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Updated: Jun 23, 2025
A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
Published on: March 21, 2025
Bi-Parameter MRI Could Quantitatively Assess the Zonal Heterogeneity of Prostate Cancer
Ye Han1, Lei Yuan2, Jingliang Zhang3
1Department of Radiology, Xijing Hospital, Air Force Medical University, Xi'an City, Shaanxi Province, China; Department of Radiology, 83 Group Military Hospital of People's Liberation Army, Xinxiang City, Henan Province, China.
Introduction:
Prostate cancer (PCa) located in the peripheral zone (PZ) and transitional zone (TZ) showed a different clinical and pathological characteristic. This passage aims to preliminarily evaluate the relationship between the zonal heterogeneity of PCa quantitatively assessed by bpMRI and pathological risk stratification of the primary lesion.
Methods:
This prospective study was conducted from January 2019 to February 2023. A total of 113 PCa patients whose bpMRI data indicated that the lesions located in only 1 single zone of the prostate were selected. A transrectal ultrasound and MRI-targeted biopsy were performed to verify the bpMRI results, and then radical prostatectomy (RP) was performed in 3 weeks after the biopsy. The high-risk (HR) group was defined as ISUP grades ≥ 3. Binary regression was performed to evaluate if the zonal heterogeneity could be an independent predictor of the HR group. The receiver operator characteristic (ROC) curve was performed to analyze the added value of zonal location in predicting the HR group.
Results:
PSA, T staging, and ISUP grades, incidence of positive surgical margins were significantly lower in the TZ PCa, and the ADCmin, and ADCmean values in the TZ PCa were significantly higher (all P < .01). The zonal heterogeneity could independently predict the HR group patients (OR: 5.170 [1.663-16.067], P = .005) and improve the predicting efficiency of HR patients (AUC 0.824, 95% CI, 0.741-0.889).
Conclusions:
BpMRI could quantitively assess the zonal heterogeneity of PCa precisely and increase the predicting efficacy of HR patients, which can provide better help for clinical individualized treatment.
