NCT07231627

AI Algorithm-Informed Biopsy for Prostate Cancer Detection With Indeterminate and Low-Risk Prostate MRI Lesions

A Prospective Randomized Phase I/II Study of Artificial Intelligence Algorithm-Informed Biopsy for Detection of Prostate Cancer in Patients With Indeterminate and Low-risk Prostate MRI Lesions

• Status: Not Yet Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 50 (estimated)
• Sponsor: University of Arkansas · Academic / Other
• Sex: Male
• Age: 40 Years
• Healthy volunteers: Not accepted

Summary

Use of AI algorithm for PCa detection is feasible, and AI-informed biopsies (AI-targeted and perilesional biopsy) improves csPCa detection in patients with indeterminate MRI lesions and in patients with low-risk MRI lesions and high-risk clinical features.

Detailed description

Primary Feasibility Objective: 1\. Assess the acceptance rate of randomization and biopsy recommendations based on study protocol and AI algorithm results by the patients. This will be assessed in the first 10 patients who enroll during the phase I feasibility segment. Primary Efficacy Objective: 1\. Evaluate the per-patient and per-lesion csPCa detection rates of AI algorithm-informed biopsy (the intervention arm) versus contemporary biopsy (the control arm) in patients randomly allocated 1:1 to each arm. This will be evaluated in all 25 patients per arm (50 patients). Secondary Objectives (These objectives will be satisfied using endpoint data from all 50 subjects (25/arm) enrolled): 1. Evaluate benign and clinically non-significant PCa rates (GS \<7) in patients who underwent AI-algorithm informed (the intervention arm) versus contemporary (the control arm) prostate biopsies. 2. Evaluate the specificity and sensitivity of AI algorithm-informed biopsy (AI-targeted and perilesional prostate biopsy) versus contemporary biopsy in detection of csPCa. 3. Obtain and evaluate adverse events (AEs), urinary function (IPSS), sexual function (IIEF) quality of life (QOL) \[ SF-12 and TMI scores\] and decision regret (DRS) measures on subjects that underwent contemporary biopsy versus AI Algorithm-informed biopsy. Exploratory Objective: 1\. Collect data via genomic and transcriptomic approaches (Whole exome sequencing + Targeted RNA sequencing OR single cell RNA sequencing) in patients whose standard contemporary biopsy, perilesional biopsy and AI-targeted biopsy revealed csPCa, and compare collected data on all endpoints for differences among perilesional biopsy, AI-targeted biopsy and contemporary standard biopsy.

Conditions

• Prostate Cancer

Interventions

Type	Name	Description
DEVICE	Bi-parametric MRI-based cascaded deep-learning AI algorithm	Artificial intelligence system used in medical imaging, primarily for the automated detection and classification of lesions (such as prostate cancer) using only specific types of magnetic resonance imaging (MRI) data.

Timeline

• Start date: 2026-03-01
• Primary completion: 2028-01-01
• Completion: 2029-01-01
• First posted: 2025-11-17
• Last updated: 2026-02-09