Objective: The aim of this study was to determine and validate the optimal combination of parameters derived from 3-T diffusion-weighted imaging, dynamic contrast-enhanced imaging, and magnetic resonance (MR) spectroscopic imaging for discriminating low-grade from high-grade prostate cancer (PCa).

Materials and methods: The study was approved by the institutional review board, and the need for informed consent was waived. Ninety-four patients with PCa who had undergone multiparametric MR imaging (MRI) before prostatectomy were included. Cancer was indicated on T2-weighted images, blinded to any functional data, with prostatectomy specimens as the reference standard. Tumors were classified as low grade or high grade based on Gleason score; peripheral zone (PZ) and transition zone (TZ) tumors were analyzed separately. In a development set (43 patients), the optimal combination of multiparametric MRI parameters was determined using logistic regression modeling. Subsequently, this combination was evaluated in a separate validation set (51 patients).

Results: In the PZ, the 25th percentile of apparent diffusion coefficient (ADC) derived from diffusion-weighted imaging and washout (WO25) derived from dynamic contrast-enhanced MRI offered the optimal combination of parameters. In the TZ, WO25 and the choline over spermine + creatine ratio (C/SC) derived from MR spectroscopic imaging showed the highest discriminating performance. Using the models built with the development set, 48 (74%) of 65 cancer lesions were classified correctly in the validation set.

Conclusions: Multiparametric MRI is a useful tool for the discrimination between low-grade and high-grade PCa and performs better than any individual functional parameter in both the PZ and TZ. The 25th percentile of ADC + WO25 offered the optimal combination in the PZ, and the choline over spermine + creatine ratio + WO25 offered the optimal combination in the TZ. The ADC parameter has no additional value for the assessment of PCa aggressiveness in the TZ.