The digital revolution in veterinary pathology.

computerized digital pathology machine learning telediagnosis veterinary pathology whole slide images

Journal

Journal of comparative pathology
ISSN: 1532-3129
Titre abrégé: J Comp Pathol
Pays: England
ID NLM: 0102444

Informations de publication

Date de publication:
05 Sep 2024
Historique:
received: 22 03 2024
revised: 14 06 2024
accepted: 01 08 2024
medline: 7 9 2024
pubmed: 7 9 2024
entrez: 6 9 2024
Statut: aheadofprint

Résumé

For the past two centuries, the use of traditional light microscopy to examine tissues to make diagnoses has remained relatively unchanged. While the fundamental concept of tissue slide analysis has stayed the same, our interaction with the microscope is undergoing significant changes. Digital pathology (DP) has gained momentum in veterinary science and is on the verge of becoming a vital tool in diagnostics, research and education. Many diagnostic laboratories have incorporated DP as a critical part of their workflows. Innovations in DP and whole slide image technology have made telediagnosis (the process of transmitting digital clinical data using telecommunication networks for distant diagnosis) more accessible, leading to improved patient care through streamlining of workflows and greater accessibility of second opinions. The integration of machine learning and artificial intelligence and human-in-the-loop protocols for DP workflows will further the development of computer-aided diagnosis and prognostic tools. Despite its present weaknesses, DP will progressively aid veterinary clinicians and pathologists in delivering more accurate and reliable diagnoses. Consistent incorporation of DP frontline advancements into routine veterinary diagnostic pipelines will assist in improving current tools and help prepare pathologists for the progression of digitalization in the field.

Identifiants

pubmed: 39241697
pii: S0021-9975(24)00288-3
doi: 10.1016/j.jcpa.2024.08.001
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

19-31

Informations de copyright

Crown Copyright © 2024. Published by Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interests KA's PhD is supported by IDEXX Laboratories Ltd in conjunction with the BBSRC. SLC is an employee of IDEXX Laboratories Ltd. JW declared no conflicts of interest in relation to the research, authorship or publication of this article.

Auteurs

Kenneth Ancheta (K)

The Royal Veterinary College, Hawkshead Campus, Hawkshead Lane, Hatfield, Hertfordshire AL9 7TA, UK.

Sophie Le Calvez (S)

IDEXX Laboratories Ltd, Grange House, Sandbeck Way, Wetherby, Yorkshire LS22 7DN, UK.

Jonathan Williams (J)

The Royal Veterinary College, Hawkshead Campus, Hawkshead Lane, Hatfield, Hertfordshire AL9 7TA, UK. Electronic address: jonwilliams@rvc.ac.uk.

Classifications MeSH