aperio ScanScope scanner using “Faint”parameters in
order to obtain a better quality of virtual slides. The
slides were viewed and annotated with Aperio Image-
Scope program by another investigator (EB). The first
layer of each virtual slide annotations was created
manually selecting glomeruli-only area (all glomeruli on
the section) (Fig. 1), the second layer included all
remaining area of renal tissue (except glomeruli and
areas of significant fibrosis, Fig. 2). Both layers were
separately analyzed with automated image analysis algo-
rithm Aperio Positive Pixel Count v9 using default set
of parameters. To test the reproducibility of automated
image analysis, it was repeated after re-creating the
annotations and running the algorithm with default
parameters.
An algorithm output provided a number of 1+, 2+ and
3+ intensity positive pixels and the number of total pixels
in each annotated layer (glomeruli and non-glomerular
tissue). Total number of pixels consisted of positive and
negative pixels excluding white area of the virtual slides
(i.e., the center of tubules, vacuoles, Bowman’s capsule
space). Since 1+ pixel areas were mostly picking-up weak
background staining of the tubules and other structures
but not C4d deposition in the capillaries, only 2+ and 3+
areas were regarded as C4d-positive for further analysis.
To compare pathologist’sscoreswithAperioalgorithm
results, the percentage of 2+ and 3+ pixels was
calculated.
Pathologist’s scores and automated image analysis
results were compared using Pearson’s correlation and
weighted kappa concordance statistics. To measure
inter-observer variability between manual PTC and
automated non-glomerular tissue scoring, scores were
divided: a) manual and automated scores into 5 equal
intervals; b) manual scores into three groups according
to Banff 07 classification: 0–10% (C4d0-1), 11–50%
(C4d2), and 51–100% (C4d3) while automatic scores of
Figure 1 Automated image analysis in glomerular tissue. Manually
selected glomeruli were analysed with Aperio Positive Pixel Count
algorithm. Different colors indicate the intensity level of C4d
positive pixels (red –3+, orange - 2+, yellow –1+ ).
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non–glomerular and glomerular C4d deposition were
divided into three intervals 0–1, 1.1 –2.6, >2.6% and
0–5, 5.1–15.9, >16 %, respectively (“3 thirds”); c) manual
scores divided the same like in b), but automated scores
divided into 3 intervals with the same proportion of
cases like in manual scoring Banff intervals (“automated
Banff”); d) manual scores divided into six groups: 0, 1,
2-10, 11-30, 31-60 and 61-100% while automated scores
were divided into 6 groups with the same number of
cases like in each manual score interval. Analysis was
performed with SAS 9.2 statistical package.
Results
C4d deposition in glomeruli
The positivity values obtained by automated analysis in
all virtual slides ranged from 0.11 to 73.21%, with a
mean of 18.96 ± 21.18%. The pathologist scored C4d
deposition in glomeruli estimating approximate propor-
tion of C4d-positive area in all glomerular capillaries
observed. The scores ranged from 0 to 100% with a
mean of 43.40 ± 40.66%.
Correlation between the pathologist’s and digital score
was strong (r=0.89, p<0.0001). The values are plotted on
the Fig. 3. To avoid the impact of asymmetrical distribu-
tion of the values, we also performed Pearson’s correla-
tion with logarithmic values (r=0.82, p<0.0001).
C4d deposition in non-glomerular area
The positivity values obtained by automated analysis in
non-glomerular tissue area averaged at 3.02±3.01 (range
0.23-13.57%). One case with an outlier value of C4d
positivity at 13.57 was observed: a review of this case
revealed cellular rejection (Banff class IA) with an
extensive C4d deposition in the interstitium and tubular
basement membranes. This case was excluded from
further analysis. After exclusion of this case, average
positivity values were 2.57 ± 2.25 (range 0.23–8.77%).
The pathologist’s score of C4d-positive PTC ranged
from 0 to 100%, the mean was 28.55 ± 31.36%.
Moderate (0.60, p<0.001) correlation was observed
between the manual and automated scores, plotted on
the Fig. 4. Exclusion of one case mentioned above,
increased this correlation up to 0.77 (p<0.001). To
avoid the impact of asymmetrical distribution of the
values, we performed additional tests that confirmed
the relation: Wilcoxon signed ranks test (p<0.001) and
Figure 2 Automated image analysis in non-glomerular area.
Glomeruli were excluded from this annotation layer. C4d positive
peritubular capillaries are marked with orange (2+ intensity pixels)
or red (3+ intensity pixels) colors.
