Assessment of parathyroid gland cellularity by digital slide analysis.

Computer-assisted image analysis Hyperparathyroidism Light Microscopy Parathyroid Adenoma Parathyroidectomy Surgical Pathology

Journal

Annals of diagnostic pathology
ISSN: 1532-8198
Titre abrégé: Ann Diagn Pathol
Pays: United States
ID NLM: 9800503

Informations de publication

Date de publication:
Jun 2022
Historique:
received: 24 05 2021
revised: 01 01 2022
accepted: 25 01 2022
pubmed: 18 3 2022
medline: 24 5 2022
entrez: 17 3 2022
Statut: ppublish

Résumé

Computer-aided examination of digital tissue images has attracted attention in recent years. Application in the field of parathyroid pathology has not been studied previously. It holds a potential to assist in the examination of parathyroid gland adenoma or hyperplasia. To explore parathyroid cell detection of slide images by digital tissue analysis and compare the results to standard human processing. 47 incisional biopsies of healthy appearing parathyroid glands were evaluated for their cellularity level. First, by the standard examination using microscopy by three independent pathologists. We compared the mean cellularity grading of the pathologists to the output of a computerized cell detection software. A disagreement was found between the standard human cellularity grading and the digital analysis output. However, the digital analysis reaches a 94% specificity and 48% sensitivity to predict high cellularity (>60% parenchymal cells). Digital analysis of parathyroid tissue can be used as a tool for hypercellularity elimination, therefore assisting in the diagnosis of parathyroid cell hyperplasia. Additional studies using more advanced algorithms are necessary for further precision enhancement.

Sections du résumé

BACKGROUND BACKGROUND
Computer-aided examination of digital tissue images has attracted attention in recent years. Application in the field of parathyroid pathology has not been studied previously. It holds a potential to assist in the examination of parathyroid gland adenoma or hyperplasia.
OBJECTIVES OBJECTIVE
To explore parathyroid cell detection of slide images by digital tissue analysis and compare the results to standard human processing.
METHODS METHODS
47 incisional biopsies of healthy appearing parathyroid glands were evaluated for their cellularity level. First, by the standard examination using microscopy by three independent pathologists. We compared the mean cellularity grading of the pathologists to the output of a computerized cell detection software.
RESULTS RESULTS
A disagreement was found between the standard human cellularity grading and the digital analysis output. However, the digital analysis reaches a 94% specificity and 48% sensitivity to predict high cellularity (>60% parenchymal cells).
CONCLUSIONS CONCLUSIONS
Digital analysis of parathyroid tissue can be used as a tool for hypercellularity elimination, therefore assisting in the diagnosis of parathyroid cell hyperplasia. Additional studies using more advanced algorithms are necessary for further precision enhancement.

Identifiants

pubmed: 35299079
pii: S1092-9134(22)00009-0
doi: 10.1016/j.anndiagpath.2022.151907
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

151907

Informations de copyright

Copyright © 2022 Elsevier Inc. All rights reserved.

Auteurs

Rotem Sagiv (R)

Joyce & Irving Goldman Medical School, The Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.

Bertha Delgado (B)

Pathology Unit, Soroka University Medical Center, Beer-Sheva, Israel.

Oleg Lavon (O)

Pathology Unit, Soroka University Medical Center, Beer-Sheva, Israel.

Vladislav Osipov (V)

Pathology Unit, Soroka University Medical Center, Beer-Sheva, Israel.

Re'em Sade (R)

The Clinical Research Center of Soroka Medical Center, Beer-Sheva, Israel.

Sagi Shashar (S)

The Clinical Research Center of Soroka Medical Center, Beer-Sheva, Israel.

Ksenia M Yegodayev (KM)

The Shraga Segal Department of Microbiology, Immunology, and Genetics, The Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.

Moshe Elkabets (M)

The Shraga Segal Department of Microbiology, Immunology, and Genetics, The Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.

Ben-Zion Joshua (BZ)

Department of Otorhinolaryngology & Head and Neck Surgery, Barzilai, University Medical Center, Ashkelon, Israel. Electronic address: benzionj@gmail.com.

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Classifications MeSH