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LonidamineView Articles
LowView Articles
Low-grade tumorsView Articles

Volume 22, Number 1Review Articles

Management of Low-grade Upper Tract Urothelial Carcinoma: An Unmet Need

Management Review

Neal D ShoreJay Raman

Upper tract urothelial cancers (UTUC) are frequently managed by radical nephroureterectomy (RNU), a major operative procedure that may entail short-term morbidity and long-term decline in renal function. Kidney-sparing procedures offer a less invasive alternative to RNU for low-risk, low-grade UTUC (LG-UTUC). They are associated with similar disease-specific survival rates and better long-term renal function, albeit with a potentially increased risk of recurrence. Strategies to decrease LG-UTUC recurrence include improved risk stratification and enhanced endoscopic instrumentation. Chemoablation may represent an alternative, innovative kidney-sparing approach for LG-UTUC. [Rev Urol. 2020;22(1):1–8] © 2020 MedReviews®, LLC

Risk stratificationUpper tract urothelial cancerRadical nephroureterectomyNephron-sparing procedureLow-grade tumors

LowerView Articles
Lower urinaryView Articles

Volume 8, Supplement 4Review Articles

The Evolution of Alpha-Blockers for the Treatment of Benign Prostatic Hyperplasia

Advances in Alpha-Blocker Therapy in the Management of Urological Disorders

Herbert Lepor

Alpha-blockers have been evaluated for the treatment of benign prostatic hyperplasia (BPH) for 30 years, from early trials with the nonselective a-inhibitor phenoxybenzamine to short-acting (prazosin) then long-acting (terazosin, doxazosin, tamsulosin, alfuzosin) selective a1-antagonists. All of the a-blockers evaluated have demonstrated comparable effectiveness, and the evolution of a-blocker therapy for BPH has therefore focused primarily on improving convenience and tolerability. Although all of the long-acting a1-blockers are well tolerated, only tamsulosin and alfuzosin SR are administered without the requirement for dose titration. Alfuzosin has the additional advantage over tamsulosin of a lower incidence of ejaculatory dysfunction. Studies of subtype-selective a1-antagonists have not demonstrated superior efficacy or improved tolerability over the existing long-acting a1-blockers. [Rev Urol. 2006;8(suppl 4):S3-S9]

Benign prostatic hyperplasiaBlockersLower urinary

Lower urinary obstructionView Articles
Lower urinary tractView Articles
Lower urinary tract symptomsView Articles
Lower urinary tract symptoms (LUTS)View Articles
Lower urinary tractsymptomsView Articles
Luteinizing hormoneView Articles
Luteinizing hormone releasing hormoneView Articles
Luteinizing hormone releasing hormone agonistView Articles
Lymph nodeView Articles
Lymph node dissectionView Articles
Lymph node metastasesView Articles

Volume 12, Number 1Review Articles

Complications of Pelvic Lymphadenectomy: Do the Risks Outweigh the Benefits?

Treatment Review

Alan W PartinEdward M SchaefferStacy Loeb

The American Urological Association Best Practice Policy states that although pelvic lymph node dissection (PLND) is commonly done with radical prostatectomy, its morbidity must be considered, particularly in cases in which it offers little additional information. The benefits of PLND include more accurate staging and reassurance for the patient. In addition, PLND may be therapeutic for men with lymph node metastases and may result in long-term biochemical cure for selected node-positive patients. However, the incidence of node positivity is declining, and accordingly a greater number of lymphadenectomies must be performed to benefit 1 patient. In addition to the associated cost, PLND has the potential for morbidity, including lymphoceles, thromboembolic events, ureteral injury, and neurovascular injury. Patients and physicians should therefore assess the risk/benefit ratio associated with PLND on an individual basis to permit informed treatment decisions.[Rev Urol. 2010;12(1):20-24 doi:10.3909/riu0422]

Prostate cancerRadical prostatectomyPelvic lymph node dissectionUreteral injuryLymph node metastasesRisk to benefit ratioLymphoceleThromboembolic eventsVascular injuryNerve injury

