Prospective validation of an AI software for detecting clinically significant prostate cancer on biparametric MRI.

ABSTRACT:

Objectives

To evaluate the feasibility and safety (primary endpoints), and performance (secondary endpoint) of a new artificial intelligence (AI) software for detecting clinically significant prostate cancer (csPCa) on biparametric MRI (bpMRI) compared to an expert radiologist.

Materials and methods

In this prospective study at St. Olavs Hospital, Norway (December 2023-October 2024), 89 consecutive biopsy-naïve men underwent bpMRI for suspected PCa. Scans were interpreted by a radiologist using PI-RADS v2.1 and a radiomics-based AI software. Biopsies were obtained from all radiologist- and/or AI-identified lesions. csPCa was defined as ISUP ≥ 2. Feasibility was defined by a < 10% software-failure rate, and safety by the absence of serious adverse device effects (SADEs). Perf

SUBMITTER: Sunoqrot MRS 

PROVIDER: S-EPMC12834860 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature