Assessment of Prostate MR Image and Predictive Value for Benign Prostate Disease among Different DWI Sequences

Background: Early diagnosis of prostate cancer can improve the survival rate of patients on the premise of high-quality images. The prerequisite for early diagnosis is high-quality images. ZOOMit is a method for high-resolution, zoomed FOV imaging, allowing diffusion-weighted images with high contrast and resolution in short acquisition times. RESOLVE DWI is an advanced MRI technique developed to obtain high-resolution diffusionweighted images with reduced susceptibility-related artifacts. Objective: This study aimed to compare the image quality of conventional single-shot Echo-planar Imaging (ss-EPI), Diffusion-weighted Imaging (DWI), zoomed FOV imaging (ZOOMit) DWI, and readout segmentation of long variable echo-trains (RESOLVE) DWI sequences for prostate imaging, and optimize the strategy to obtain high-quality Magnetic Resonance Imaging (MRI) in order to discriminate malignant and benign prostate diseases. Methods: Fifty-one patients were enrolled, including 31 with prostate cancer, 11 with prostate benign disease, and 9 with bladder cancer. Patients underwent MRI scans using T2-weighted (T2W), ss-EPI DWI, ZOOMit DWI, and RESOLVE DWI (b = 0, 50, 1400 s/mm2) sequences using a 3.0T MRI scanner. Subjective scores of image quality were evaluated by two independent radiologists. Differences in the subjective scores and objective parameters among the three sequences were compared. The agreement and consistency between the findings of the two raters were evaluated with Kappa or Intra-class Correlation Coefficient (ICC). Receiver Operating Characteristic (ROC) curves were used to distinguish malignant and benign prostate disease. Results: The agreement of subjective scores of 51 patients was high or moderate between the two radiologists (kappa: 0.529–0.880). ZOOMit displayed the highest clarity and the lowest distortion and artifacts compared to ss-EPI and RESOLVE. The two radiologic technicians obtained moderate or high consistency of objective measurement (ICC: 0.527–0.924). In the ROC analysis, ADCmean and Prostate Imaging Reporting and Data System (PI-RADS) scores for three sequences were comparable in differentiating prostate cancer from benign prostate disease (all p>0.05), in which ZOOMit indicated the highest Area Under the Curve (AUC) (0.930 and 0.790, respectively). Conclusion: Compared to the other two sequences, ZOOMit can be deemed preferable to improve prostate MRI diffusion imaging as it has exhibited the highest AUC in identifying prostate cancer.