Advantages of manual and automatic computer-aided compared to traditional histopathological diagnosis of melanoma: A pilot study.
Computer-aided diagnosis
Diagnostic variability, histopathology
Image analysis, melanocytes, melanoma
Skin cancer
Journal
Pathology, research and practice
ISSN: 1618-0631
Titre abrégé: Pathol Res Pract
Pays: Germany
ID NLM: 7806109
Informations de publication
Date de publication:
Sep 2022
Sep 2022
Historique:
received:
04
05
2022
revised:
04
07
2022
accepted:
07
07
2022
pubmed:
24
7
2022
medline:
26
10
2022
entrez:
23
7
2022
Statut:
ppublish
Résumé
Cutaneous malignant melanoma (CMM) accounts for the highest mortality rate among all skin cancers. Traditional histopathologic diagnosis may be limited by the pathologists' subjectivity. Second-opinion strategies and multidisciplinary consultations are usually performed to overcome this issue. An available solution in the future could be the use of automated solutions based on a computational algorithm that could help the pathologist in everyday practice. The aim of this pilot study was to investigate the potential diagnostic aid of a machine-based algorithm in the histopathologic diagnosis of CMM. We retrospectively examined excisional biopsies of 50 CMM and 20 benign congenital compound nevi. Hematoxylin and eosin (H&E) stained WSI were reviewed independently by two expert dermatopathologists. A fully automated pipeline for WSI processing to support the estimation and prioritization of the melanoma areas was developed. The spatial distribution of the nuclei in the sample provided a multi-scale overview of the tumor. A global overview of the lesion's silhouette was achieved and, by increasing the magnification, the topological distribution of the nuclei and the most informative areas of interest for the CMM diagnosis were identified and highlighted. These silhouettes allow the histopathologist to discriminate between nevus and CMM with an accuracy of 96% without any extra information. In this study we proposed an easy-to-use model that produces segmentations of CMM silhouettes at fine detail level.
Sections du résumé
BACKGROUND
BACKGROUND
Cutaneous malignant melanoma (CMM) accounts for the highest mortality rate among all skin cancers. Traditional histopathologic diagnosis may be limited by the pathologists' subjectivity. Second-opinion strategies and multidisciplinary consultations are usually performed to overcome this issue. An available solution in the future could be the use of automated solutions based on a computational algorithm that could help the pathologist in everyday practice. The aim of this pilot study was to investigate the potential diagnostic aid of a machine-based algorithm in the histopathologic diagnosis of CMM.
METHODS
METHODS
We retrospectively examined excisional biopsies of 50 CMM and 20 benign congenital compound nevi. Hematoxylin and eosin (H&E) stained WSI were reviewed independently by two expert dermatopathologists. A fully automated pipeline for WSI processing to support the estimation and prioritization of the melanoma areas was developed.
RESULTS
RESULTS
The spatial distribution of the nuclei in the sample provided a multi-scale overview of the tumor. A global overview of the lesion's silhouette was achieved and, by increasing the magnification, the topological distribution of the nuclei and the most informative areas of interest for the CMM diagnosis were identified and highlighted. These silhouettes allow the histopathologist to discriminate between nevus and CMM with an accuracy of 96% without any extra information.
CONCLUSION
CONCLUSIONS
In this study we proposed an easy-to-use model that produces segmentations of CMM silhouettes at fine detail level.
Identifiants
pubmed: 35870238
pii: S0344-0338(22)00258-8
doi: 10.1016/j.prp.2022.154014
pii:
doi:
Substances chimiques
Eosine Yellowish-(YS)
TDQ283MPCW
Hematoxylin
YKM8PY2Z55
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
154014Informations de copyright
Copyright © 2022 The Authors. Published by Elsevier GmbH.. All rights reserved.
Déclaration de conflit d'intérêts
Conflict of interest statement The authors have no conflict of interest to declare.