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
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 50
- 试验地点
- 1
- 主要终点
- 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
研究概览
简要总结
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.
详细描述
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):
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 40 Years 至 —（Adult, Older Adult）
- 性别
- Male
- 接受健康志愿者
- 否
入选标准
- •40 years of age or older.
- •A recent pMRI performed within last 12 weeks
- •Eastern Cooperative Oncology Group (ECOG) performance status 0 -
- •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).
排除标准
- •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.
- •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.
研究组 & 干预措施
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
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.
干预措施: Bi-parametric MRI-based cascaded deep-learning AI algorithm (Device)
结局指标
主要结局
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
时间窗: 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.
Acceptance rate of randomization and biopsy recommendations based on study protocol and AI algorithm results by the patients
时间窗: 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
时间窗: 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.
次要结局
- 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)
- 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)
- 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)
- 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 decision regret using the Decision Regret Scale (Form DRS) to measure on subjects that underwent contemporary biopsy versus AI Algorithm-informed biopsy(4 months)