Urethrocutaneous fistulas (UCF) after hypospadias repair are typically managed surgically, but conservative approaches may offer a less invasive, cost-effective alternative. While surgical repair remains the standard, non-operative strategies may eliminate anesthesia exposure, shorten recovery time, and lower healthcare costs. However, systematic evidence regarding these approaches remains limited. This narrative systematic review evaluates non-operative management for small (typically ≤ 2 mm) UCFs. A comprehensive search was conducted across PubMed, Cochrane, ScienceDirect, Wiley, and Google Scholar up to April 2025. The study followed PRISMA guidelines and is registered in PROSPERO (CRD420251069870). We included randomized controlled trials (RCTs), comparative trials, case series, and anecdotal reports involving children (< 18 years). Risk of bias was assessed using Cochrane RoB-2, ROBINS-I, and JBI Critical Appraisal tools. Five studies involving 73 patients were included for analysis. Due to significant clinical heterogeneity in fistula characteristics and interventions, a pooled closure rate was not calculated. Reported individual study closure rates ranged from 53.8

Kidney stone diseases (KSDs) are one of the oldest documented renal conditions, with cases tracing back to ancient history. Due to its recurrent nature, KSDs often require patients to undergo lifelong periodic monitoring. Artificial intelligence can automate and speed up the tracking of kidney stone presence, growth, and location. Computed tomography (CT) remains one of the most widely used methods for KSD diagnosis. However, accurately segmenting kidney stones within a full abdominal CT scan is challenging because of their small size, necessitating extensive scope reduction to enable the deep learning (DL) model to focus on the relevant regions. While traditional saliency-map-based localization provides a general estimate of stone location, it lacks precise details on the stone’s size, shape, and specific position within the renal cortex. Addressing these limitations, this study introduces a dual-stage, DL-based framework for efficient kidney stone segmentation from CT slices. First, the dataset scope is reduced using the proposed successive scope reduction (SSR) method, sequentially narrowing the kidney and stone focus for enhanced accuracy. With the successive scope reduction network (SSRNet) classification model, an overall F1-score of 94.45% is achieved for scope reduction. On the scope-reduced dataset, the kidney stone segmentation network (KSSNet) model reaches a dice score of 97.44% and a Jaccard index of 95.01% for stone segmentation, significantly surpassing existing benchmarks. The proposed framework is robust, with subject-independent evaluations and ablation studies confirming its reliability and computational efficiency, and the proposed models surpassing the state-of-the-art in respective domains, supporting its application in a real-world clinical setup.

The formation of the external genitalia of the male is a complex developmental process. The SRY region on the Y chromosome causes the undifferentiated gonads to differentiate and produce testosterone (Leydig cells) and anti-Müllerian hormone (Sertoli cells). It starts in the fourth gestational week with the appearance of the genital tubercle. The genital tubercle elongates, while the urogenital sinus gives rise to the urethral plate (which tubularizes) and the labioscrotal folds fuse to form the scrotum, all under the influence of testosterone produced by the testes, which has been converted to dihydrotestosterone by the action of 5-alpha reductase. This chapter covers the embryology of the penis and urethra. Many of the common conditions that affect the prepuce (foreskin), buried penis, hypospadias, and urethral conditions are congenital abnormalities where normal development has not occurred.

Renal cortical abnormalities frequently signify severe kidney conditions, rendering their precise diagnosis crucial for clinical management and treatment strategy formulation. Nonetheless, manual evaluation of nuclear renal imaging is arduous and prone to considerable inter-observer variability, resulting in conflicting results. This paper presents a fully automated method for the differential detection of renal cortical anomalies via deep learning-based segmentation and classification. Initially, we generated an innovative compilation of rigorously annotated renal nuclear images from 613 patients. Among them 193 patients are primarily diagnosed with kidney scar. Utilizing this dataset, we devised a novel segmentation method to precisely identify and outline renal areas. The proposed DenseNet121_Self-ONN_FPN model combines the DenseNet121 backbone, Self-Organizing Neural Network (Self-ONN) layers in the Feature Pyramid Network (FPN) for enhanced performance in segmentation tasks achieving impressive results: an Accuracy of 98.74

Objective To synthesize and quantitatively analyze available evidence regarding sexual function in adults who underwent hypospadias repair during childhood. Methods A systematic review and meta-analysis were conducted based on PRISMA guidelines to assess long-term outcomes of hypospadias repair on adult sexual function. Studies were evaluated for methodological quality, surgical techniques, patient demographics, and primary outcomes related to erectile function, sexual satisfaction, and psychosexual health. Meta-analytic methods were employed to calculate pooled incidences and heterogeneity of key outcomes. Results Thirteen studies were included in the review, with pooled analyses revealing an overall incidence of erectile dysfunction at 12% (95% CI: 7%-19%) and sexual dissatisfaction at 16% (95% CI: 12%-22%). Most studies demonstrated favorable outcomes in erectile function and sexual satisfaction, although variability in outcomes was noted across subgroups. Meta-analysis highlighted significant heterogeneity due to differences in surgical techniques, patient populations, and follow-up durations. Conclusion Hypospadias repair during childhood generally leads to positive long-term sexual function outcomes. However, approximately 12%-16% of individuals may experience persistent challenges. Standardization of outcome measures and long-term follow-up studies are essential to refine surgical approaches and improve patient care.

