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

University of Arkansas

Status: Not yet enrolling

Conditions: Prostate Cancer

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

Study type: Interventional

Funder types: Other

Identifiers

NCT07231627

299514

Details and patient eligibility

About

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.

Full 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.

Enrollment: 50 estimated patients

Sex: Male

Ages: 40+ years old

Volunteers: No Healthy Volunteers

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/ml/g or higher),
   2. suspicious DRE,
   3. a positive/high-risk blood or urine biomarker test,
   4. high-risk ancestry (Black/African American),
   5. those with germline mutations that increase the risk for prostate cancer,
   6. significant personal medical history,
   7. significant family history,
   8. 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).

Exclusion criteria

1. Patients younger than 18 years old.

2. Any patient with PIRADS 4-5 lesion per pMRI.

3. Any patient with known csPCa (GS ≥7 (3+4)) per biopsy.

4. 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).

5. Medically unfit for anesthesia.

6. Any history of allergic reactions attributed to contrast agents, or other compounds of similar chemical compositions.

7. Any medical history preventing pMRI or prostate biopsy.

8. Any medical condition distorting quality of pMRI such as artificial hip prosthesis, and excessive rectal gas.

9. Any other condition that, in the opinion of the investigator, might interfere with the safe conduct of the study.

Inclusion of Women and Minorities: All participants will be men without previous diagnosis for PCa. Men of all ethnic groups and races are eligible for the study. Thus, women will not be included in this study.

Trial design

Primary purpose: Diagnostic

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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50 participants in 2 patient groups

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

Experimental group

Description:

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.

Treatment:

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

Perilesional prostate biopsy

No Intervention group

Description:

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