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

NCT07231627 | Not Yet Recruiting

• 1 other identifier: 299514
• Study Type: interventional
• Target: 50
• Locations: 1 country
• Sites: 1

Brief 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.

Conditions

Prostate Cancer

Outcome Measures

Primary Outcomes (2)

• Acceptance rate of randomization and biopsy recommendations based on study protocol and AI algorithm results by the patients

  Number and percent of the first 10 enrolled and randomized subjects who agree to undergo the prostate biopsy procedure to which they were randomized and accept the biopsy recommendations based on study protocol and AI algorithm results.

  4 months

• 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

  The percent of csPCa detected per-patient and per-lesion in the biopsy cores obtained from each study arm. We expect at least 42% for the csPCa detection rate on the AI algorithm-informed-biopsy arm, which would be a 27% increase relative to the current csPCa detection rate (15%) expected on the contemporary prostate-biopsy arm.

  4 months

Secondary Outcomes (7)

• Percentage of benign and clinically non-significant PCa detected in patients who underwent AI Algorithm-informed or contemporary prostate biopsies.

  4 months

• Percentage of true positive, false positive, true negative and false negative findings for csPCa in all patients who enrolled in both study arms.versus contemporary biopsy in detection of csPCa

  4 months

• Evaluation of adverse events on subjects that underwent contemporary biopsy versus AI Algorithm-informed biopsy graded by CTCAE v5.0

  4 months

• Evaluation of urinary function (IPSS) on subjects that underwent contemporary biopsy versus AI Algorithm-informed biopsy

  4 months

• Evaluation of sexual function (Form IIEF) on subjects that underwent contemporary biopsy versus AI Algorithm-informed biopsy

  4 months

Other Outcomes (1)

• Expression levels and/or expression profiles of genomic and transcriptomic signatures in csPCa diagnosed from perilesional biopsy, AI-targeted biopsy and contemporary standard biopsy

  4 months

Study Arms (2)

Bi-parametric MRI-based cascaded deep-learning AI algorithm

EXPERIMENTAL

The AI model inputs biparametric DICOM sequences (T2-weighted images, high-b-value diffusion-weighted images, and apparent diffusion coefficient maps), and the outputs include binary prostate organ and intraprostatic lesion segmentations. This study will assess a recently developed and both internally and externally validated AI algorithm for PCa detection capability in patients with equivocal lesions (PI-RADS 3 lesions) and negative lesions (PI-RADS 1-2 lesions) with higher clinical risk features such as high PSA density.

Device: Bi-parametric MRI-based cascaded deep-learning AI algorithm

Perilesional prostate biopsy

NO INTERVENTION

Standard of care prostate biopsy which is a systematic template biopsy (with 12 biopsy cores) + MRI-targeted biopsy (for PI-RADS category 3 lesions only, with 3 biopsy cores), consistent with current NCCN guideline recommendations

Interventions

Bi-parametric MRI-based cascaded deep-learning AI algorithm DEVICE

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.

Bi-parametric MRI-based cascaded deep-learning AI algorithm

Eligibility Criteria

• Age: 40 Years+
• Sex: male
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• years of age or older.
• A recent pMRI performed within last 12 weeks
• Eastern Cooperative Oncology Group (ECOG) performance status 0 - 1.
• 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).
• 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:
• High PSA density (0.15 ng/ml/g or higher),
• suspicious DRE,
• a positive/high-risk blood or urine biomarker test,
• high-risk ancestry (Black/African American),
• those with germline mutations that increase the risk for prostate cancer,
• significant personal medical history,
• significant family history,
• persistent and significant increase in PSA levels (persistently elevated PSA for at least 12 months with an increase of at least 100% or more within 24 months, last level confirmed twice).

You may not qualify if:

• Patients younger than 18 years old.
• Any patient with PIRADS 4-5 lesion per pMRI.
• Any patient with known csPCa (GS ≥7 (3+4)) per biopsy.
• Any patient with PCa and managed with active surveillance, surgery or radiation.
• a. (Patients who never scanned with pMRI before, had GS 6 (3+3) PCa only per systematic biopsy, and currently need confirmatory prostate biopsy will be allowed to enroll in the trial).
• Medically unfit for anesthesia.
• Any history of allergic reactions attributed to contrast agents, or other compounds of similar chemical compositions.
• Any medical history preventing pMRI or prostate biopsy.
• Any medical condition distorting quality of pMRI such as artificial hip prosthesis, and excessive rectal gas.
• Any other condition that, in the opinion of the investigator, might interfere with the safe conduct of the study.

Sponsors & Collaborators

• University of Arkansas: lead

Study Sites (1)

University of Arkansas for Medical Sciences

Little Rock, Arkansas, 72205, United States

Location

MeSH Terms

Conditions

Prostatic Neoplasms

Condition Hierarchy (Ancestors)

Genital Neoplasms, Male; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Genital Diseases, Male; Genital Diseases; Urogenital Diseases; Prostatic Diseases; Male Urogenital Diseases

Study Officials

• Ahmet M Aydin, MD

  University of Arkansas

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Aaron Holley

CONTACT

5016868274; JAHolley@uams.edu

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: November 13, 2025
• First Posted: November 17, 2025
• Study Start: May 1, 2026
• Primary Completion (Estimated): January 1, 2028
• Study Completion (Estimated): January 1, 2029
• Last Updated: May 19, 2026

Record last verified: 2026-05

Locations

US (1)