Evidence map›Paper›PMID 36268058›Full record

ArticleJournal of pathology informatics2022

Accuracy of whole slide image based image analysis is adversely affected by preanalytical factors such as stained tissue slide and paraffin block age.

Nada Shaker, Ruhani Sardana, Satoshi Hamasaki, David G Nohle, Leona W Ayers, Anil V Parwani

Abstract read
In one paragraph

Article in Journal of pathology informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Review
  2. Quality Management System in Clinical Digital Pathology Operations at a Tertiary Cancer Center.Laboratory investigation; a journal of technical methods and pathology · 2023
    Article
  3. Article
  4. Review
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.

Nada ShakerDepartment of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
Ruhani SardanaDepartment of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
Satoshi HamasakiDepartment of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
David G NohleDepartment of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
Leona W AyersDepartment of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
Anil V ParwaniDepartment of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, USA.

Funding

The Cooperative Human Tissue Network Midwestern Division (CHTN MWD)UM1CA239749 · NCI · OHIO STATE UNIVERSITY · PI Anil V Parwani · 2019 to 2026
$6.1M
NCI NIH HHS UM1 CA239749
6 · The paper itself

Abstract

Background: Personalized medicine and accurate quantification of tumor and biomarker expression have become the cornerstone of cancer diagnostics. This requires Quality Control (QC) of research tissue samples to confirm adequate targeted tumor tissue sampling. Digitalization of stained tissue slides offer a precious way to archive, preserve, and retrieve necessary information when needed. This study is aimed to assess the most significant pre-analytic and analytic factors that might contribute to the efficacy of obtaining accurate whole slide images (WSIs) interpretation. Various studies are needed to identifysuch factors to allow for appropriate AI application and adequate tumor area/percentage quantification. Methods: Hematoxylene and Eosine (H&E) satined WSIs collected from tissue specimens provided by the Cooperative Human Tissue Network (CHTN) Midwestern Division (CHTNMWD) were analyzed. Tissue specimens were processed, fixed, stained, and scanned contemporaneously (within 1 month). Two cohorts of malignant, colorectal cancer, 20X WSI (ScanscopeXT, Leica Biosystems, Illinois), were assembled. The study identified a "recent cohort" that included 76 WSIs created on 2018 or later. "Aged cohort" included 73 WSIs from specimens procured in the period of (2012-2014). Twenty recent WSIs of adenocarcinoma cases were used to construct WSIs analysis algorithms (VIS, Visiopharm A/S, Denmark) using machine learning to produce morphometric maps and calculate tissue and tumor areas. Results: Algorithmic analysis of 69 WSIs from rescanned aged slides vs. that of contemporaneous WSIs concluded 18 (28%) similar finding in tumor areas (within 10%), 56 (82%) had identicaltissue areas, and 54 (79%) had similar tumor percentages. Conclusion: WSIs of aged H&E slides and stained paraffin block re-cuts produce different tumor quantification compared to those of original scanned sslides most likely due to pre-analytical factors. The difference in tumor area detected between original and rescanned WSIs trended upward in the period between 2012 and 2014. Less tumor area was detected as the slides age. Recut and H&E-stained tissues from stored paraffin blocks may detect more tumor due to excess eosinophilia. These results highlights the value of documenting archives of H&E WSIs collected at the procurement time. Such images provide a superior archive over glass slides and Formalin-Fixed Paraffin-Embedded (FFPE) blocks and contribute betterg to WSIs analysis application.

Indexed as

AI algorithmOverall tumor percentageSlide ageTumor area identificationWhole slide images

Identifiers

PMID36268058
PMCPMC9577058

What OpenQuestion holds

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Registered trials

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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.