Review ArticlesContemporary Management of Bulbar Urethral StricturesManagement ReviewJames E WrightErica SternRoss S LiaoAndrew J CohenUrethral stricture disease (USD) is a progressive scar-forming disease commonly encountered by urologists and is challenging to manage. USD most frequently occurs in the bulbar urethra. Patients typically present with chronic obstructive voiding symptoms but may develop recurrent urinary tract infections, detrusor failure, or renal disease. The authors review the pathophysiology, diagnostic workup, and evidence-based management of bulbar urethral strictures (BUS). There are multiple surgical options to treat BUS. Endoscopic techniques (eg, dilation and urethrotomy) are suitable for the initial management of short strictures but new evidence-based guidelines recommend against repeated endoscopic treatment. Urethroplasty is the gold standard treatment for BUS of all lengths, with anastomotic techniques appropriate for strictures <2 cm and tissue substitution performed for longer strictures. New techniques, such as non-transecting urethroplasty, lack long-term data but may represent a paradigm shift in the field. Future treatments may utilize tissue-engineered grafts and agents that inhibit inflammation and scar formation. [Rev Urol. 2020;22(4):139–151] © 2021 MedReviews®, LLCUrethroplastyBulbar urethral strictureUrethrotomyUrethral dilationBuccal graft non-transecting
Review ArticlesLow Penetrance Germline Genetic Testing: Role for Risk Stratification in Prostate Cancer Screening and Examples From Clinical PracticeManagement UpdateA Karim KaderChristopher J KanePaul DatoKelly K BreeFranklin GaylisGerald L AndrioleBroad-based prostate-specific antigen (PSA) screening has saved lives but at a substantial human and financial cost. One way of mitigating this harm, while maintaining and possibly improving the benefit, is by focusing screening efforts on men at higher risk. With age, race, and family history as the only risk factors, many men lack any reliable data to inform their prostate cancer (PCa) screening decisions. Complexities including history of previous negative biopsies, interpretation of negative and/or equivocal mpMRI findings, and patient comorbidities further compound the already complicated decisions surrounding PCa screening and early detection. The authors present cases that provide real-world examples of how a single nucleotide polymorphism–based test can provide patients and providers with personalized PCa risk assessments and allow for development of improved risk-stratified screening regimens. [Rev Urol. 2020;22(4):152–158] © 2021 MedReviews®, LLCProstate cancer screeningRisk stratificationSomatic DNA testGermline DNA testsSingle nucleotide polymorphism DNA test
Review ArticlesApplication of Artificial Intelligence/Machine Vision & Learning for the Development of a Live Single-cell Phenotypic Biomarker Test to Predict Prostate Cancer Tumor AggressivenessOriginal ResearchMichael S ManakAshok C ChanderCJ JiangWendell R SuBrad J HoganMatthew J WhitfieldJonathan S VarsanikGrannum R SantDavid M. AlbalaTo assess the usefulness and applications of machine vision (MV) and machine learning (ML) techniques that have been used to develop a single cell–based phenotypic (live and fixed biomarkers) platform that correlates with tumor biological aggressiveness and risk stratification, 100 fresh prostate samples were acquired, and areas of prostate cancer were determined by post-surgery pathology reports logged by an independent pathologist. The prostate samples were dissociated into single-cell suspensions in the presence of an extracellular matrix formulation. These samples were analyzed via live-cell microscopy. Dynamic and fixed phenotypic biomarkers per cell were quantified using objective MV software and ML algorithms. The predictive nature of the ML algorithms was developed in two stages. First, random forest (RF) algorithms were developed using 70% of the samples. The developed algorithms were then tested for their predictive performance using the blinded test dataset that contained 30% of the samples in the second stage. Based on the ROC (receiver operating characteristic) curve analysis, thresholds were set to maximize both sensitivity and specificity. We determined the sensitivity and specificity of the assay by comparing the algorithm-generated predictions with adverse pathologic features in the radical prostatectomy (RP) specimens. Using MV and ML algorithms, the biomarkers predictive of adverse pathology at RP were ranked and a prostate cancer patient risk stratification test was developed that distinguishes patients based on surgical adverse pathology features. The ability to identify and track large numbers of individual cells over the length of the microscopy experimental monitoring cycles, in an automated way, created a large biomarker dataset of primary biomarkers. This biomarker dataset was then interrogated with ML algorithms used to correlate with post-surgical adverse pathology findings. Algorithms were generated that predicted adverse pathology with >0.85 sensitivity and specificity and an AUC (area under the curve) of >0.85. Phenotypic biomarkers provide cellular and molecular details that are informative for predicting post-surgical adverse pathologies when considering tumor biopsy samples. Artificial intelligence ML-based approaches for cancer risk stratification are emerging as important and powerful tools to compliment current measures of risk stratification. These techniques have capabilities to address tumor heterogeneity and the molecular complexity of prostate cancer. Specifically, the phenotypic test is a novel example of leveraging biomarkers and advances in MV and ML for developing a powerful prognostic and risk-stratification tool for prostate cancer patients. [Rev Urol. 2020;22(4):159–167] © 2021 MedReviews®, LLCProstate cancerArtificial intelligencePhenotypic biomarkersMachine visionMachine learning
LUGPA NewsWashington RoundupR Jonathan Henderson[Rev Urol. 2020;22(4):168–169] © 2021 MedReviews®, LLC
Case ReviewCryptozoospermia Associated With Genital Tucking Behavior in a TranswomanRobert J CarrasquilloJames T TrusslerTranswomen may elect to pursue fertility preservation prior beginning hormonal treatment or proceeding with gender-affirming surgery. To date, there has been little research specifically investigating factors influencing fertility and preservation thereof among transwomen. Here, we review the case of a transwoman who engaged in genital tucking behavior presenting with severe oligospermia, and we review the literature regarding transgender fertility preservation and the role of the heat stress hypothesis with regards to this common behavior. [Rev Urol. 2020;22(4):170–173] © 2021 MedReviews®, LLC
NYU Case of the MonthSurgical Management of the “Large” Prostate: The Robotic Simple ProstatectomyNYU Case of the Month, October 2020Alice DrainBenjamin M Brucker[Rev Urol. 2020;22(4):174–176] © 2021 MedReviews®, LLC
NYU Case of the MonthGenetic Mutations Associated With Prostate Cancer and Normal Serum PSA and DRE—Implications for Prostate Cancer Screening and ManagementNYU Case of the Month, November 2020James S Wysock[Rev Urol. 2020;22(4):177–181] © 2021 MedReviews®, LLC
NYU Case of the MonthUpdate in Female Hormonal Therapy: What the Urologist Should KnowNYU Case of the Month, December 2020Nirit Rosenblum[Rev Urol. 2020;22(4):182–185] © 2021 MedReviews®, LLC
CorrigendaAuthor’s Name Correction for “From Radical to Partial Nephrectomy in the Setting of Solitary Functioning Kidney: Neoadjuvant Treatment of Renal Cell Carcinoma,” Rev Urol. 2020;22(3):126–129David D WatsonA J FarhaShaker DakhilK James KallailNicole G Farha[Rev Urol. 2020;22(4):186] © 2021 MedReviews®, LLC