For prostate cancer detection on prostate multiparametric MRI (mpMRI), the Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2) and computer-aided diagnosis (CAD) systems aim to widely improve standardization across radiologists and centers. Our goal was to evaluate CAD assistance in prostate cancer detection compared with conventional mpMRI interpretation in a diverse dataset acquired from five institutions tested by nine readers of varying experience levels, in total representing 14 globally spread institutions.Index lesion sensitivities of mpMRI-alone were 79% (whole prostate (WP)), 84% (peripheral zone (PZ)), 71% (transition zone (TZ)), similar to CAD at 76% (WP, p=0.39), 77% (PZ, p=0.07), 79% (TZ, p=0.15). Greatest CAD benefit was in TZ for moderately-experienced readers at PI-RADSv2 <3 (84% vs mpMRI-alone 67%, p=0.055). Detection agreement was unchanged but CAD-assisted read times improved (4.6 vs 3.4 minutes, p<0.001). At PI-RADSv2 ≥ 3, CAD improved patient-level specificity (72%) compared to mpMRI-alone (45%, p<0.001).PI-RADSv2 and CAD-assisted mpMRI interpretations have similar sensitivities across multiple sites and readers while CAD has potential to improve specificity and moderately-experienced radiologists’ detection of more difficult tumors in the center of the gland. The multi-institutional evidence provided is essential to future prostate MRI and CAD development.
One proposed solution is to use artificial intelligence (AI)-based detection systems.With the help of machine learning, classification algorithms can be trained to predict results and outcomes, provided that enough training data are available. In 2017, we at the National Cancer Institute [7] proposed an AI system based on intensity and texture analysis and a random forest classification algorithm. This system was validated in a large multireader multicenter study in 2018 [8]. Results of that study revealed an increase in detection of transition zone lesions among moderately experienced readers only. Overall, however, the AI system was equivalent to conventional MRI interpretation [8]. In that study, color-coded prediction maps were used to draw attention to AI-detected lesions. Feedback from the study suggested that prediction maps compromised the interaction between the radiologists and the AI system with resultant decreased accuracy for some readers. To address this issue a new AI detection system with more expert annotated
<b><i>Objective:</i></b> The objective of this study is to evaluate the effect of diagnostic ureterorenoscopy (URS) prior to radical nephroureterectomy (RNU) on intravesical recurrence (IVR), in patients with primary upper urinary tract urothelial carcinoma (UTUC). <b><i>Materials and Methods:</i></b> Retrospective analysis of 354 patients, who underwent RNU for UTUC from 10 urology centers between 2005 and 2019, was performed. The primary endpoint was the occurrence of IVR after RNU. Patients were divided into URS prior to RNU (Group 1) and no URS prior to RNU (Group 2). Rates of IVR after RNU were compared, and a Cox proportional hazards model was used to evaluate potential predictors of IVR. <b><i>Results:</i></b> After exclusion, a total of 194 patients were analyzed: Group 1 <i>n</i> = 95 (49.0%) and Group 2 <i>n</i> = 99 (51.0%). In Group 1, a tumor biopsy and histopathological confirmation during URS were performed in 58 (61.1%). The mean follow-up was 39.17 ± 39.3 (range 12–250) months. In 54 (27.8%) patients, IVR was recorded after RNU, and the median recurrence time within the bladder was 10.0 (3–144) months. IVR rate was 38.9% in Group 1 versus 17.2% in Group 2 (<i>p</i> = 0.001). In Group 1, IVR rate was 43.1% in those undergoing intraoperative biopsy versus 32.4% of patients without biopsy during diagnostic URS (<i>p</i><b> =</b>0.29). Intravesical recurrence-free survival (IRFS) was longer in Group 2 compared to Group 1 (median IRFS was 111 vs. 60 months in Groups 2 and 1, respectively (<i>p</i><b></b>< 0.001)). Univariate analysis revealed that IRFS was significantly associated with URS prior to RNU (HR: 2.9, 95% CI 1.65–5.41; <i>p</i> < 0.001). In multivariate analysis, URS prior to RNU (HR: 3.5, 95% CI 1.74–7.16; <i>p</i> < 0.001) was found to be an independent prognostic factor for IRFS. <b><i>Conclusion:</i></b> Diagnostic URS was associated with the poor IRFS following RNU for primary UTUC. The decision for a diagnostic URS with or without tumor biopsy should be reserved for cases where this information might influence further treatment decisions.
Percutaneous nephrolithotomy is a safe and effective treatment for children with cystine stones. Our high recurrence and regrowth rates emphasize that our treatment schedule is inadequate to prevent recurrent cystine calculi. Additional investigation is needed to determine the optimal medical therapy for preventing recurrence and regrowth of cystine stones.
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