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Updated: Oct 28, 2025

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Published on: March 21, 2025
IVIM Parameters on MRI Could Predict ISUP Risk Groups of Prostate Cancers on Radical Prostatectomy
Chun-Bi Chang1,2, Yu-Chun Lin2,3, Yon-Cheong Wong1,2
1Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Taoyuan, Taiwan.
Purpose:
To elucidate the usefulness of intravoxel incoherent motion (IVIM)/apparent diffusion coefficient (ADC) parameters in preoperative risk stratification using International Society of Urological Pathology (ISUP) grades.
Materials And Methods:
Forty-five prostate cancer (PCa) patients undergoing radical prostatectomy (RP) after prostate multiparametric magnetic resonance imaging (mpMRI) were included. The ISUP grades were categorized into low-risk (I-II) and high-risk (III-V) groups, and the concordance between the preoperative and postoperative grades was analyzed. The largest region of interest (ROI) of the dominant tumor on each IVIM/ADC image was delineated to obtain its histogram values (i.e., minimum, mean, and kurtosis) of diffusivity (D), pseudodiffusivity (D*), perfusion fraction (PF), and ADC. Multivariable logistic regression analysis of the IVIM/ADC parameters without and with preoperative ISUP grades were performed to identify predictors for the postoperative high-risk group.
Results:
Thirty-two (71.1%) of 45 patients had concordant preoperative and postoperative ISUP grades. Dmean, D*kurtosis, PFkurtosis, ADCmin, and ADCmean were significantly associated with the postoperative ISUP risk group (all p < 0.05). Dmean and D*kurtosis (model I, both p < 0.05) could predict the postoperative ISUP high-risk group with an area under the curve (AUC) of 0.842 and a 95% confidence interval (CI) of 0.726-0.958. The addition of D*kurtosis to the preoperative ISUP grade (model II) may enhance prediction performance, with an AUC of 0.907 (95% CI 0.822-0.992).
Conclusions:
The postoperative ISUP risk group could be predicted by Dmean and D*kurtosis from mpMRI, especially D*kurtosis. Obtaining the biexponential IVIM parameters is important for better risk stratification for PCa.
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