Figure 3 A plot of manual and automated evaluation of C4d
deposition in glomeruli.
Figure 4 A plot of manual and automated evaluation of C4d in the
non–glomerular area (one outlier case (Banff class IA) at 14%
automated score can be noted).
Brazdziute and Laurinavicius Diagnostic Pathology 2011, 6(Suppl 1):S5
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Pearson’s correlation with logarithmic values (r=0.79,
p<0.0001).
To test potential impact of occasional C4d–positivity
in the arterioles on the automated score, we performed
additional analyses of the non-glomerular area after
manual annotation excluding the arterioles from the
automated analysis. The average scores slightly but not
significantly decreased (3.02 to 2.81) and the correlation
with the manual score did not change substantially -
0.59 (p< 0.001).
Inter- and intraobserver variability
Intraobserver agreement for manual glomerular area
scores ranged from 0.76-0.87 for various grouping of
cases while intraobserver‘s agreement for automated glo-
merular area scores was perfect (k=1). Kappa values for
interobserver agreement for manual and automated glo-
merular scoring (subdivided into various intervals, not
shown) ranged from 0.68 to 0.79.
Kappa values for various scoring intervals of the non-
glomerular area are presented in the Table 1. While
intraobserver concordance of manual evaluation ranged
at kappa values of 0.67 to 0.71, intraobserver concor-
dance of the automated scoring was excellent (k=0.93÷1).
Remarkably, manual-automated interobserver agreement
(kappa values in the range of 0.50 to 0.71) was compar-
able to that of manual intraobserver variability.
Discussion
Many studies reveal rather low inter- (k=0.57) and intra-
pathologist‘s (k=0.68) variability for semi-quantitative
evaluation of pathological changes, especially when
pathologist‘s work in different centers and countries. In
fact, this reveals the need of more objective and repro-
ducible measurement not only in clinical practice but
also for research and clinical studies. We tested a
hypothesis if automated image analysis tool –Aperio
Positive Pixel Count algorithm –is comparable to the
pathologist‘s scoring and could add benefits of auto-
mated and reproducible measurement. As our data
showed, automated scoring strongly correlated with
manual scores for the glomerular and moderately for
the non-glomerular C4d deposition. Interobserver agree-
ment (k=0.50 - 0.71) did not differ substantially from
intrapathologist‘s agreement (k=0.67- 0.71) while the
reproducibility of automated scoring was much better
(k=0.93- 1) than that of manual scoring. Although auto-
mated measurement produces a different parameter
(proportion of positive pixels in the whole non-glomeru-
lar area) from the manual scoring (proportion of posi-
tive PTC), they both aim to measure relative quantity of
C4d in the renal tissue. We assumed that in cases with-
out signifficant fibrosis, atrophy or inflammation, the
number of peritubular capillaries is more or less the
same from case to case, therefore the measurement of
positive pixel area should correlate the manual measure-
ment of C4d according to the Banff07 classification.
Since the concordance measures revealed similar man-
ual-automated interobserver and manual intraobserver
variability at the level of kappa of 0.7, automated analy-
sis of C4d could be a useful tool for quality assurance
and intercenter studies with the advantage of better
intraobserver agreement.
Conclusion
Digital evaluation of C4d deposition in allograft kidney
correlates with pathologist‘s scoring and exceeds the lat-
ter in reproducibilty. Therefore, it provides a useful tool
to control for intraobserver and interobserver variability
and may serve as quality assurance measure for allograft
pathology diagnosis and research.
Acknowledgements
Ernesta Brazdziute acknowledges Student Research Fellowship Award from
the Lithuanian Science Council. The authors thank Justinas Bauzys and
Kestutis Mikalajunas for their excellent technical support.
This article has been published as part of Diagnostic Pathology Volume 6
Supplement 1, 2011: Proceedings of the 10th European Congress on
Telepathology and 4th International Congress on Virtual Microscopy. The full
contents of the supplement are available online at
http://www.diagnosticpathology.org/supplements/6/S1.
Authors‘contributions
Both authors contributes equally.
Competing interests
The authors declare that they have no competing interests.
Published: 30 March 2011
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doi:10.1186/1746-1596-6-S1-S5
Cite this article as: Brazdziute and Laurinavicius: Digital pathology
evaluation of complement C4d component deposition in the kidney
allograft biopsies is a useful tool to improve reproducibility of the
scoring. Diagnostic Pathology 2011 6(Suppl 1):S5.
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