Evidence map›Paper›PMID 31238983›Full record

ArticleDiagnostic pathology2019

Validation of mitotic cell quantification via microscopy and multiple whole-slide scanners.

Kazuhiro Tabata, Naohiro Uraoka, Jamal Benhamida, Matthew G Hanna, Sahussapont Joseph Sirintrapun, Brandon D Gallas, Qi Gong, Rania G Aly, Katsura Emoto, Kant M Matsuda and 3 more

Abstract readValidation Study
In one paragraph

Article in Diagnostic pathology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
  8. Histology Image Viewer and Converter (HIVC): A High-Speed Freeware Software to View and Convert Whole Slide Histology Images.Computer methods in biomechanics and biomedical engineering. Imaging & visualization · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Counting mitoses: SI(ze) matters!Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2021
    Review
  14. Article
  15. Article
  16. (Re) Defining the High-Power Field for Digital Pathology.Journal of pathology informatics · 2020
    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

13 authors.

Kazuhiro TabataDepartment of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA. t-kaz@nagasaki-u.ac.jp.ORCID http://orcid.org/0000-0002-4524-4813
Naohiro UraokaDepartment of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Jamal BenhamidaDepartment of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Matthew G HannaDepartment of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Sahussapont Joseph SirintrapunDepartment of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Brandon D GallasCenter For Devices and Radiological Health, Office of Science and Engineering Laboratories, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD, 20993, USA.
Qi GongCenter For Devices and Radiological Health, Office of Science and Engineering Laboratories, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD, 20993, USA.
Rania G AlyDepartment of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Katsura EmotoDepartment of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Kant M MatsudaDepartment of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Meera R HameedDepartment of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
David S KlimstraDepartment of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Yukako YagiDepartment of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

backgroundThe establishment of whole-slide imaging (WSI) as a medical diagnostic device allows that pathologists may evaluate mitotic activity with this new technology. Furthermore, the image digitalization provides an opportunity to develop algorithms for automatic quantifications, ideally leading to improved reproducibility as compared to the naked eye examination by pathologists. In order to implement them effectively, accuracy of mitotic figure detection using WSI should be investigated. In this study, we aimed to measure pathologist performance in detecting mitotic figures (MFs) using multiple platforms (multiple scanners) and compare the results with those obtained using a brightfield microscope.

methodsFour slides of canine oral melanoma were prepared and digitized using 4 WSI scanners. In these slides, 40 regions of interest (ROIs) were demarcated, and five observers identified the MFs using different viewing modes: microscopy and WSI. We evaluated the inter- and intra-observer agreements between modes with Cohen's Kappa and determined "true" MFs with a consensus panel. We then assessed the accuracy (agreement with truth) using the average of sensitivity and specificity.

resultsIn the 40 ROIs, 155 candidate MFs were detected by five pathologists; 74 of them were determined to be true MFs. Inter- and intra-observer agreement was mostly "substantial" or greater (Kappa = 0.594-0.939). Accuracy was between 0.632 and 0.843 across all readers and modes. After averaging over readers for each modality, we found that mitosis detection accuracy for 3 of the 4 WSI scanners was significantly less than that of the microscope (p = 0.002, 0.012, and 0.001).

conclusionsThis study is the first to compare WSIs and microscopy in detecting MFs at the level of individual cells. Our results suggest that WSI can be used for mitotic cell detection and offers similar reproducibility to the microscope, with slightly less accuracy.

Indexed as

AnimalsDog DiseasesDogsImage Interpretation, Computer-AssistedMelanomaMicroscopyMitosisMouth NeoplasmsObserver VariationPathologistsReproducibility of ResultseeDAPMicroscopyMitotic cell quantificationMultiple whole slide scannerValidation studyWhole slide imaging

Identifiers

PMID31238983
PMCPMC6593538

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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.