Ki67 proliferation index in medullary thyroid carcinoma: a comparative study of multiple counting methods and validation of image analysis and deep learning platforms.
Ki67 proliferation index
deep learning
grade
machine learning
medullary thyroid carcinoma
Journal
Histopathology
ISSN: 1365-2559
Titre abrégé: Histopathology
Pays: England
ID NLM: 7704136
Informations de publication
Date de publication:
Dec 2023
Dec 2023
Historique:
revised:
16
08
2023
received:
21
06
2023
accepted:
18
08
2023
medline:
7
11
2023
pubmed:
14
9
2023
entrez:
14
9
2023
Statut:
ppublish
Résumé
The International Medullary Thyroid Carcinoma Grading System, introduced in 2022, mandates evaluation of the Ki67 proliferation index to assign a histological grade for medullary thyroid carcinoma. However, manual counting remains a tedious and time-consuming task. We aimed to evaluate the performance of three other counting techniques for the Ki67 index, eyeballing by a trained experienced investigator, a machine learning-based deep learning algorithm (DeepLIIF) and an image analysis software with internal thresholding compared to the gold standard manual counting in a large cohort of 260 primarily resected medullary thyroid carcinoma. The Ki67 proliferation index generated by all three methods correlate near-perfectly with the manual Ki67 index, with kappa values ranging from 0.884 to 0.979 and interclass correlation coefficients ranging from 0.969 to 0.983. Discrepant Ki67 results were only observed in cases with borderline manual Ki67 readings, ranging from 3 to 7%. Medullary thyroid carcinomas with a high Ki67 index (≥ 5%) determined using any of the four methods were associated with significantly decreased disease-specific survival and distant metastasis-free survival. We herein validate a machine learning-based deep-learning platform and an image analysis software with internal thresholding to generate accurate automatic Ki67 proliferation indices in medullary thyroid carcinoma. Manual Ki67 count remains useful when facing a tumour with a borderline Ki67 proliferation index of 3-7%. In daily practice, validation of alternative evaluation methods for the Ki67 index in MTC is required prior to implementation.
Substances chimiques
Ki-67 Antigen
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
981-988Subventions
Organisme : Cancer Center Support Grant of the National Institutes of Health/National Cancer Institute
ID : P30CA008748
Organisme : Italian Government Ministry of Health,
ID : RF-2011-02350857
Organisme : Cancer Tissue and Pathology, Emory Integrated Genomics Core (EIGC)
Organisme : Emory Integrated Computational Core (EICC),
Organisme : Winship Cancer Institute of Emory University and NIH/NCI
ID : P30CA138292
Organisme : National Center for Georgia Clinical and Translational Science Alliance of the National Institutes of Health
ID : UL1TR002378
Informations de copyright
© 2023 John Wiley & Sons Ltd.
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