Evidence map›Paper›PMID 31321298›Full record

ArticleAcademic pathology

Agreement in Histological Assessment of Mitotic Activity Between Microscopy and Digital Whole Slide Images Informs Conversion for Clinical Diagnosis.

Bih-Rong Wei, Charles H Halsey, Shelley B Hoover, Munish Puri, Howard H Yang, Brandon D Gallas, Maxwell P Lee, Weijie Chen, Amy C Durham, Jennifer E Dwyer and 14 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Academic pathology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Defining the area of mitoses counting in invasive breast cancer using whole slide image.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2022
    Article
  6. Article
  7. Article
  8. (Re) Defining the High-Power Field for Digital Pathology.Journal of pathology informatics · 2020
    Article
  9. Article
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

24 authors.

Bih-Rong WeiLaboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Charles H HalseyLaboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Shelley B HooverLaboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Munish PuriLaboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Howard H YangLaboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Brandon D GallasDivision of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA.ORCID https://orcid.org/0000-0001-7332-1620
Maxwell P LeeLaboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Weijie ChenDivision of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA.
Amy C DurhamDepartment of Pathobiology, University of Pennsylvania, Philadelphia, PA, USA.
Jennifer E DwyerLaboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Melissa D SánchezDepartment of Pathobiology, University of Pennsylvania, Philadelphia, PA, USA.
Ryan P TraslavinaSection of Infections of the Nervous System, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
Chad FrankDepartment of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, USA.
Charles BradleyDepartment of Pathobiology, University of Pennsylvania, Philadelphia, PA, USA.
Lawrence D McGillAnimal Reference Pathology, Salt Lake City, UT, USA.
D Glen EsplinAnimal Reference Pathology, Salt Lake City, UT, USA.
Paula A SchafferDepartment of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, USA.
Sarah D CramerCancer and Inflammation Program, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
L Tiffany LyleWomen's Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Jessica BeckLaboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Elizabeth BuzaDepartment of Pathobiology, University of Pennsylvania, Philadelphia, PA, USA.
Qi GongDivision of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA.
Stephen M HewittLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
R Mark SimpsonLaboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.ORCID https://orcid.org/0000-0001-8852-1297

Funding

Integrated analyses of genetics, epigenetics, and gene expressionZIHBC011703 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI LEE, MAXWELL · 2016 to 2025
$10.9M
Comparative Biomedical Scientist Training ProgramZ01BC010931 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI SIMPSON, ROBERT · 2008 to 2008
$560k
Intramural NIH HHS Z01 BC010931
6 · The paper itself

Abstract

Validating digital pathology as substitute for conventional microscopy in diagnosis remains a priority to assure effectiveness. Intermodality concordance studies typically focus on achieving the same diagnosis by digital display of whole slide images and conventional microscopy. Assessment of discrete histological features in whole slide images, such as mitotic figures, has not been thoroughly evaluated in diagnostic practice. To further gauge the interchangeability of conventional microscopy with digital display for primary diagnosis, 12 pathologists examined 113 canine naturally occurring mucosal melanomas exhibiting a wide range of mitotic activity. Design reflected diverse diagnostic settings and investigated independent location, interpretation, and enumeration of mitotic figures. Intermodality agreement was assessed employing conventional microscopy (CM40×), and whole slide image specimens scanned at 20× (WSI20×) and at 40× (WSI40×) objective magnifications. An aggregate 1647 mitotic figure count observations were available from conventional microscopy and whole slide images for comparison. The intraobserver concordance rate of paired observations was 0.785 to 0.801; interobserver rate was 0.784 to 0.794. Correlation coefficients between the 2 digital modes, and as compared to conventional microscopy, were similar and suggest noninferiority among modalities, including whole slide image acquired at lower 20× resolution. As mitotic figure counts serve for prognostic grading of several tumor types, including melanoma, 6 of 8 pathologists retrospectively predicted survival prognosis using whole slide images, compared to 9 of 10 by conventional microscopy, a first evaluation of whole slide image for mitotic figure prognostic grading. This study demonstrated agreement of replicate reads obtained across conventional microscopy and whole slide images. Hence, quantifying mitotic figures served as surrogate histological feature with which to further credential the interchangeability of whole slide images for primary diagnosis.

Indexed as

cancer gradingdigital pathologyinformaticsprognosisreproducibility studytechnology adoptiontrainingvalidation

Identifiers

PMID31321298
PMCPMC6628521

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.