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Updated: Jun 12, 2026

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
Published on: March 21, 2025
Evaluation of MRI-based risk models versus PI-RADS version 2.1 and arterial spin labeling perfusion imaging strategy
Wanwan Wang1, Xin Zheng2, Jing Wang1
1Division of Life Sciences and Medicine, The First Affiliated Hospital of the University of Science and Technology of China, University of Science and Technology of China, Hefei, China.
Background:
Arterial spin labeling (ASL) is a non-invasive magnetic resonance imaging (MRI) technique that enables quantitative assessment of prostate blood flow (PBF). Although the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 is widely used for risk stratification of clinically significant prostate cancer (csPCa), whether combining ASL with the PI-RADS system can improve diagnostic accuracy remains to be explored. This study aimed to evaluate the risk of csPCa by integrating non-invasive ASL-derived PBF measurements with PI-RADS v2.1 scores in a clinical-imaging model.
Methods:
Of 233 patients with suspected prostate cancer (PCa) who underwent biparametric magnetic resonance imaging (bp-MRI) and ASL, 133 had pathologically confirmed benign or malignant lesions. The analysis included PBF measurements, PI-RADS v2.1 scores, and relevant clinical data from this cohort. This study employed both univariable and multivariable logistic regression to sequentially identify prognostic features. The diagnostic performance of PBF, PI-RADS v2.1 scores, and their combination in detecting csPCa was assessed using receiver operating characteristic (ROC) analysis. Bootstrap resampling was used for internal validation to ensure model stability. A nomogram was constructed to visualize the predictive model for csPCa risk, and decision curve analysis (DCA) was performed to evaluate its clinical utility.
Results:
Independent risk factors for csPCa included maximum prostate blood flow (PBF-max), PI-RADS v2.1 score, total prostate-specific antigen (tPSA), and prostate volume (PV). The diagnostic performance for csPCa, measured by the area under the curve (AUC), was 0.872 for PBF-max alone and 0.916 for the PI-RADS v2.1 score alone. Their combination significantly improved accuracy, yielding an AUC of 0.965. Furthermore, PI-RADS v2.1 scores demonstrated a strong positive correlation with PBF-max (r=0.62).
Conclusions:
The non-invasive quantification of PBF via ASL enhances the diagnostic capability of PI-RADS v2.1 scores for the detection of csPCa.
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