An international multi-institutional validation study of the algorithm for prostate cancer detection and Gleason grading.
Ontology highlight
ABSTRACT: Pathologic examination of prostate biopsies is time consuming due to the large number of slides per case. In this retrospective study, we validate a deep learning-based classifier for prostate cancer (PCA) detection and Gleason grading (AI tool) in biopsy samples. Five external cohorts of patients with multifocal prostate biopsy were analyzed from high-volume pathology institutes. A total of 5922 H&E sections representing 7473 biopsy cores from 423 patient cases (digitized using three scanners) were assessed concerning tumor detection. Two tumor-bearing datasets (core n = 227 and 159) were graded by an international group of pathologists including expert urologic pathologists (n = 11) to validate the Gleason grading classifier. The sensitivity, specificity, and NPV for the detection of tum
SUBMITTER: Tolkach Y
PROVIDER: S-EPMC10427608 | biostudies-literature | 2023 Aug
REPOSITORIES: biostudies-literature
ACCESS DATA