Artificial intelligence-based algorithms for the diagnosis of prostate cancer: A systematic review.
Am J Clin Pathol
; 161(6): 526-534, 2024 Jun 03.
Article
em En
| MEDLINE
| ID: mdl-38381582
ABSTRACT
OBJECTIVES:
The high incidence of prostate cancer causes prostatic samples to significantly affect pathology laboratories workflow and turnaround times (TATs). Whole-slide imaging (WSI) and artificial intelligence (AI) have both gained approval for primary diagnosis in prostate pathology, providing physicians with novel tools for their daily routine.METHODS:
A systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was carried out in electronic databases to gather the available evidence on the application of AI-based algorithms to prostate cancer.RESULTS:
Of 6290 articles, 80 were included, mostly (59%) dealing with biopsy specimens. Glass slides were digitized to WSI in most studies (89%), roughly two-thirds of which (66%) exploited convolutional neural networks for computational analysis. The algorithms achieved good to excellent results about cancer detection and grading, along with significantly reduced TATs. Furthermore, several studies showed a relevant correlation between AI-identified histologic features and prognostic predictive variables such as biochemical recurrence, extraprostatic extension, perineural invasion, and disease-free survival.CONCLUSIONS:
The published evidence suggests that AI can be reliably used for prostate cancer detection and grading, assisting pathologists in the time-consuming screening of slides. Further technologic improvement would help widening AI's adoption in prostate pathology, as well as expanding its prognostic predictive potential.Palavras-chave
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Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Próstata
/
Algoritmos
/
Inteligência Artificial
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article