Evaluation of Diffusion Kurtosis Imaging Versus Standard Diffusion Imaging for Detection and Grading of Peripheral Zone Prostate Cancer.

OBJECTIVES

The purpose of the study was to evaluate and validate diffusion kurtosis imaging (DKI) for detection grading of peripheral zone prostate cancer (PCa) compared with standard diffusion-weighted imaging (DWI) in a cohort of patients with biopsy-proven PCa.

MATERIALS AND METHODS

In this retrospective, single-institutional study, 55 patients (age, 67.5 ± 6.9 years; range, 52-84 years) who underwent multiparametric magnetic resonance imaging (MRI) before transperineal magnetic resonance/transrectal ultrasound-guided fusion biopsy were included. Suspicious lesions identified in multiparametric MRI underwent image-guided targeted biopsy procedure using a hybrid magnetic resonance/transrectal ultrasound-guided fusion biopsy system. Multiparametric MRI examinations were performed at 3.0 T using a 16-channel phased array coil. Diffusion kurtosis imaging has been acquired with 9 b values (0, 50, 250, 500, 750, 1000, 1250, 1500, and 2000 s/mm). In patients with histologically proven PCa, a representative tumor region was determined as region of interest (ROI) on axial T2-weighted images in consensus by 2 board-certified radiologists. For quantitative evaluation, ROIs located in malignant and contralateral tumor-free regions were transferred to diffusion-weighted images. Diffusion kurtosis imaging parameters (Dapp and Kapp) and apparent diffusion coefficient (ADC) values of the ROIs in tumor and contralateral remote areas were calculated. Estimation of the kurtosis-derived parameters was performed using a voxel-by-voxel fit followed by an ROI-based averaging and a second fit to ROI-averaged signal values. A subgroup analysis was performed to determine the influence of aggressiveness of PCa using ADC, Dapp, and Kapp. The receiver operating characteristic (ROC) curves were calculated for DKI parameters and ADC values.

RESULTS

In the 55 patients, the average prostate-specific antigen level was 12.4 ± 12.6 ng/mL (range, 2.7–75.0 ng/mL), and the median Gleason score was 7 (range, 6–10). Dapp (units, 10(-3) mm(2)/s) was significantly lower in tumor compared with control regions (1.48 ± 0.35 vs 2.00 ± 0.32, P < 0.05), and Kapp was significantly higher (1.01 ± 0.21 vs 0.76 ± 0.14, P < 0.05). Dapp was significantly higher than standard ADC (units, 10(-3) mm(2)/s) both in tumor regions and in controls (1.48 ± 0.35 vs 1.10 ± 0.25 and 2.00 ± 0.32 vs 1.43 ± 0.25, P < 0.05). Neither the ROI-based calculation of the kurtosis parameters nor the application of the noise correction significantly changed the DKI parameter estimation. There was no significant difference for the applied fitting method for DKI-derived parameters considering the differentiation between tumor and control tissue. Subsequent ROC analyses did not reveal a significant difference between DKI and ADC for detection of PCa. Sensitivities derived by Youden J statistics cutoff values ranged from 69% to 91% for DKI parameters; specificities ranged from 71% to 89%. Subgroup analysis for DKI (Dapp, Kapp) and ADC for assessing aggressiveness of PCa found significant difference (P < 0.05) for discrimination between high- and low-grade findings. However, no significant difference could be obtained between standard DWI- and DKI-derived parameters.

CONCLUSIONS

The results of this study demonstrated no significant benefit of DKI for detection and grading of PCa as compared with standard ADC in the peripheral zone determined from b values of 0 and 800 s/mm. For clinical routine application, ADC derived from monoexponential fitting of DWI data remains the standard for characterizing peripheral zone cancer of the prostate.