Pathologist Computer-Aided Diagnostic Scoring of Tumor Cell Fraction: A Swiss National Study.

artificial intelligence computer-aided diagnostic tool digital pathology interobserver variability pathology tumor cell fraction

Journal

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
ISSN: 1530-0285
Titre abrégé: Mod Pathol
Pays: United States
ID NLM: 8806605

Informations de publication

Date de publication:
22 Sep 2023
Historique:
received: 31 05 2023
revised: 25 08 2023
accepted: 15 09 2023
pubmed: 25 9 2023
medline: 25 9 2023
entrez: 24 9 2023
Statut: aheadofprint

Résumé

Tumor cell fraction (TCF) estimation is a common clinical task with well-established large interobserver variability. It thus provides an ideal test bed to evaluate potential impacts of employing a tumor cell fraction computer-aided diagnostic (TCFCAD) tool to support pathologists' evaluation. During a National Slide Seminar event, pathologists (n = 69) were asked to visually estimate TCF in 10 regions of interest (ROIs) from hematoxylin and eosin colorectal cancer images intentionally curated for diverse tissue compositions, cellularity, and stain intensities. Next, they re-evaluated the same ROIs while being provided a TCFCAD-created overlay highlighting predicted tumor vs nontumor cells, together with the corresponding TCF percentage. Participants also reported confidence levels in their assessments using a 5-tier scale, indicating no confidence to high confidence, respectively. The TCF ground truth (GT) was defined by manual cell-counting by experts. When assisted, interobserver variability significantly decreased, showing estimates converging to the GT. This improvement remained even when TCFCAD predictions deviated slightly from the GT. The standard deviation (SD) of the estimated TCF to the GT across ROIs was 9.9% vs 5.8% with TCFCAD (P < .0001). The intraclass correlation coefficient increased from 0.8 to 0.93 (95% CI, 0.65-0.93 vs 0.86-0.98), and pathologists stated feeling more confident when aided (3.67 ± 0.81 vs 4.17 ± 0.82 with the computer-aided diagnostic [CAD] tool). TCFCAD estimation support demonstrated improved scoring accuracy, interpathologist agreement, and scoring confidence. Interestingly, pathologists also expressed more willingness to use such a CAD tool at the end of the survey, highlighting the importance of training/education to increase adoption of CAD systems.

Identifiants

pubmed: 37742926
pii: S0893-3952(23)00240-5
doi: 10.1016/j.modpat.2023.100335
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

100335

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.

Auteurs

Ana Leni Frei (AL)

Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland. Electronic address: ana.frei@unibe.ch.

Raphaël Oberson (R)

Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.

Elias Baumann (E)

Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.

Aurel Perren (A)

Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.

Rainer Grobholz (R)

Medical Faculty University of Zurich, Institute of Pathology, Cantonal Hospital Aarau, Aarau, Switzerland.

Alessandro Lugli (A)

Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.

Heather Dawson (H)

Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.

Christian Abbet (C)

Signal Processing Laboratory 5, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.

Ibai Lertxundi (I)

Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.

Stefan Reinhard (S)

Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.

Aart Mookhoek (A)

Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.

Johann Feichtinger (J)

Labor Dr. Ulm GmbH, Wien, Austria.

Rossella Sarro (R)

Istituto Cantonale di Patologia, Ente ospedaliero cantonale (EOC), Locarno, Switzerland.

Gallus Gadient (G)

Institute of Pathology, Medica, Zürich, Switzerland.

Corina Dommann-Scherrer (C)

Institute of Pathology, Cantonal Hospital Winterthur, Winterthur, Switzerland.

Jessica Barizzi (J)

Istituto Cantonale di Patologia, Ente ospedaliero cantonale (EOC), Locarno, Switzerland.

Sabina Berezowska (S)

Institute of Pathology, Lausanne University Hospital, Lausanne, Switzerland.

Katharina Glatz (K)

Institut of Pathology, University Hospital Basel, Basel, Switzerland.

Susanne Dertinger (S)

Institute of Pathology, Landeskrankenhaus Feldkirch, Feldkirch, Austria.

Yara Banz (Y)

Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.

Rene Schoenegg (R)

Institute of Pathology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland.

Laura Rubbia-Brandt (L)

Department of Pathology and Immunology, Geneva University Hospital, Genève, Switzerland.

Achim Fleischmann (A)

Institute of Pathology, Cantonal Hospital Thurgau, Münsterlingen, Switzerland.

Guenter Saile (G)

Labor team w AG, St. Gallen, Switzerland.

Pierre Mainil-Varlet (P)

Unilabs Bern, Bern, Switzerland.

Ruggero Biral (R)

Pathologie Länggasse, Ittigen, Switzerland.

Luca Giudici (L)

Istituto Cantonale di Patologia, Ente ospedaliero cantonale (EOC), Locarno, Switzerland.

Alex Soltermann (A)

Pathologie Länggasse, Ittigen, Switzerland.

Audrey Baur Chaubert (AB)

FMH Pathology, Pathology Department of SYNLAB Switzerland SA, Lausanne, Switzerland.

Sylvia Stadlmann (S)

Institute of Pathology, Cantonal Hospital Baden, Baden, Switzerland.

Joachim Diebold (J)

Institute of Pathology, Cantonal Hospital Luzern, Luzern, Switzerland.

Kristof Egervari (K)

Department of Pathology and Immunology, Geneva University Hospital, Genève, Switzerland.

Charles Bénière (C)

Aurigen, Centre de Pathologie, Lausanne Switzerland.

Francesca Saro (F)

Institute of Pathology and Molecular Pathology, University Hospital Zürich, Zürich, Switzerland.

Andrew Janowczyk (A)

Department of Biomedical Engineering, Emory University, Atlanta, Georgia; Department of Oncology, Division of Precision Oncology, University Hospital of Geneva, Geneva, Switzerland; Department of Clinical Pathology, Division of Clinical Pathology, University Hospital of Geneva, Geneva, Switzerland.

Inti Zlobec (I)

Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland. Electronic address: inti.zlobec@unibe.ch.

Classifications MeSH