OBJECTIVE: The objective of this study was to investigate whether the apparent diffusion coefficient (ADC) value from DWI and the forward volume transfer constant (Ktrans) value from dynamic contrast-enhanced MRI independently predict prostate cancer aggressiveness, and to determine whether the combination of both parameters performs better than either parameter alone in assessing tumor aggressiveness before treatment. MATERIALS AND METHODS: This retrospective study included 158 men with histopathologically confirmed prostate cancer who underwent 3-T MRI before undergoing prostatectomy in 2011. Whole-mount step-section pathologic maps identified 195 prostate cancer foci that were 0.5 mL or larger; these foci were then volumetrically assessed to calculate the per-tumor ADC and Ktrans values. Associations between MRI and histopathologic parameters were assessed using Spearman correlation coefficients, univariate and multivariable logistic regression, and AUCs. RESULTS: The median ADC and Ktrans values showed moderate correlation only for tumors for which the Gleason score (GS) was 4 + 4 or higher (ρ = 0.547; p = 0.042). The tumor ADC value was statistically significantly associated with all dichotomized GSs (p < 0.005), including a GS of 3 + 3 versus a GS of 3 + 4 or higher (AUC, 0.693; p = 0.001). The tumor Ktrans value differed statistically significantly only between tumors with a GS of 3 + 3 and those with a primary Gleason grade of 4 (p. 0.015), and it made a statistically significant contribution only in differentiating tumors with a GS of 4 + 3 or higher (AUC, 0.711; p < 0.001) and those with a GS of 4 + 4 or higher (AUC, 0.788; p < 0.001) from lower-grade tumors. Combining ADC and Ktrans values improved diagnostic performance in characterizing tumors with a GS of 4 + 3 or higher and those with a GS of 4 + 4 or higher (AUC, 0.739 and 0.856, respectively; p < 0.01). CONCLUSION: Although the ADC value helped to differentiate between all GSs, the Ktrans value was only a benefit in characterizing more aggressive tumors. Combining these parameters improves their performance in identifying patients with aggressive tumors who may require radical treatment.
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