Evidence map›Paper›PMID 28851404›Full record

ArticleDiagnostic pathology2017

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

Ann C Eriksen, Johnnie B Andersen, Martin Kristensson, René dePont Christensen, Torben F Hansen, Sanne Kjær-Frifeldt, Flemming B Sørensen

Open access · goldAbstract readComparative Study
In one paragraph

Article in Diagnostic pathology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.4field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Article
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  4. High-performance Data Management for Whole Slide Image Analysis in Digital Pathology.Proceedings of SPIE--the International Society for Optical Engineering · 2024
    Article
  5. Article
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  7. An Accelerated Pipeline for Multi-label Renal Pathology Image Segmentation at the Whole Slide Image Level.Proceedings of SPIE--the International Society for Optical Engineering · 2023
    Article
  8. Article
  9. Article
  10. Spatial Architecture and Arrangement of Tumor-Infiltrating Lymphocytes for Predicting Likelihood of Recurrence in Early-Stage Non-Small Cell Lung Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2019
    Article
  11. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Ann C EriksenDanish Colorectal Cancer Center South, Vejle Hospital, Vejle, Denmark. ann.christina.eriksen@rsyd.dk.
Johnnie B AndersenDepartment of Clinical Medicine, Stereological Research Laboratory, Aarhus University, Nørrebrogade 44, 10G, 8000, Aarhus C, Denmark.
Martin KristenssonVisiopharm A/S, Agern Allé 24, 2970, Hoersholm, Denmark.
René dePont ChristensenResearch Unit of General Practice, University of Southern Denmark, J.B. Winsløws Vej 9 A, 1st, 5000, Odense C, Denmark.
Torben F HansenDanish Colorectal Cancer Center South, Vejle Hospital, Vejle, Denmark.
Sanne Kjær-FrifeldtDanish Colorectal Cancer Center South, Vejle Hospital, Vejle, Denmark.
Flemming B SørensenDanish Colorectal Cancer Center South, Vejle Hospital, Vejle, Denmark.
Vejle Sygehus · DKAarhus University · DKUniversity of Southern Denmark · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrecise 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.

methodsFrom 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.

resultsBased 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.

conclusionsExact 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.

Indexed as

AgedCD3 ComplexCD8 AntigensColonic NeoplasmsHumansImage Processing, Computer-AssistedLymphocytes, Tumor-InfiltratingMiddle AgedNeoplasm StagingPrognosisCD3 ComplexCD8 AntigensColon cancerHeterogeneityImage analysisStereologyTumor infiltrating lymphocytes

Identifiers

PMID28851404
PMCPMC5575870
OpenAlexW2611149950

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.