IMPORTANCE Magnetic resonance imaging (MRI) with targeted biopsy is an appealing alternative to systematic 12-core transrectal ultrasonography (TRUS) biopsy for prostate cancer diagnosis, but has yet to be widely adopted.OBJECTIVE To determine whether MRI with only targeted biopsy was noninferior to systematic TRUS biopsies in the detection of International Society of Urological Pathology grade group (GG) 2 or greater prostate cancer. DESIGN, SETTING, AND PARTICIPANTSThis multicenter, prospective randomized clinical trial was conducted in 5 Canadian academic health sciences centers between January 2017 and November 2019, and data were analyzed between January and March 2020. Participants included biopsy-naive men with a clinical suspicion of prostate cancer who were advised to undergo a prostate biopsy. Clinical suspicion was defined as a 5% or greater chance of GG2 or greater prostate cancer using the Prostate Cancer Prevention Trial Risk Calculator, version 2. Additional criteria were serum prostate-specific antigen levels of 20 ng/mL or less (to convert to micrograms per liter, multiply by 1) and no contraindication to MRI. INTERVENTIONS Magnetic resonance imaging-targeted biopsy (MRI-TB) only if a lesion with aProstate Imaging Reporting and Data System (PI-RADS), v 2.0, score of 3 or greater was identified vs 12-core systematic TRUS biopsy. MAIN OUTCOME AND MEASURESThe proportion of men with a diagnosis of GG2 or greater cancer. Secondary outcomes included the proportion who received a diagnosis of GG1 prostate cancer; GG3 or greater cancer; no significant cancer but subsequent positive MRI results and/or GG2 or greater cancer detected on a repeated biopsy by 2 years; and adverse events. RESULTSThe intention-to-treat population comprised 453 patients (367 [81.0%] White, 19 [4.2%] African Canadian, 32 [7.1%] Asian, and 10 [2.2%] Hispanic) who were randomized to undergo TRUS biopsy (226 [49.9%]) or ), of which 421 (93.0%) were evaluable per protocol. A lesion with a PI-RADS score of 3 or greater was detected in 138 of 221 men (62.4%) who underwent MRI, with 26 (12.1%), 82 (38.1%), and 30 (14.0%) having maximum PI-RADS scores of 3, 4, and 5, respectively. Eighty-three of 221 men who underwent MRI-TB (37%) had a negative MRI result and avoided biopsy. Cancers GG2 and greater were identified in 67 of 225 men (30%) who underwent TRUS biopsy vs 79 of 227 (35%) allocated to MRI-TB (absolute difference, 5%, 97.5% 1-sided CI, −3.4% to ϱ; noninferiority margin, −5%). Adverse events were less common in the MRI-TB arm. Grade group 1 cancer detection was reduced by more than half in the MRI arm (from 22% to 10%; risk difference, −11.6%; 95% CI, −18.2% to −4.9%).CONCLUSIONS AND RELEVANCE Magnetic resonance imaging followed by selected targeted biopsy is noninferior to initial systematic biopsy in men at risk for prostate cancer in detecting GG2 or greater cancers.

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Cardiac left ventricle (LV) quantification is among the most clinically important tasks for identification and diagnosis of cardiac diseases, yet still a challenge due to the high variability of cardiac structure and the complexity of temporal dynamics. Full quantification, i.e., to simultaneously quantify all LV indices including two areas (cavity and myocardium), six regional wall thicknesses (RWT), three LV dimensions, and one cardiac phase, is even more challenging since the uncertain relatedness intra and inter each type of indices may hinder the learning procedure from better convergence and generalization. In this paper, we propose a newly-designed multitask learning network (FullLVNet), which is constituted by a deep convolution neural network (CNN) for expressive feature embedding of cardiac structure; two followed parallel recurrent neural network (RNN) modules for temporal dynamic modeling; and four linear models for the final estimation. During the final estimation, both intra-and inter-task relatedness are modeled to enforce improvement of generalization: 1) respecting intra-task relatedness, group lasso is applied to each of the regression tasks for sparse and common feature selection and consistent prediction; 2) respecting inter-task relatedness, three phase-guided constraints are proposed to penalize violation of the temporal behavior of the obtained LV indices. Experiments on MR sequences of 145 subjects show that FullLVNet achieves high accurate prediction with our intra-and inter-task relatedness, leading to MAE of 190mm 2 , 1.41mm, 2.68mm for average areas, RWT, dimensions and error rate of 10.4% for the phase classification. This endows our method a great potential in comprehensive clinical assessment of global, regional and dynamic cardiac function.

