Purpose We evaluated the accuracy of magnetic resonance imaging in determining the size and shape of localized prostate cancer. Materials and Methods The subjects were 114 men who underwent multi-parametric magnetic resonance imaging before radical prostatectomy with patient specific mold processing of the specimen from 2013 to 2015. T2-weighted images were used to contour the prostate capsule and cancer suspicious regions of interest. The contours were used to design and 3-dimentional print custom molds, which permitted alignment of excised prostates with magnetic resonance imaging scans. Tumors were reconstructed in 3 dimensions from digitized whole mount sections. Tumors were then matched with regions of interest and the relative geometries were compared. Results Of the 222 tumors evident on whole mount sections 118 had been identified on magnetic resonance imaging. For the 118 regions of interest mean volume was 0.8 cc and the longest 3-dimensional diameter was 17 mm. However, for matched pathological tumors, of which most were Gleason score 3 + 4 or greater, mean volume was 2.5 cc and the longest 3-dimensional diameter was 28 mm. The median tumor had a 13.5 mm maximal extent beyond the magnetic resonance imaging contour and 80% of cancer volume from matched tumors was outside region of interest boundaries. Size estimation was most accurate in the axial plane and least accurate along the base-apex axis. Conclusions Magnetic resonance imaging consistently underestimates the size and extent of prostate tumors. Prostate cancer foci had an average diameter 11 mm longer and a volume 3 times greater than T2-weighted magnetic resonance imaging segmentations. These results may have important implications for the assessment and treatment of prostate cancer.

Objective To demonstrate enabling multi-institutional training without centralizing or sharing the underlying physical data via federated learning (FL). Materials and Methods Deep learning models were trained at each participating institution using local clinical data, and an additional model was trained using FL across all of the institutions. Results We found that the FL model exhibited superior performance and generalizability to the models trained at single institutions, with an overall performance level that was significantly better than that of any of the institutional models alone when evaluated on held-out test sets from each institution and an outside challenge dataset. Discussion The power of FL was successfully demonstrated across 3 academic institutions while avoiding the privacy risk associated with the transfer and pooling of patient data. Conclusion Federated learning is an effective methodology that merits further study to enable accelerated development of models across institutions, enabling greater generalizability in clinical use.

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.

Focal laser ablation of the prostate is feasible and safe in men with intermediate risk prostate cancer without serious adverse events or changes in urinary or sexual function at 6 months. Comprehensive biopsy followup indicates that larger treatment margins than previously thought necessary may be required for complete tumor ablation.

Focal laser ablation of prostate cancer appears safe and feasible with the patient under local anesthesia in a urology clinic using magnetic resonance imaging-ultrasound fusion for guidance and thermal probes for monitoring. Further development is necessary to refine out of bore focal laser ablation and additional studies are needed to determine appropriate treatment margins and oncologic efficacy.