Prostate Cancer
Conditions
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.
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.
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.
Sponsors
University of Arkansas
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
NONE
Eligibility
Sex/Gender
MALE
Age
40 Years to No maximum
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/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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Acceptance rate of randomization and biopsy recommendations based on study protocol and AI algorithm results by the patients | 4 months | 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. |
| 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 | 4 months | 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. |
Secondary
| Measure | Time frame |
|---|---|
| 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 sexual function (Form IIEF) on subjects that underwent contemporary biopsy versus AI Algorithm-informed biopsy | 4 months |
| Evaluation of adverse events on subjects that underwent contemporary biopsy versus AI Algorithm-informed biopsy graded by CTCAE v5.0 | 4 months |
| Percentage of benign and clinically non-significant PCa detected in patients who underwent AI Algorithm-informed or contemporary prostate biopsies. | 4 months |
| Evaluation of quality of life using Form TMI and Form SF12 scores on subjects that underwent contemporary biopsy versus AI Algorithm-informed biopsy | 4 months |
| Evaluation of urinary function (IPSS) on subjects that underwent contemporary biopsy versus AI Algorithm-informed biopsy | 4 months |
| Evaluation of decision regret using the Decision Regret Scale (Form DRS) to measure on subjects that underwent contemporary biopsy versus AI Algorithm-informed biopsy | 4 months |
Countries
United States
Contacts
CONTACTAaron Holley
PRINCIPAL_INVESTIGATORAhmet M Aydin, MD
University of Arkansas
Outcome results
None listed