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
University of Arkansas
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.
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 Objective…
Eligibility
- Age range
- 40+ years
- Sex
- Male
- Healthy volunteers
- No
Inclusion Criteria: 1. 40 years of age or older. 2. A recent pMRI performed within last 12 weeks 3. Eastern Cooperative Oncology Group (ECOG) performance status 0 - 1. 4. Any patient with PIRADS 3 lesions per pMRI, AND elevated PSA ("=\> 3.0 ng/ml" for patients between 40 and 75 years old, and "=\> 4.0 ng/ml" for the patients older than 75 years). 5. Patients with PIRADS 1-2 lesions per pMRI, AND elevated PSA ("=\> 3.0 ng/ml" for patients between 40 and 75 years old, and "=\> 4.0 ng/ml" for the patients older than 75 years), AND at least one of the following: 1. High PSA density (0.15 ng/…
Interventions
- DeviceBi-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.
Location
- University of Arkansas for Medical SciencesLittle Rock, Arkansas