Meeting Banner
Abstract #0107

Preliminary Results of Prospective Clinical Study Evaluating Machine Learning Software for Detecting Significant Prostate Cancer on bpMRI

Mohammed R. S. Sunoqrot1,2, Rebecca Segre1, Torill A. Sjøbakk1, Gabriel A. Nketiah1,2, Petter Davik3,4, Sverre Langørgen2, Mattijs Elschot1,2, and Tone F. Bathen1,2
1Department of Circulation and Medical Imaging, NTNU - Norwegian University of Science and Technology, Trondheim, Norway, 2Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway, 3Department of Clinical and Molecular Medicine, NTNU - Norwegian University of Science and Technology, Trondheim, Norway, 4Department of Urology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway

Synopsis

Keywords: Diagnosis/Prediction, AI/ML Software, Prostate Cancer; Detection; Diagnosis; Analysis

Motivation: Prostate cancer (PCa) diagnosis through manual MRI interpretation is variable and prone to overdiagnosis, leading to unnecessary biopsies. PROVIZ, a radiomics-based tool, aims to reduce overdiagnosis by automating clinically significant PCa (csPCa) detection on bi-parametric MRI (bpMRI).

Goal(s): This study assesses the feasibility, safety, and performance of PROVIZ in detecting csPCa, aiming to validate its clinical utility in minimizing unnecessary biopsies.

Approach: In this prospective clinical study, 81 biopsy-naive men underwent bpMRI, evaluated by both radiologists and PROVIZ. Targeted and systematic biopsies confirmed results.

Results: PROVIZ demonstrated feasibility, safety, and higher specificity than radiologists at the same sensitivity, with six fewer biopsy referrals.

Impact: his prospective clinical study suggests that PROVIZ software can enhance diagnostic accuracy in prostate cancer care, improve clinically significant lesion targeting, and potentially reduce unnecessary biopsies, thereby minimizing overdiagnosis and improving patient outcomes in prostate cancer management.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.

Keywords