Luminal Water Imaging: A New MR Imaging T2 Mapping Technique for Prostate Cancer Diagnosis.

Purpose To assess the feasibility of luminal water imaging, a quantitative T2-based magnetic resonance (MR) imaging technique, for the detection and grading of prostate cancer (PCa). Materials and Methods Eighteen patients with biopsy-proven PCa provided informed consent to be included in this institutional human ethics board-approved prospective study between January 2015 and January 2016. Patients underwent 3.0-T MR imaging shortly before radical prostatectomy. T2 distributions were generated with a regularized non-negative least squares algorithm from multiecho spin-echo MR imaging data. From T2 distributions, maps of seven MR parameters, N, T2, T2, geometric mean T2 (gmT2), luminal water fraction (LWF), A, and A, were generated and compared with digitized images of hematoxylin-eosin-stained whole-mount histologic slices. A paired t test was used to determine significant differences between MR parameters in malignant and nonmalignant tissue. Correlation with Gleason score (GS) was evaluated with the Spearman rank correlation test. Diagnostic accuracy was evaluated by using logistic generalized linear mixed-effect models and receiver operating characteristic (ROC) analysis. Results The average values of four MR parameters (gmT2, A, A, and LWF) were significantly different between malignant and nonmalignant tissue. All MR parameters except for T2 showed significant correlation (P < .05) with GS in the peripheral zone. The highest correlation with GS was obtained for LWF (-0.78 ± 0.11, P < .001). ROC analysis demonstrated high accuracy for tumor detection, with the highest area under the ROC curve obtained for LWF (0.97 in the peripheral zone and 0.98 in the transition zone). Conclusion Results of this pilot study demonstrated the feasibility of luminal water imaging in the detection and grading of PCa. A study with a larger cohort of patients and a broader range of GS is required to further evaluate this new technique in clinical settings. RSNA, 2017.