Urology

Is Nonpapillary Puncture a Feasible Alternative to Papillary Access in Percutaneous Nephrolithotomy? A Systematic Review and Meta-Analysis.

PURPOSE: Percutaneous nephrolithotomy (PCNL) is the gold standard for treating large and complex renal calculi, but puncture path selection (papillary vs nonpapillary) remains a critical debate because of bleeding risk concerns. This systematic review and meta-analysis aimed to compare the safety and efficacy of nonpapillary vs papillary access in PCNL. METHODS: A comprehensive literature search w...

Shifting from black box decisions to informed decision-making in using artificial intelligence to analyze prostate MRI.

Prostate magnetic resonance imaging (MRI) is central to the detection and localization of clinically significant prostate cancers. However, its interpretation is time-consuming and variable. Artificial intelligence (AI) tools for prostate MRI are rapidly emerging, with their performance approaching that of expert readers in select settings, although robust external validation in unselected real-wo...

Deep learning classification of significant prostate cancer on MRI: a systematic review and meta-analysis.

Deep learning (DL) image analysis of prostate MRI can be integrated into the prostate cancer diagnostic pathway to improve biopsy decision making, red...

GUSL: A novel and efficient machine learning model for prostate segmentation on MRI.

Prostate and zonal segmentation is a crucial step for the clinical diagnosis of prostate cancer (PCa). Computer-aided diagnosis tools for prostate seg...

Integrative machine learning and experimental validation reveal the molecular mechanisms of 2-bromo-4,6-dinitroaniline nephrotoxicity: CD45 and cyclophilin C as early response biomarkers of renal tubular injury.

2-Bromo-4,6-dinitroaniline (BDNA), a synthetic intermediate of brominated azo dyes, poses potential nephrotoxicity risks; however, its early molecular...

Associations between body composition and radiotherapy-related side-effects and health-related quality of life in patients with prostate or lung cancer: sub-analysis of the REQUITE trial.

BACKGROUND: Body composition is emerging as a prognostic biomarker in cancer and may be associated with treatment tolerance, side-effects, and health-...

A fully optimized deep learning framework for explainable and efficient kidney stone detection in computed tomography imaging.

PURPOSE: To develop and rigorously evaluate a hyperparameter-optimized custom convolutional neural network for kidney stone detection on axial compute...

Respiratory motion augmentation for personalized super-resolution (RMApSR) of 3D cine MR images in MRI-guided radiotherapy.

The technical implementation of volumetric magnetic resonance imaging (MRI) has the potential to substantially advance tumor tracking in MRI-guided ra...

Machine learning-based early kidney stone risk classification in diabetic-hypertensive patients using obesity composite indices.

Kidney stone disease (KSD) is increasingly prevalent among patients with diabetes mellitus and hypertension. Obesity-related metabolic abnormalities m...

Artificial intelligence in genitourinary oncology: publication trends and systematic review.

OBJECTIVE: To conduct an analysis of publication trends and a systematic review of randomized controlled trials (RCTs) to characterize the current sta...

Prostatic artery embolization and imaging-based biomarkers: current tools in monitoring treatment response and emerging strategies.

Prostatic artery embolization (PAE) is a safe and effective minimally invasive treatment for lower urinary tract symptoms (LUTS) attributed to benign ...

AI-Based Pathology classifier Predicts Sensitivity to Enzalutamide in Metastatic Hormone-Sensitive Prostate Cancer: A Biomarker Analysis of the ENZAMET Trial.

PURPOSE: The ENZAMET trial established that enzalutamide added to androgen deprivation therapy (ADT) improves overall survival (OS) in metastatic horm...

Machine Learning-Based single-cell characterization of lipid metabolic reprogramming in prostate cancer.

Prostate cancer (PCa) is one of the most prevalent malignancies in men worldwide, and metabolic reprogramming particularly of lipid metabolism plays a...

A digital twin framework for adaptive treatment planning in radiotherapy.

This work aims to develop a digital twin (DT) framework for fast online adaptive proton therapy planning in prostate stereotactic body radiation thera...

Performance of Artificial Intelligence Chatbots Compared with Young Academic Urologists in Reconstructive Urology.

INTRODUCTION: Artificial intelligence (AI) is increasingly used in surgery, but its role in reconstructive urology remains insufficiently studied. The...

Immunosuppressive regimens and long-term kidney transplant outcomes: A dual survival modeling framework.

Optimizing immunosuppressive therapy remains central to improving long-term outcomes after kidney transplantation. Both induction and maintenance ther...

Development and validation of an explainable machine learning model for predicting acute kidney injury in critically ill patients with primary peritonitis: a multicenter cohort study.

Primary peritonitis-associated acute kidney injury (PPA-AKI) represents a complex complication that substantially elevates mortality risk. Currently, ...

Correction to: Prediction of severe erectile dysfunction after penile fracture repair: machine learning analysis results from the reconstruction and trauma working group of the society of urological surgery (RAT-SUS).

[This corrects the article DOI: 10.1093/sexmed/qfaf101.].

The evolving landscape of acute kidney injury: research directions and changes in clinical practice.

Acute kidney injury (AKI) is a common and serious disease, needing a comprehensive and management-based approach. While traditional practice focused o...

Development and validation of a multimodal artificial intelligence-based model for predicting post-prostatectomy treatment outcomes from baseline biparametric prostate magnetic resonance imaging.

PURPOSE: Prostate cancer (PCa) is the second most common cancer and cause of cancer deaths among American men. Existing risk prediction methods have l...