Evidence map›Paper›PMID 22527018›Full record

ArticleVirchows Archiv : an international journal of pathology2012

An improved image analysis method for cell counting lends credibility to the prognostic significance of T cells in colorectal cancer.

Juha P Väyrynen, Juha O Vornanen, Sara Sajanti, Jan P Böhm, Anne Tuomisto, Markus J Mäkinen

Abstract read
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In one paragraph

Article in Virchows Archiv : an international journal of pathology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

52 citing papers in PubMed, 89 citations in OpenAlex.

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  14. Computer Vision in the Operating Room: Opportunities and Caveats.IEEE transactions on medical robotics and bionics · 2021
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  19. Evolution of ischemia and neovascularization in a murine model of full thickness human wound healing.Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society · 2020
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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

6 authors at 2 institutions in 1 country.

Juha P VäyrynenDepartment of Pathology, University of Oulu, POB 5000, 90014 Oulu, Finland.
Juha O Vornanen
Sara Sajanti
Jan P Böhm
Anne Tuomisto
Markus J Mäkinen
University of Oulu · FICentral Finland Health Care District · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Numerous immunohistochemically detectable proteins, such as immune cell surface (CD) proteins, vascular endothelial growth factor, and matrix metalloproteinases, have been proposed as potential prognostic markers in colorectal cancer (CRC) and other malignancies. However, the lack of reproducibility has been a major problem in validating the clinical use of such markers, and this has been attributed to insufficiently robust methods used in immunohistochemical staining or its assessment. In this study, we assessed how computer-assisted image analysis might contribute to the reliable assessment of positive area percentage and immune cell density in CRC specimens, and subsequently, we applied the computer-assisted cell counting method in assessing the prognostic value of T cell infiltration in CRC. The computer-assisted analysis methods were based on separating hematoxylin and diaminobenzidine color layers and then applying a brightness threshold using open source image analysis software ImageJ. We found that computer-based analysis results in a more reproducible assessment of the immune positive area percentage than visual semiquantitative estimation. Computer-assisted immune cell counting was rapid to perform and accurate (Pearson r > 0.96 with exact manual cell counts). Moreover, the computer-assisted determination of peritumoral and stromal T cell density had independent prognostic value. Our results suggest that computer-assisted image analysis, utilizing freely available image analysis software, provides a valuable alternative to semiquantitative assessment of immunohistochemical results in cancer research, as well as in clinical practice. The advantages of using computer-assisted analysis include objectivity, accuracy, reproducibility, and time efficiency. This study supports the prognostic value of assessing T cell infiltration in CRC.

Indexed as

AgedCell CountColorectal NeoplasmsFemaleHumansImage Interpretation, Computer-AssistedImmunohistochemistryMaleNeoplasm GradingNeoplasm StagingPrognosisReproducibility of ResultsSoftwareT-Lymphocytes

Identifiers

PMID22527018
OpenAlexW2079641633

What OpenQuestion holds

Textmetadata
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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.