التفاصيل البيبلوغرافية
| العنوان: |
Artificial intelligence–based algorithms for the diagnosis of prostate cancer: A systematic review |
| المؤلفون: |
Marletta, Stefano, Eccher, Albino, Martelli, Filippo Maria, Santonicco, Nicola, Girolami, Ilaria, Scarpa, Aldo, Pagni, Fabio, L’Imperio, Vincenzo, Pantanowitz, Liron, Gobbo, Stefano, Seminati, Davide, Dei Tos, Angelo Paolo, Parwani, Anil |
| المصدر: |
American Journal of Clinical Pathology ; ISSN 0002-9173 1943-7722 |
| بيانات النشر: |
Oxford University Press (OUP) |
| سنة النشر: |
2024 |
| الوصف: |
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. |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
English |
| DOI: |
10.1093/ajcp/aqad182 |
| DOI: |
10.1093/ajcp/aqad182/56729093/aqad182.pdf |
| الإتاحة: |
https://doi.org/10.1093/ajcp/aqad182Test |
| حقوق: |
https://academic.oup.com/pages/standard-publication-reuse-rightsTest |
| رقم الانضمام: |
edsbas.DA163A6F |
| قاعدة البيانات: |
BASE |