Lymph node metastasisView Articles

Volume 8, Supplement 1Review Articles

The Emergence of Radioimmunoscintigraphy for Prostate Cancer

Prostate Cancer Imaging

David G McLeodThomas E KeaneInger L RosnerM Scott Wingo

The ability to label tissue-specific antibodies has long been of interest for improving detection and guidance for therapeutic applications. The most studied target for prostate cancer is the prostate-specific membrane antigen, which is upregulated in prostate cancer, hormone-refractive disease, and prostate cancer metastases. Investigations using radioimmunoscintigraphy with the radiolabeled 7E11 antibody capromab pendetide have significantly improved sensitivity for prostate cancer detection compared with standard cross-sectional imaging, based on tissue confirmation of pathologic results. Over the past 5 years, significantly greater image resolution from improved camera technology and the use of co-registration to fuse functional and anatomic (computerized tomography and magnetic resonance imaging) images have dramatically enhanced prostate cancer localization. Outcomes data from several sources have spurred a resurgence in interest in this imaging modality. [Rev Urol. 2006;8(suppl 1):S20-S28]

Prostate cancerProstaScintProstate-specific membrane antigenRadioimmunoscintigraphyCapromab pendetideImage co-registrationLymph node metastasis

LymphadenectomyView Articles
LymphoceleView Articles

Volume 12, Number 1Review Articles

Complications of Pelvic Lymphadenectomy: Do the Risks Outweigh the Benefits?

Treatment Review

Alan W PartinEdward M SchaefferStacy Loeb

The American Urological Association Best Practice Policy states that although pelvic lymph node dissection (PLND) is commonly done with radical prostatectomy, its morbidity must be considered, particularly in cases in which it offers little additional information. The benefits of PLND include more accurate staging and reassurance for the patient. In addition, PLND may be therapeutic for men with lymph node metastases and may result in long-term biochemical cure for selected node-positive patients. However, the incidence of node positivity is declining, and accordingly a greater number of lymphadenectomies must be performed to benefit 1 patient. In addition to the associated cost, PLND has the potential for morbidity, including lymphoceles, thromboembolic events, ureteral injury, and neurovascular injury. Patients and physicians should therefore assess the risk/benefit ratio associated with PLND on an individual basis to permit informed treatment decisions.[Rev Urol. 2010;12(1):20-24 doi:10.3909/riu0422]

Prostate cancerRadical prostatectomyPelvic lymph node dissectionUreteral injuryLymph node metastasesRisk to benefit ratioLymphoceleThromboembolic eventsVascular injuryNerve injury

Lymphovascular invasionView Articles

Volume 9, Number 4Meeting Reviews

Best of the 2007 AUA Annual Meeting (2)

Meeting Review

John P Stein

Bladder Cancer Highlights from the 2007 Annual Meeting of the American Urological Association, May 19-24, 2007, Anaheim, CA [Rev Urol. 2007;9(4):220-234]

Bladder cancerQuality of lifeRisk factorsAgeCystectomyLaparoscopic surgeryIntravesical therapyPrognosisCystoscopyGenderInvasive cancerLymph node dissectionLymphovascular invasionMetastatic cancerOutcomesRepeat TURRobotic-assisted surgerySuperficial cancer

Machine learningView Articles

Volume 22, Number 4Review Articles

Application of Artificial Intelligence/Machine Vision & Learning for the Development of a Live Single-cell Phenotypic Biomarker Test to Predict Prostate Cancer Tumor Aggressiveness

Original Research

David M. AlbalaGrannum R SantJonathan S VarsanikMichael S ManakMatthew J WhitfieldBrad J HoganWendell R SuCJ JiangAshok C Chander

To 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®, LLC

Prostate cancerArtificial intelligencePhenotypic biomarkersMachine visionMachine learning

Machine visionView Articles

Volume 22, Number 4Review Articles

Application of Artificial Intelligence/Machine Vision & Learning for the Development of a Live Single-cell Phenotypic Biomarker Test to Predict Prostate Cancer Tumor Aggressiveness

Original Research

David M. AlbalaGrannum R SantJonathan S VarsanikMichael S ManakMatthew J WhitfieldBrad J HoganWendell R SuCJ JiangAshok C Chander

To 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®, LLC

Prostate cancerArtificial intelligencePhenotypic biomarkersMachine visionMachine learning

Magnetic resonance imagingView Articles
Magnetic resonance imaging (MRI)View Articles

Volume 23, Number 4Prostate Cancer

Deep Learning for Magnetic Resonance Imaging–Based Radiation Therapy for Prostate Cancer: Current Status

Jessica E. ScholeyAbhejit RajagopalJulian HongPeder LarsonKe Sheng

Magnetic resonance imaging (MRI) is increasingly being used for external beam radiation therapy in the treatment of prostate cancer because of its excellent soft tissue contrast and ability to provide functional and physiologic information about tumor behavior. At the same time, deep learning has seen widespread applications in medical imaging, including for MRI-based classification and synthesis. Deep learning–based approaches are being incorporated into the MRI-guided clinical external beam radiation therapy workflow for patient simulation, contouring of targets and critical structures, treatment planning, and treatment delivery. In this review, we examine the current status of deep learning for MRI-guided prostate external beam radiation therapy.

