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Computer-assisted stereology and automated image analysis for quantification of tumor infiltrating lymphocytes in colon cancer

BACKGROUND: Precise prognostic and predictive variables allowing improved post-operative treatment stratification are missing in patients treated for stage II colon cancer (CC). Investigation of tumor infiltrating lymphocytes (TILs) may be rewarding, but the lack of a standardized analytic technique...

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Autores principales: Eriksen, Ann C., Andersen, Johnnie B., Kristensson, Martin, dePont Christensen, René, Hansen, Torben F., Kjær-Frifeldt, Sanne, Sørensen, Flemming B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5575870/
https://www.ncbi.nlm.nih.gov/pubmed/28851404
http://dx.doi.org/10.1186/s13000-017-0653-0
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author Eriksen, Ann C.
Andersen, Johnnie B.
Kristensson, Martin
dePont Christensen, René
Hansen, Torben F.
Kjær-Frifeldt, Sanne
Sørensen, Flemming B.
author_facet Eriksen, Ann C.
Andersen, Johnnie B.
Kristensson, Martin
dePont Christensen, René
Hansen, Torben F.
Kjær-Frifeldt, Sanne
Sørensen, Flemming B.
author_sort Eriksen, Ann C.
collection PubMed
description BACKGROUND: Precise prognostic and predictive variables allowing improved post-operative treatment stratification are missing in patients treated for stage II colon cancer (CC). Investigation of tumor infiltrating lymphocytes (TILs) may be rewarding, but the lack of a standardized analytic technique is a major concern. Manual stereological counting is considered the gold standard, but digital pathology with image analysis is preferred due to time efficiency. The purpose of this study was to compare manual stereological estimates of TILs with automatic counts obtained by image analysis, and at the same time investigate the heterogeneity of TILs. METHODS: From 43 patients treated for stage II CC in 2002 three paraffin embedded, tumor containing tissue blocks were selected one of them representing the deepest invasive tumor front. Serial sections from each of the 129 blocks were immunohistochemically stained for CD3 and CD8, and the slides were scanned. Stereological estimates of the numerical density and area fraction of TILs were obtained using the computer-assisted newCAST stereology system. For the image analysis approach an app-based algorithm was developed using Visiopharm Integrator System software. For both methods the tumor areas of interest (invasive front and central area) were manually delineated by the observer. RESULTS: Based on all sections, the Spearman’s correlation coefficients for density estimates varied from 0.9457 to 0.9638 (p < 0.0001), whereas the coefficients for area fraction estimates ranged from 0.9400 to 0.9603 (P < 0.0001). Regarding heterogeneity, intra-class correlation coefficients (ICC) for CD3+ TILs varied from 0.615 to 0.746 in the central area, and from 0.686 to 0.746 in the invasive area. ICC for CD8+ TILs varied from 0.724 to 0.775 in the central area, and from 0.746 to 0.765 in the invasive area. CONCLUSIONS: Exact objective and time efficient estimates of numerical densities and area fractions of CD3+ and CD8+ TILs in stage II colon cancer can be obtained by image analysis and are highly correlated to the corresponding estimates obtained by the gold standard based on stereology. Since the intra-tumoral heterogeneity was low, this method may be recommended for quantifying TILs in only one histological section representing the deepest invasive tumor front. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13000-017-0653-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-55758702017-08-30 Computer-assisted stereology and automated image analysis for quantification of tumor infiltrating lymphocytes in colon cancer Eriksen, Ann C. Andersen, Johnnie B. Kristensson, Martin dePont Christensen, René Hansen, Torben F. Kjær-Frifeldt, Sanne Sørensen, Flemming B. Diagn Pathol Methodology BACKGROUND: Precise prognostic and predictive variables allowing improved post-operative treatment stratification are missing in patients treated for stage II colon cancer (CC). Investigation of tumor infiltrating lymphocytes (TILs) may be rewarding, but the lack of a standardized analytic technique is a major concern. Manual stereological counting is considered the gold standard, but digital pathology with image analysis is preferred due to time efficiency. The purpose of this study was to compare manual stereological estimates of TILs with automatic counts obtained by image analysis, and at the same time investigate the heterogeneity of TILs. METHODS: From 43 patients treated for stage II CC in 2002 three paraffin embedded, tumor containing tissue blocks were selected one of them representing the deepest invasive tumor front. Serial sections from each of the 129 blocks were immunohistochemically stained for CD3 and CD8, and the slides were scanned. Stereological estimates of the numerical density and area fraction of TILs were obtained using the computer-assisted newCAST stereology system. For the image analysis approach an app-based algorithm was developed using Visiopharm Integrator System software. For both methods the tumor areas of interest (invasive front and central area) were manually delineated by the observer. RESULTS: Based on all sections, the Spearman’s correlation coefficients for density estimates varied from 0.9457 to 0.9638 (p < 0.0001), whereas the coefficients for area fraction estimates ranged from 0.9400 to 0.9603 (P < 0.0001). Regarding heterogeneity, intra-class correlation coefficients (ICC) for CD3+ TILs varied from 0.615 to 0.746 in the central area, and from 0.686 to 0.746 in the invasive area. ICC for CD8+ TILs varied from 0.724 to 0.775 in the central area, and from 0.746 to 0.765 in the invasive area. CONCLUSIONS: Exact objective and time efficient estimates of numerical densities and area fractions of CD3+ and CD8+ TILs in stage II colon cancer can be obtained by image analysis and are highly correlated to the corresponding estimates obtained by the gold standard based on stereology. Since the intra-tumoral heterogeneity was low, this method may be recommended for quantifying TILs in only one histological section representing the deepest invasive tumor front. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13000-017-0653-0) contains supplementary material, which is available to authorized users. BioMed Central 2017-08-29 /pmc/articles/PMC5575870/ /pubmed/28851404 http://dx.doi.org/10.1186/s13000-017-0653-0 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology
Eriksen, Ann C.
Andersen, Johnnie B.
Kristensson, Martin
dePont Christensen, René
Hansen, Torben F.
Kjær-Frifeldt, Sanne
Sørensen, Flemming B.
Computer-assisted stereology and automated image analysis for quantification of tumor infiltrating lymphocytes in colon cancer
title Computer-assisted stereology and automated image analysis for quantification of tumor infiltrating lymphocytes in colon cancer
title_full Computer-assisted stereology and automated image analysis for quantification of tumor infiltrating lymphocytes in colon cancer
title_fullStr Computer-assisted stereology and automated image analysis for quantification of tumor infiltrating lymphocytes in colon cancer
title_full_unstemmed Computer-assisted stereology and automated image analysis for quantification of tumor infiltrating lymphocytes in colon cancer
title_short Computer-assisted stereology and automated image analysis for quantification of tumor infiltrating lymphocytes in colon cancer
title_sort computer-assisted stereology and automated image analysis for quantification of tumor infiltrating lymphocytes in colon cancer
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5575870/
https://www.ncbi.nlm.nih.gov/pubmed/28851404
http://dx.doi.org/10.1186/s13000-017-0653-0
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