Cognitive Versus Software-based Fusion Targeted Biopsy for the Diagnosis of Clinically Significant Prostate Cancer: A Multicenter, Randomized, Noninferiority Trial (IMAGINATION)

医学 置信区间 活检 前列腺癌 前列腺活检 磁共振成像 人口 内科学 前列腺 泌尿科 随机对照试验 认知 放射科 不利影响 临床终点 肿瘤科 外科 临床试验 相对风险 比例危险模型 优势比
作者
Bi-Ming He,K X Zhang,Zhien Zhou,Xingfa Chen,Yi Liu,Biao Dong,Yuxing Wang,Yaping Xing,Wenqiang He,Z Jin,Tongqing Zhang,Tianrui Feng,Liang Liang,Bo Chen,Shouzhen Chen,Zhenquan Lu,Shuming Zhou,Yanfang Zhao,Yingtao Liu,Z L Wang
出处
期刊:European Urology [Elsevier BV]
被引量:1
标识
DOI:10.1016/j.eururo.2026.06.020
摘要

Background Magnetic resonance imaging–targeted prostate biopsy relies heavily on costly software-fusion platforms, limiting global accessibility. Objective We aimed to determine whether cognitive fusion (mental registration) is noninferior to software-based fusion targeted biopsy for detecting clinically significant prostate cancer (csPCa). Design, setting, and participants This multicenter, randomized, blinded, noninferiority trial enrolled 648 predominantly biopsy-naive men (prostate-specific antigen 4–20 ng/ml; Prostate Imaging Reporting and Data System ≥3) at nine centers in China. Intervention Participants were randomly assigned 1:1 to cognitive fusion or software-based fusion targeted biopsy, followed by systematic biopsy. Outcome measurements and statistical analysis The primary outcome was csPCa (ISUP grade group ≥2) detection on targeted biopsy, evaluated using generalized estimating equations with a prespecified −10 percentage point noninferiority margin. Results and limitations In the intention-to-treat population (327 cognitive and 321 software), targeted biopsy detected csPCa in 32% and 34% of the patients, respectively. The adjusted risk difference was –1.02 percentage points (90% confidence interval [CI], –5.6 to 3.6), establishing noninferiority. Combined targeted and systematic biopsy detected csPCa in 35–39% of the patients, respectively (difference, –1.50% [90% CI, –6.4 to 3.4]). A significant body mass index (BMI) interaction was observed ( p < 0.001): cognitive fusion performed best in men with BMI <24 kg/m 2 , whereas software-based fusion improved detection in men with BMI ≥24 kg/m 2 . Adverse event rates were comparable (15% vs 18%). Limitations include conducting the trial predominantly in Asian populations, necessitating cautious geographic extrapolation of specific BMI cutoffs. Conclusions Cognitive fusion is diagnostically noninferior to software-based fusion within a prespecified –10% margin overall. However, a significant BMI interaction raises serious concerns regarding the diagnostic feasibility of cognitive fusion in obese populations, where software-based fusion is strictly superior. Future prospective trials in both Asian and Western populations must evaluate the BMI effect as a primary end point. Trial registration: ClinicalTrials.gov NCT04271527.
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