BACKGROUND:Penile curvature (PC) may occur in up to 10 % of male births worldwide and is typically associated with the birth defect hypospadias. While the extent of PC impacts surgical management and patient outcomes, curvature evaluation is inconsistent between surgeons due to a lack of reliable assessment techniques. Our goal was to create a dependable, automated deep-learning solution to precisely assess PC from real-time intraoperative 2D images. MATERIALS AND METHODS:A dataset of 421 images was assembled and annotated by four human experts. Annotations were used to calculate PC angles and determine ground truth curvature degrees in each case. All images and ground truth angle information were used to train 3 different deep-learning models. A YOLOv8 model was trained to localize and crop the penile region, then a deep-learning model was employed to segment the shafts and generate binary mask images. In the final stage, a modified HRNet model was used to integrate angle error, predict four key points denoting mid-axes of the proximal and distal shaft, and then use these landmarks to calculate curvature automatically. RESULTS:The proposed system demonstrated a high level of reliability in localizing penile areas, as evidenced by a mean average precision score of 99.4 %. Furthermore, our pipeline exhibited strong performance in the segmentation task, achieving an impressive Intersection over the Union metric of 83.56 % and a Dice Similarity Coefficient of 91.02 %. In terms of angle prediction, the system achieved a mean absolute error of 7.9°. By comparison, variability among human raters ranged between 6.5 and 12.0° (median ≈ 8.9°), consistent with previously reported manual errors of 3.5-13.6°. Thus, the AI system matched or outperformed human raters, providing more consistent and reliable curvature estimation. The model achieved a median error of 7.8° across 421 images, with 82 % of predictions within ±10° of ground truth. Only 6 % of cases crossed the 30° surgical threshold, confirming the tool's reliability for clinical decision-making. DISCUSSION:This study demonstrates the successful implementation of deep learning and keypoint-based measurement of PC that could significantly improve patient assessment by surgeons and hypospadiology researchers.

BACKGROUND:Hypospadias-associated ventral curvature (VC) exerts a critical influence on surgical decision-making and repair outcomes. Despite the clinical significance of VC, assessment is frequently performed by unaided visual inspection (UVI) which is prone to error. Alternative objective measurement techniques have therefore been proposed, including goniometry, smartphone applications, and artificial intelligence (AI)-based tools. OBJECTIVE:This review aims to evaluate the various techniques available for VC measurement in hypospadias surgery, focusing on their accuracy, reliability, and clinical utility. METHODS:A comprehensive literature search was conducted using PubMed, MEDLINE, and the Cochrane Database, covering publications from 1994 to 2024. Included studies assessed VC measurement techniques, including UVI, standard goniometry, smartphone-based goniometry, and AI-based tools. Risk of bias was determined using the Robvis tool. RESULTS:Of 501 studies identified, 13 met the inclusion criteria. Findings revealed that UVI was associated with significant inaccuracy, leading to misclassification of VC severity and potential errors in surgical planning. Standard goniometry, while objective, was cumbersome in pediatric patients due to parallax errors and anatomical constraints. Smartphone-based goniometry provided improved accuracy and interobserver reliability. AI-based methods demonstrated the highest precision by minimizing subjectivity and enhancing standardization. CONCLUSION:Objective measurement techniques, particularly smartphone-based and AI-driven approaches, are superior to UVI in assessing penile curvature in hypospadias. Future advances in AI technology and digital imaging may further refine VC assessment, leading to improved surgical outcomes. Adoption of standardized, objective measurement methods should be encouraged in clinical practice.

