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Purpose: To determine whether water diffusion and the perfusion fraction coefficients in prostate peripheral zone (PZ) and prostate cancer (PCa) are affected by intravenous contrast injection and explore the potential mechanism behind previously reported differences between pre- and post-contrast ADC values., Methods: Our institutional review board waived informed consent for this HIPAA-compliant, retrospective study, which included 32 patients (median age, 63 years; range, 47-77 years) with biopsy-proven, untreated PCa who underwent 3-Tesla MRI, including DW-MRI at b-values 0, 400, 700, 1000 s/mm 2 before and after gadolinium injection. For regions of interest (ROIs) in presumed benign PZ and PZ PCa, apparent diffusion coefficient (ADC), perfusion fraction f, and diffusion coefficient D were estimated voxel-wise, and signal-to-noise ratio (SNR) and contrast-to-noise (CNR) were estimated. Pre- and post-contrast measurements were compared by Wilcoxon signed-rank test; P < 0.05 was considered significant., Results: In PZ, f (P = 0.002) was significantly higher on post-contrast imaging than on pre-contrast imaging, but ADC and D values did not change significantly (P = 0.562 and 0.295 respectively). In PCa, all parameters differed significantly between post-contrast and pre-contrast imaging (P < 0.0001 for ADC, P = 0.0084 for D, and P = 0.029 for f). On post-contrast imaging, SNR was not significantly different in PZ (P = 0.260) but was significantly lower in PCa (P < 0.0001); CNR did not change significantly (P = 0.059)., Conclusion: After contrast injection, ADC and D declined significantly in PCa only, while f increased significantly in both PCa and PZ. Pre- and post-contrast diffusion parameters cannot be used interchangeably for diagnostic purposes that require quantitative diffusion estimates., (Copyright © 2018. Published by Elsevier Inc.)

Purpose: To assess the abilities of the standard mono-exponential (ME), bi-exponential (BE), diffusion kurtosis (DK) and stretched exponential (SE) models to characterize diffusion signal in malignant and prostatic tissues and determine which of the four models best characterizes these tissues on a per-voxel basis., Materials and Methods: This institutional-review-board-approved, HIPAA-compliant, retrospective study included 55 patients (median age, 61years; range, 42-77years) with untreated, biopsy-proven PCa who underwent endorectal coil MRI at 3-Tesla, diffusion-weighted MRI acquired at eight b-values from 0 to 2000s/mm 2 . Estimated parameters were apparent diffusion coefficent (ME model); diffusion coefficients for the fast (D fast ) and slow (D slow ) components and fraction of fast component, f fast (BE model); diffusion coefficient D, and kurtosis K (DK model); distributed diffusion coefficient DDC and α for (SE model). For one region-of-interest (ROI) in PZ and another in PCa in each patient, the corrected Akaike information criterion (AICc) and the Akaike weight (w) were calculated for each voxel., Results: Based on AICc and w, all non-monoexponential models outperformed the ME model in PZ and PCa. The DK model in PZ and SE model in PCa ROIs best fit the greatest average percentages of voxels (39% and 43%, respectively) and had the highest mean w (35±16×10 -2 and 41±22×10 -2 , respectively)., Conclusion: DK and SE models best fit DWI data in PZ and PCa, and non-ME models consistently outperformed the ME model. Voxel-wise mapping of the preferential model demonstrated that the vast majority of voxels in either tissue type were best fit with one of the non-monoexponential models. At the given SNR levels, the maximum b-value of 2000s/mm 2 is not sufficiently high to identify the preferred non-monoexponential model., (Copyright © 2017 Elsevier Inc. All rights reserved.)