Smart learning for urology residents during the COVID-19 pandemic and beyond: insights from a nationwide survey in Italy

The covid 19 pandemic represents a global emergency worldwide. Italy is one of the Countries that has been hit the most, facing since the beginning an urgent need to reshape the whole healthcare system to optimize resources

Prostate volume index and prostatic chronic inflammation predicted low tumor load in 945 patients at baseline prostate biopsy

Purpose: To assess associations of prostate volume index (PVI), defined as the ratio of the volume of the central transition zone to the volume of the peripheral zone of the prostate and prostatic chronic inflammation (PCI) as predictors of tumor load by number of positive cores (PC) in patients undergoing baseline random biopsies. Methods: Parameters evaluated included age, PSA, total prostate volume, PSA density, digital rectal exam, PVI, and PCI. All patients underwent standard transperineal random biopsies. Tumor load was evaluated as absent (no PC), limited (1\u20133 PC), and extensive (more than 3 PC). The association of factors with the risk of tumor load was evaluated by the multinomial logistic regression model. Results: The study evaluated 945 patients. Cancer PC were detected in 477 (507%) cases of whom 207 (43.4%) had limited tumor load and 270 (56.6%) had extensive tumor load. Among other factors, comparing patients with limited tumor load with negative cases, PVI [odds ratio, OR = 0.521, 95% confidence interval (CI) 0.330\u20130.824; p < 0.005] and PCI (OR = 0.289, 95% CI 0.180\u20130.466; p < 0.0001) were inversely associated with the PCA risk. Comparing patients with extensive tumor load with negative patients, PVI (OR = 0.579, 95% CI 0.356\u20130.944; p = 0.028), and PCI (OR = 0.150, 95% CI 0.085\u20130.265; p < 0.0001), predicted PCA risk. Comparing extensive tumor load with limited tumor load patients, PVI and PCI did not show any association with the tumor load. Conclusions: Increased PVI and the presence of PCI decreased the risk of increased tumor load and associated with less aggressive prostate cancer biology in patients at baseline random biopsies

Artificial intelligence and neural networks in urology: current clinical applications

As we enter the era of "big data", an increasing amount of complex health- care data will become available. These data are often redundant, "noisy", and characterized by wide variability. In order to offer a precise and transversal view of a clinical scenario the Artificial Intelligence (AI) with Machine learning (ML) algorithms and Artificial neuron networks (ANNs) process were adopted, with a promising wide diffusion in the near future. The present work aims to provide a comprehensive and critical overview of the current and potential applications of AI and ANNs in Urology

"Augmented reality" applications in urology: a systematic review

INTRODUCTION: Augmented reality (AR) applied to surgical procedures refers to the superimposition of preopera-tive or intraoperative images into the operative field. Augmented reality has been increasingly used in myriad surgical specialties including urology. The following study reviews advance in the use of AR for improvements in urologic outcomes.EVIDENCE ACQUISITION: We identified all descriptive, validity, prospective randomized/nonrandomized tri-als and retrospective comparative/noncomparative studies about the use of AR in urology until March 2021. The Medline, Scopus, and Web of Science databases were used for literature search. We conducted the study selection according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis State-ment) Guidelines. We limited included studies to only those using AR, excluding all that used virtual reality technology.EVIDENCE SYNTHESIS: A total of 60 studies were identified and included in the present analysis. Overall, 19 studies were descriptive/validity/phantom studies for specific AR methodologies, 4 studies were case reports, and 37 studies included clinical prospective/retrospective comparative studies.CONCLUSIONS: Advances in AR have led to increasing registration accuracy as well as increased ability to identify anatomic landmarks and improve outcomes during urologic procedures such as RARP and robot-assisted partial nephrec-tomy

Artificial intelligence for renal cancer: From imaging to histology and beyond

Artificial intelligence (AI) has made considerable progress within the last decade and is the subject of contemporary literature. This trend is driven by improved computational abilities and increasing amounts of complex data that allow for new approaches in analysis and interpretation. Renal cell carcinoma (RCC) has a rising incidence since most tumors are now detected at an earlier stage due to improved imaging. This creates considerable challenges as approximately 10%-17% of kidney tumors are designated as benign in histopathological evaluation; however, certain co-morbid populations (the obese and elderly) have an increased peri-interventional risk. AI offers an alternative solution by helping to optimize precision and guidance for diagnostic and therapeutic decisions. The narrative review introduced basic principles and provide a comprehensive overview of current AI techniques for RCC. Currently, AI applications can be found in any aspect of RCC management including diagnostics, perioperative care, pathology, and follow-up. Most commonly applied models include neural networks, random forest, support vector machines, and regression. However, for implementation in daily practice, health care providers need to develop a basic understanding and establish interdisciplinary collaborations in order to standardize datasets, define meaningful endpoints, and unify interpretation. (C) 2022 Editorial Office of Asian Journal of Urology. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Improving oncological outcomes after robot-assisted radical prostatectomy: what novel tools do we have?

The recent application of novel technologies to the robot-assisted radical prostatectomy (RARP) procedure has provided a new perspective and demonstrated potential usefulness in surgical planning, intraoperative navigation, and education of both patients and healthcare professionals, allowing for a patient-tailored prostate cancer (PCa) treatment. Integration of novel techniques into robotic surgery has improved the accuracy of surgery and has demonstrated a potential benefit in functional and oncological outcomes in patients with PCa. However, further randomized and prospective studies are needed to assess and validate the role of these technologies in clinical practice. The aim of this review is to summarize the current evidence on the new emerging techniques, such as three-dimensional (3D) imaging and printing, augmented reality (AR), and confocal microscopy (CM), and their impact on RARP and its oncological outcomes