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BACKGROUND Prostate magnetic resonance imaging (MRI) is technically demanding, requiring high image quality to reach its full diagnostic potential. An automated method to identify diagnostically inadequate images could help optimize image quality. PURPOSE To develop a convolutional neural networks (CNNs) based analysis pipeline for the classification of prostate MRI image quality. STUDY TYPE Retrospective. SUBJECTS Three hundred sixteen prostate mpMRI scans and 312 men (median age 67). FIELD STRENGTH/SEQUENCE A 3 T; fast spin echo T2WI, echo planar imaging DWI, ADC, gradient-echo dynamic contrast enhanced (DCE). ASSESSMENT MRI scans were reviewed by three genitourinary radiologists (V.P., M.D.M., S.C.) with 21, 12, and 5 years of experience, respectively. Sequences were labeled as high quality (Q1) or low quality (Q0) and used as the reference standard for all analyses. STATISTICAL TESTS Sequences were split into training, validation, and testing sets (869, 250, and 120 sequences, respectively). Inter-reader agreement was assessed with the Fleiss kappa. Following preprocessing and data augmentation, 28 CNNs were trained on MRI slices for each sequence. Model performance was assessed on both a per-slice and a per-sequence basis. A pairwise t-test was performed to compare performances of the classifiers. RESULTS The number of sequences labeled as Q0 or Q1 was 38 vs. 278 for T2WI, 43 vs. 273 for DWI, 41 vs. 275 for ADC, and 38 vs. 253 for DCE. Inter-reader agreement was almost perfect for T2WI and DCE and substantial for DWI and ADC. On the per-slice analysis, accuracy was 89.95% ± 0.02% for T2WI, 79.83% ± 0.04% for DWI, 76.64% ± 0.04% for ADC, 96.62% ± 0.01% for DCE. On the per-sequence analysis, accuracy was 100% ± 0.00% for T2WI, DWI, and DCE, and 92.31% ± 0.00% for ADC. The three best algorithms performed significantly better than the remaining ones on every sequence (P-value

BackgroundTissue clearing technologies have enabled remarkable advancements for in situ characterization of tissues and exploration of the three-dimensional (3D) relationships between cells, however, these studies have predominantly been performed in non-human tissues and correlative assessment with clinical imaging has yet to be explored. We sought to evaluate the feasibility of tissue clearing technologies for3Dimaging of intact human prostate and the mapping of structurally and molecularly preserved pathology data with multi-parametric volumetric MR imaging (mpMRI).MethodsWhole-mount prostates were processed with either hydrogel-based CLARITY or solvent-based iDISCO. The samples were stained with a nuclear dye or fluorescently labeled with antibodies against androgen receptor, alpha-methylacyl coenzyme-A racemase, or p63, and then imaged with 3D confocal microscopy. The apparent diffusion coefficientand Ktrans maps were computed from preoperative mpMRI.ResultsQuantitative analysis of cleared normal and tumor prostate tissue volumes displayed differences in 3D tissue architecture, marker-specific cell staining, and cell densities that were significantly correlated with mpMRI measurements in this initial, pilot cohort.Conclusions3D imaging of human prostate volumes following tissue clearing is a feasible technique for quantitative radiology-pathology correlation analysis with mpMRI and provides an opportunity to explore functional relationships between cellular structures and cross-sectional clinical imaging.

OBJECTIVES (I) To determine Vesical Imaging-Reporting and Data System (VI-RADS) score 5 accuracy in predicting locally advanced bladder cancer (BCa), so as to potentially identify those patients who could avoid the morbidity of deep transurethral resection of bladder tumour (TURBT) in favour of histological sampling-TUR prior to radical cystectomy (RC). (II) To explore the predictive value of VI-RADS score 5 on time-to-cystectomy (TTC) outcomes. PATIENTS AND METHODS We retrospectively reviewed patients' ineligible or refusing cisplatin-based combination neoadjuvant chemotherapy who underwent multiparametric magnetic resonance imaging (mpMRI) of the bladder prior to staging TURBT followed by RC for muscle-invasive BCa. Sensitivity, specificity, positive and negative predictive values (PPV, NPV) were calculated for VI-RADS score 5 vs. score 2-4 cases to assess the accuracy of mpMRI for extravesical BCa detection (≥pT3). VI-RADS score performance was assessed by receiver operating characteristics curve analysis. A Κ statistic was calculated to estimate mpMRI and pathological diagnostic agreement. The risk of delayed TTC (i.e. time from initial BCa diagnosis of >3 months) was assessed using multivariable logistic regression model. RESULTS A total of 149 T2-T4a, cN0-M0 patients (VI-RADS score 5, n = 39 vs VI-RADS score 2-4, n = 110) were examined. VI-RADS score 5 demonstrated sensitivity, specificity, PPV and NPV, in detecting extravesical disease of 90.2% (95% confidence interval [CI] 84-94.3), 98.1% (95% CI 94-99.6), 94.9% (95% CI 89.6-97.6) and 96.4% (95% CI 91.6-98.6), respectively. The area under the curve was 94.2% (95% CI 88.7-99.7) and inter-reader agreement was excellent (Κinter 0.89). The mean (SD) TTC was 4.2 (2.3) and 2.8 (1.1) months for score 5 vs 2-4, respectively (P

Accurate staging of bladder cancer (BC) is critical, with local tumor staging directly influencing management decisions and affecting prognosis. However, clinical staging based on clinical examination, including cystoscopy and transurethral resection of bladder tumor (TURBT), often understages patients compared to final pathology at radical cystectomy and lymph node (LN) dissection, mainly due to underestimation of the depth of local invasion and the presence of LN metastasis. MRI has now become established as the modality of choice for the local staging of BC and can be additionally utilized for the assessment of regional LN involvement and tumor spread to the pelvic bones and upper urinary tract (UUT). The recent development of the Vesical Imaging-Reporting and Data System (VI-RADS) recommendations has led to further improvements in bladder MRI, enabling standardization of image acquisition and reporting. Multiparametric magnetic resonance imaging (mpMRI) incorporating morphological and functional imaging has been proven to further improve the accuracy of primary and recurrent tumor detection and local staging, and has shown promise in predicting tumor aggressiveness and monitoring response to therapy. These sequences can also be utilized to perform radiomics, which has shown encouraging initial results in predicting BC grade and local stage. In this article, the current state of evidence supporting MRI in local, regional, and distant staging in patients with BC is reviewed. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:649-667.