Assessment of a computerized quantitative quality control tool for whole slide images of kidney biopsies.

NEPTUNE batch effects computational pathology computer vision digital pathology inter-reader variability kidney biopsies machine learning quality control whole-slide image

Journal

The Journal of pathology
ISSN: 1096-9896
Titre abrégé: J Pathol
Pays: England
ID NLM: 0204634

Informations de publication

Date de publication:
03 2021
Historique:
received: 10 08 2020
revised: 30 10 2020
accepted: 11 11 2020
pubmed: 17 11 2020
medline: 29 5 2021
entrez: 16 11 2020
Statut: ppublish

Résumé

Inconsistencies in the preparation of histology slides and whole-slide images (WSIs) may lead to challenges with subsequent image analysis and machine learning approaches for interrogating the WSI. These variabilities are especially pronounced in multicenter cohorts, where batch effects (i.e. systematic technical artifacts unrelated to biological variability) may introduce biases to machine learning algorithms. To date, manual quality control (QC) has been the de facto standard for dataset curation, but remains highly subjective and is too laborious in light of the increasing scale of tissue slide digitization efforts. This study aimed to evaluate a computer-aided QC pipeline for facilitating a reproducible QC process of WSI datasets. An open source tool, HistoQC, was employed to identify image artifacts and compute quantitative metrics describing visual attributes of WSIs to the Nephrotic Syndrome Study Network (NEPTUNE) digital pathology repository. A comparison in inter-reader concordance between HistoQC aided and unaided curation was performed to quantify improvements in curation reproducibility. HistoQC metrics were additionally employed to quantify the presence of batch effects within NEPTUNE WSIs. Of the 1814 WSIs (458 H&E, 470 PAS, 438 silver, 448 trichrome) from n = 512 cases considered in this study, approximately 9% (163) were identified as unsuitable for subsequent computational analysis. The concordance in the identification of these WSIs among computational pathologists rose from moderate (Gwet's AC1 range 0.43 to 0.59 across stains) to excellent (Gwet's AC1 range 0.79 to 0.93 across stains) agreement when aided by HistoQC. Furthermore, statistically significant batch effects (p < 0.001) in the NEPTUNE WSI dataset were discovered. Taken together, our findings strongly suggest that quantitative QC is a necessary step in the curation of digital pathology cohorts. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Identifiants

pubmed: 33197281
doi: 10.1002/path.5590
pmc: PMC8392148
mid: NIHMS1733690
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

268-278

Subventions

Organisme : NCI NIH HHS
ID : R01 CA216579
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01-DK-118431.
Pays : United States
Organisme : NCI NIH HHS
ID : R01CA208236-01A1
Pays : United States
Organisme : NIDDK NIH HHS
ID : U54 DK083912
Pays : United States
Organisme : NCRR NIH HHS
ID : C06 RR012463
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA220581-01A1
Pays : United States
Organisme : NCI NIH HHS
ID : U24 CA199374
Pays : United States
Organisme : NCI NIH HHS
ID : 1U01 CA239055-01
Pays : United States
Organisme : NIBIB NIH HHS
ID : R43 EB028736
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA239055
Pays : United States
Organisme : NIDDK NIH HHS
ID : T32 DK007470
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL151277
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA220581
Pays : United States
Organisme : NCI NIH HHS
ID : 1U24CA199374-01
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA202752
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA208236
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA248226
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA216579-01A1
Pays : United States
Organisme : National Institute for Biomedical Imaging and Bioengineering
ID : 1R43EB028736-01
Organisme : BLRD VA
ID : I01 BX004121
Pays : United States
Organisme : NCI NIH HHS
ID : 1U01 CA248226-01
Pays : United States
Organisme : NCI NIH HHS
ID : R01CA202752-01A1
Pays : United States
Organisme : Neptune Career Development Award
ID : 5T32DK747033
Organisme : NCRR NIH HHS
ID : 1 C06 RR12463-01
Pays : United States

Informations de copyright

© 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

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Auteurs

Yijiang Chen (Y)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.

Jarcy Zee (J)

Arbor Research Collaborative for Health, Ann Arbor, MI, USA.

Abigail Smith (A)

Arbor Research Collaborative for Health, Ann Arbor, MI, USA.

Catherine Jayapandian (C)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.

Jeffrey Hodgin (J)

Department of Pathology, University of Michigan, Ann Arbor, MI, USA.

David Howell (D)

Department of Pathology, Duke University, Durham, NC, USA.

Matthew Palmer (M)

Department of Pathology, University of Pennsylvania, Philadelphia, PA, USA.

David Thomas (D)

Department of Pathology, Duke University, Durham, NC, USA.
Nephrocor, Memphis, TN, USA.

Clarissa Cassol (C)

Renal Pathology Division, Arkana Laboratories, Little Rock, AK, USA.
Department of Pathology - Renal Pathology Division, Ohio State University Medical Center, Columbus, OH, USA.

Alton B Farris (AB)

Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, USA.

Kathryn Perkinson (K)

Department of Pathology, Duke University, Durham, NC, USA.

Anant Madabhushi (A)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Louis Stokes VA Medical Center, Cleveland, OH, USA.

Laura Barisoni (L)

Department of Pathology, Duke University, Durham, NC, USA.
Department of Medicine, Division of Nephrology, Duke University, Durham, NC, USA.

Andrew Janowczyk (A)

Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Precision Oncology Center, University of Lausanne, Lausanne, Switzerland.

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Classifications MeSH