Artificial intelligenceProstatic neoplasmsRadiotherapyMagnetic resonance imaging (MRI)Deep Learning

Magnetic resonance spectroscopyView Articles
Magnetic resonanceimagingView Articles

Volume 8, Number 3Review Articles

The Importance of Pelvic Lymph Node Dissection in Men With Clinically Localized Prostate Cancer

Diagnostic Review

Alan W PartinH Ballentine CarterMohamad E Allaf

Despite advances in noninvasive staging, pelvic lymph node dissection (PLND) remains the most accurate means of detecting lymph node metastases in men with clinically localized prostate cancer. Nomograms exist that can identify patients at low risk for lymphatic metastases according to preoperative information. In general, it seems reasonable to omit PLND in men with a biopsy Gleason sum of 6 or less and a prostate-specific antigen level of 10 ng/mL or less. Ultimately, however, this decision should be made according to physician and patient preference, considering the low contemporary morbidity associated with PLND. When PLND is performed, studies suggest that an extended dissection maximizes the detection rate of nodal involvement. Retrospective data indicate that an extended dissection might play a therapeutic role in a subset of patients with a limited lymph node burden. However, this might be an artifact of stage migration, and prospective studies are needed to evaluate this further. [Rev Urol. 2006;8(3):112-119]

Prostate cancerNomogramsRadioimmunoscintigraphyLymphadenectomyClinical stagingMagnetic resonanceimagingAlgorithms

Male genital tuberculosisView Articles

Volume 10, Number 3Review Articles

Urogenital Tuberculosis: Update and Review of 8961 Cases from the World Literature

Treatment Update

André A FigueiredoAntonio M Lucon

The AIDS epidemic caused unexpected worldwide levels of tuberculosis, even in developed countries where the incidence used to be low. Patients with urogenital tuberculosis in developed countries have fewer specific symptoms and lower rates of delayed diagnoses compared with patients from other countries. As a result, the disease tends to be less serious, with more patients presenting without significant lesions of the upper urinary tract on diagnosis. These data point to a correlation of the timing of diagnosis with the severity of urogenital tuberculosis. A systematic search for urogenital tuberculosis, regardless of symptoms, is warranted for early detection. [Rev Urol. 2008;10(3):207-217]

CystitisNephrectomyMale genital tuberculosisTuberculosis, urogenitalTuberculosis, renalUrinary bladder, surgery

Male hot flashesView Articles

Volume 9, Number 4Review Articles

Estrogenic Side Effects of Androgen Deprivation Therapy

Treatment Update

Michael S CooksonJames A EasthamTheresa A GuiseMichael G OefeleinMatthew R SmithCelestia Higano

Androgen deprivation therapy (ADT) is part of standard therapy for locally advanced or metastatic prostate cancer and is frequently used in men with a rising prostate-specific antigen following radical prostatectomy or radiation therapy. In some men, ADT may be administered for years or even decades. The intended therapeutic effect of ADT is testosterone deficiency. Because estrogen is a normal metabolite of testosterone, ADT also results in estrogen deficiency. ADT has a variety of adverse effects, many of which are primarily related to estrogen deficiency. Bone mineral density may decrease by 4% to 13% per year in men receiving ADT. The fracture rate for patients on ADT averages 5% to 8% per year of therapy. Hot flashes, gynecomastia, and breast tenderness are common side effects associated with ADT. In the clinic, minimum baseline testing should include weight measurement, blood pressure reading, and fasting lipid panel and serum glucose tests. Currently, there are no large outcome trials in men on ADT testing the available therapies for adverse effects. No therapies are specifically approved for treatment of adverse effects in men on ADT. Although some therapies can be used for a single indication (based upon small studies), there is currently no agent to treat the multiple estrogenic side effects of ADT. [Rev Urol. 2007;9(4):163-180]

Androgen deprivation therapyCardiovascular diseaseGynecomastiaOsteoporosis fractureMale hot flashes

Male infertilityView Articles
Male osteoporosisView Articles