Related Experiment Video
Updated: Jul 12, 2026
A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
Published on: March 21, 2025
Cognitive Versus Software-based Fusion Targeted Biopsy for the Diagnosis of Clinically Significant Prostate Cancer: A
Bi-Ming He1, Keqin Zhang2, Zhien Zhou3
1Department of Urology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
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/m2, whereas software-based fusion improved detection in men with BMI ≥24 kg/m2. 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.
