AI Algorithm-Informed Biopsy for Prostate Cancer Detection With Indeterminate and Low-Risk Prostate MRI Lesions
NCT ID: NCT07231627
Last Updated: 2025-11-17
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
NOT_YET_RECRUITING
NA
50 participants
INTERVENTIONAL
2026-01-31
2029-01-31
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Artificial Intelligence-Based Computer-Aided Diagnosis of Prostate Cancer
NCT05513638
The Application of Multimodal Artificial Intelligence Systems in Prostate Cancer Diagnosis and Prognosis Analysis
NCT06589154
Artificial Intelligence (AI)-Assisted Risk-based Prostate Cancer Detection
NCT05443412
Integrating Quantitative MRI and Artificial Intelligence to Improve Prostate Cancer Classification
NCT04765150
Study of Predicting Lymph Node Metastasis of High-risk Prostate Cancer by Artificial Intelligence Multi-omics Analysis
NCT07112599
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
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
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
RANDOMIZED
PARALLEL
DIAGNOSTIC
NONE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
Bi-parametric MRI-based cascaded deep-learning AI algorithm
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.
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.
Perilesional prostate biopsy
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
No interventions assigned to this group
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
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.
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
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
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.
40 Years
MALE
No
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
University of Arkansas
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Central Contacts
Reach out to these primary contacts for questions about participation or study logistics.
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
299514
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.