GENITOURINARY IMAGINGM ultiparametric MRI is an important tool in the diagnosis of prostate cancer (PCa) (1,2). However, multiparametric MRI still misses PCa in up to 45% of men and faces challenges in distinguishing clinically significant PCa from indolent PCa (2,3). Thus, histopathologic examination of PCa remains the reference standard. A Gleason score based on the microscopic appearance of PCa is assigned to indicate its aggressiveness (4).Diffusion-weighted MRI is a critical component of multiparametric MRI and is sensitive to tissue microstructure changes in PCa (5). However, current clinical analysis using a monoexponential signal model to calculate apparent diffu-Materials and Methods: Men with PCa who underwent 3-T MRI and robotic-assisted radical prostatectomy between June 2018 and January 2019 were prospectively studied. After prostatectomy, the fresh whole prostate specimens were imaged in patient-specific threedimensionally printed molds by using 3-T MRI with DR-CSI and were then sliced to create coregistered WMHP slides. The DR-CSI spectral signal component fractions (f A , f B , f C ) were compared with epithelial, stromal, and luminal area fractions (f epithelium , f stroma , f lumen ) quantified in PCa and benign tissue regions. A linear mixed-effects model assessed the correlations between (f A , f B , f C ) and (f epithelium , f stroma , f lumen ), and the strength of correlations was evaluated by using Spearman correlation coefficients. Differences between PCa and benign tissues in terms of DR-CSI signal components and microscopic tissue compartments were assessed using two-sided t tests.Results: Prostate specimens from nine men (mean age, 65 years 6 7 [standard deviation]) were evaluated; 20 regions from 17 PCas, along with 20 benign tissue regions of interest, were analyzed. Three DR-CSI spectral signal components (spectral peaks) were consistently identified. The f A , f B , and f C were correlated with f epithelium , f stroma , and f lumen (all P , .001), with Spearman correlation coefficients of 0.74 (95% confidence interval [CI]: 0.62, 0.83), 0.80 (95% CI: 0.66, 0.89), and 0.67 (95% CI: 0.51, 0.81), respectively. PCa exhibited differences compared with benign tissues in terms of increased f A (PCa vs benign, 0.37 6 0.05 vs 0.27 6 0.06; P , .001), decreased f C (PCa vs benign, 0.18 6 0.06 vs 0.31 6 0.13; P = .01), increased f epithelium (PCa vs benign, 0.44 6 0.13 vs 0.26 6 0.16; P , .001), and decreased f lumen (PCa vs benign, 0.14 6 0.08 vs 0.27 6 0.18; P = .004). Conclusion:Diffusion-relaxation correlation spectrum imaging signal components correlate with microscopic tissue compartments in the prostate and differ between cancer and benign tissue.

Background: Prostate diffusion-weighted imaging (DWI) using monopolar encoding is sensitive to eddy-current-induced distortion artifacts. Twice-refocused bipolar encoding suppresses eddy current artifacts, but increases echo time (TE), leading to lower signal-to-noise ratio (SNR). Optimization of the diffusion encoding might improve prostate DWI. Purpose: To evaluate eddy current nulled convex optimized diffusion encoding (ENCODE) for prostate DWI with minimal TE. Study Type: Prospective cohort study. Population: A diffusion phantom, an ex vivo prostate specimen, 10 healthy male subjects (27 AE 3 years old), and five prostate cancer patients (62 AE 7 years old). Field Strength/Sequence: 3T; single-shot spin-echo echoplanar DWI. Assessment: Eddy-current artifacts, TE, SNR, apparent diffusion coefficient (ADC), and image quality scores from three independent readers were compared between monopolar, bipolar, and ENCODE prostate DWI for standard-resolution (1.6 × 1.6 mm 2 , partial Fourier factor [pF] = 6/8) and higher-resolution protocols (1.6 × 1.6 mm 2 , pF = off; 1.0 × 1.0 mm 2 , pF = 6/8). Statistical Testing: SNR and ADC differences between techniques were tested with Kruskal-Wallis and Wilcoxon signedrank tests (P < 0.05 considered significant). Results: Eddy current suppression with ENCODE was comparable to bipolar encoding (mean coefficient of variation across three diffusion directions of 9.4% and 9%). For a standard-resolution protocol, ENCODE achieved similar TE as monopolar and reduced TE by 14 msec compared to bipolar, resulting in 27% and 29% higher mean SNR in prostate transition zone (TZ) and peripheral zone (PZ) (P < 0.05) compared to bipolar, respectively. For higher-resolution protocols, ENCODE achieved the shortest TE (67 msec), with 17-21% and 58-70% higher mean SNR compared to monopolar (TE = 77 msec) and bipolar (TE = 102 msec) in PZ and TZ (P < 0.05). No significant differences were found in mean TZ (P = 0.91) and PZ ADC (P = 0.94) between the three techniques. ENCODE achieved similar or higher image quality scores than bipolar DWI in patients, with mean intraclass correlation coefficient of 0.77 for overall quality between three independent readers. Data Conclusion: ENCODE minimizes TE (improves SNR) and reduces eddy-current distortion for prostate DWI compared to monopolar and bipolar encoding. Level of Evidence: 2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2020;51:1526-1539. P ROSTATE CANCER (PCa) is the most prevalent noncutaneous cancer diagnosed in men and the second leading cause of cancer-related death in men in the United States. 1 Multiparametric magnetic resonance imaging (mp-MRI) of the prostate, including T 2 -weighted MRI, diffusionweighted MRI (DWI), apparent diffusion coefficient (ADC) View this article online at wileyonlinelibrary.com.

Diffusion-Relaxation Correlation Spectrum Imaging (DR-CSI) can provide unique microstructural information for prostate cancer characterization, but requires longer scan times for two-dimensional encoding of TE and b-values. This study developed a data-driven sequential backward selection framework that determined subsampled encoding schemes for DR-CSI, achieving 70% reduction of scan time to 6min while maintaining accurate ex vivo prostate microstructure mapping.