3D left ventricle (LV) segmentation on echocardiography is very important for diagnosis and treatment of cardiac disease. It is not only because of that echocardiography is a real-time imaging technology and widespread in clinical application, but also because of that LV segmentation on 3D echocardiography can provide more full volume information of heart than LV segmentation on 2D echocardiography. However, 3D LV segmentation on echocardiography is still an open and challenging task owing to the lower contrast, higher noise and data dimensionality, limited annotation of 3D echocardiography. In this paper, we proposed a novel real-time framework, i.e., VoxelAtlasGAN, for 3D LV segmentation on 3D echocardiography. This framework has three contributions: 1) It is based on voxel-to-voxel conditional generative adversarial nets (cGAN). For the first time, cGAN is used for 3D LV segmentation on echocardiography. And cGAN advantageously fuses substantial 3D spatial context information from 3D echocardiography by self-learning structured loss; 2) For the first time, it embeds the atlas into an end-to-end optimization framework, which uses 3D LV atlas as a powerful prior knowledge to improve the inference speed, address the lower contrast and the limited annotation problems of 3D echocardiography; 3) It combines traditional discrimination loss and the new proposed consistent constraint, which further improves the generalization of the proposed framework. Voxe-lAtlasGAN was validated on 60 subjects on 3D echocardiography and it achieved satisfactory segmentation results and high inference speed. The mean surface distance is 1.85 mm, the mean hausdorff surface distance is 7.26 mm, mean dice is 0.953, the correlation of EF is 0.918, and the mean inference speed is 0.1s. These results have demonstrated that our proposed method has great potential for clinical application.

Introduction: This study evaluates the clinical benefit of magnetic resonance-transrectal ultrasound (MR-TRUS) fusion biopsy over systematic biopsy between first-time and repeat prostate biopsy patients with prior atypical small acinar proliferation (ASAP). Materials: 100 patients were enrolled in a single-centre prospective cohort study: 50 for first biopsy, 50 for repeat biopsy with prior ASAP. Multiparameteric magnetic resonance imaging (MP-MRI) and standard 12-core ultrasound biopsy (Std-Bx) were performed on all patients. Targeted biopsy using MRI-TRUS fusion (Fn-Bx) was performed f suspicious lesions were identified on the prebiopsy MP-MRI. Classification of clinically significant disease was assessed independently for the Std-Bx vs. Fn-Bx cores to compare the two approaches. Results: Adenocarcinoma was detected in 49/100 patients (26 first biopsy, 23 ASAP biopsy), with 25 having significant disease (17 first, 8 ASAP). Fn-Bx demonstrated significantly higher per-core cancer detection rates, cancer involvement, and Gleason scores for first-time and ASAP patients. However, Fn-Bx was significantly more likely to detect significant cancer missed on Std-Bx for ASAP patients than first-time biopsy patients. The addition of Fn-Bx to Std-Bx for ASAP patients had a 166.7% relative risk reduction for missing Gleason ≥ 3 + 4 disease (number needed to image with MP-MRI=10 patients) compared to 6.3% for first biopsy (number to image=50 patients). Negative predictive value of MP-MRI for negative biopsy was 79% for first-time and 100% for ASAP patients, with median followup of 32.1 ± 15.5 months. Conclusions: MR-TRUS Fn-Bx has a greater clinical impact for repeat biopsy patients with prior ASAP than biopsy-naïve patients by detecting more significant cancers that are missed on Std-Bx.