Using prostate-specific membrane antigen positron-emission tomography to guide prostate biopsies and stage men at high-risk of prostate cancer.

Objective: To assess whether a diagnostic pathway in which prostate-specific membrane antigen (PSMA) positron-emission tomography (PET)/computed tomography (CT) is used as a single imaging modality is feasible to guide targeted biopsy and to detect clinically significant prostate cancer (csPCa) in biopsy-naïve men at high-risk of disease.

Patients And Methods: A total of 60 men with a prostate-specific antigen (PSA) level of 20-50 ng/mL underwent F-PSMA(DCFPyL)-PET/CT prior to prostate biopsies in this prospective, non-randomised cohort study. Magnetic resonance imaging (MRI) was not performed.

Evaluating machine learning algorithms to Predict 30-day Unplanned REadmission (PURE) in Urology patients.

Background: Unplanned hospital readmissions are serious medical adverse events, stressful to patients, and expensive for hospitals. This study aims to develop a probability calculator to predict unplanned readmissions (PURE) within 30-days after discharge from the department of Urology, and evaluate the respective diagnostic performance characteristics of the PURE probability calculator developed with machine learning (ML) algorithms comparing regression versus classification algorithms.

Methods: Eight ML models (i.

Implications of resampling data to address the class imbalance problem (IRCIP): an evaluation of impact on performance between classification algorithms in medical data.

Objective: When correcting for the "class imbalance" problem in medical data, the effects of resampling applied on classifier algorithms remain unclear. We examined the effect on performance over several combinations of classifiers and resampling ratios.

Materials And Methods: Multiple classification algorithms were trained on 7 resampled datasets: no correction, random undersampling, 4 ratios of Synthetic Minority Oversampling Technique (SMOTE), and random oversampling with the Adaptive Synthetic algorithm (ADASYN).

Cancer detection and complications of transperineal prostate biopsy with antibiotics when indicated.

Objectives: To describe the prostate cancer (PCa) detection rate, including clinically significant prostate cancer (csPCa), in a large cohort of patients who underwent transperineal ultrasonography-guided systematic prostate biopsy (TPB-US) using a probe-mounted transperineal access system, with magnetic resonance imaging (MRI) cognitive fusion in case of a Prostate Imaging-Reporting and Data System grade 3-5 lesion, under local anaesthesia in an outpatient setting. Additionally, to compare the incidence of procedure-related complications with a cohort of patients undergoing transrectal ultrasonography-guided (TRB-US) and transrectal MRI-guided biopsies (TRB-MRI).

Patients And Methods: This was an observational cohort study in men who underwent TPB-US prostate biopsy in a large teaching hospital.

Inter- and Intraobserver Agreement in Measuring Urolithiasis Density on Nonenhanced Computed Tomography.

Treatment choice for urolithiasis is partially based on measuring stone density in HU on nonenhanced computed tomography (NECT). Interobserver variability in these measurements could have treatment consequences. This study aims to assess the observer agreement of measuring HU and whether the use of a protocol leads to a better agreement.