Introduction Hypospadias is a prevalent congenital anomaly that requires effective parental education. Current online resources often exceed recommended readability levels, potentially hindering understanding. This study evaluates the utility of ChatGPT in providing accurate, clear, and actionable information towards parental education about hypospadias. Methods A structured set of questions was posed to ChatGPT 4.0 covering diagnosis, treatment options, and postoperative care. Responses were quantitatively assessed using the Patient Education Material Assessment Tool for Printable Materials (PEMAT-P) to measure understandability and actionability. Qualitative evaluations were conducted by six pediatric urologists who rated the information for accuracy on a scale from 1 (completely accurate) to 4 (completely inaccurate). The Fleiss' Kappa statistic was calculated to assess inter-observer agreement among the urologists. Results The quantitative assessment yielded understandability scores between 84% and 92% (average 88%), while actionability scores ranged from 37% to 70% (average 51%). In the qualitative assessment, 41% of responses were deemed completely accurate, with 35% considered accurate but inadequate, and 24% rated as inaccurate. The overall Kappa value was 0.607, indicating substantial agreement among reviewers regarding the accuracy of the information provided by ChatGPT. Conclusion ChatGPT can effectively convey information about hypospadias, but enhancing the actionability of its responses is crucial. Inaccuracy is still a main concern in using AI-generated search engine. Future updates should include more accurate and reliable responses and visual aids addition may support parents in navigating their child’s care.

OBJECTIVE:To develop and evaluate a deep learning framework for automatic kidney and fluid segmentation in renal ultrasound images, aiming to enhance diagnostic accuracy and reduce variability in hydronephrosis assessment. METHODS:A dataset of 1731 renal ultrasound images, annotated by four experienced urologists, was used for model training and evaluation. The proposed framework integrates a DenseNet201 backbone, Feature Pyramid Network (FPN), and Self-Organizing Neural Network (SelfONN) layers to enable multi-scale feature extraction and improve spatial precision. Several architectures were tested under identical conditions to ensure a fair comparison. Segmentation performance was assessed using standard metrics, including the Dice coefficient, precision, and recall. The framework also supported hydronephrosis classification using the fluid-to-kidney area ratio, with a threshold of 0.213 derived from prior literature. RESULTS:The model achieved strong segmentation performance for kidneys (Dice: 0.92, precision: 0.93, recall: 0.91) and fluid regions (Dice: 0.89, precision: 0.90, recall: 0.88), outperforming baseline methods. The classification accuracy for detecting hydronephrosis reached 94%, based on the computed fluid-to-kidney ratio. Performance was consistent across varied image qualities, reflecting the robustness of the overall architecture. CONCLUSION:This study presents an automated, objective pipeline for analyzing renal ultrasound images. The proposed framework supports high segmentation accuracy and reliable classification, facilitating standardized and reproducible hydronephrosis assessment. Future work will focus on model optimization and incorporating explainable AI to enhance clinical integration.

Introduction:Vesicoureteral reflux (VUR) is a prevalent pediatric urological condition that increases children's risk of urinary tract infections (UTIs) and renal damage. Renal scarring linked to VUR can lead to long-term complications, including hypertension and chronic kidney disease (CKD). Although traditional imaging techniques, such as dimercaptosuccinic acid (DMSA) scans, are regarded as the gold standard for identifying renal scarring, they come with risks of radiation exposure and high costs. This review investigates the diagnostic accuracy of blood and urine biomarkers as alternative methods for detecting renal scarring in VUR. Methods:This systematic review adhered to the PRISMA 2020 guidelines. We conducted a comprehensive search across three databases-PubMed, ScienceDirect, and Cochrane-for studies on biomarkers associated with renal scarring in children with VUR. The included studies were evaluated for diagnostic accuracy (sensitivity and specificity) and assessed for risk of bias using the QUADAS-2 framework. Results:Nine studies met the eligibility criteria and were included in the qualitative synthesis. Biomarkers such as NGAL, CRP, CXCL8/IL-8, LL-37, and IL-6 were evaluated. Among these, urinary NGAL demonstrated the best diagnostic performance, with sensitivity ranging from 72%-84% and specificity between 60% and 81%. Other biomarkers exhibited moderate accuracy, although they were less reliable than NGAL. Overall, biomarkers present a promising non-invasive alternative to traditional imaging for detecting renal scarring in children with VUR. Conclusion:Urinary biomarkers, particularly NGAL, hold potential for detecting VUR and renal scarring in children, providing a non-invasive alternative to traditional imaging methods. However, additional validation and standardization are necessary before these biomarkers can be routinely applied in clinical practice.

Technetium-99m dimercaptosuccinic acid (DMSA) scintigraphy plays a critical role in pediatric imaging for detecting renal cortical scarring, which is essential for diagnosing and managing kidney damage in children. However, variability in observer interpretation poses challenges, potentially impacting clinical decision-making and outcomes. This study aims to assess intra- and inter-observer agreement in interpreting DMSA scans for detecting renal cortical scarring in pediatric patients, focusing on the presence, location, and percentage of kidney involvement. This prospective study analyzed 220 pediatric patients with suspected renal scarring. Four experienced radiologists independently reviewed DMSA scans on two separate occasions, 3–4 weeks apart, using standardized assessment criteria. Intra-observer agreement was measured using Cohen’s kappa, while inter-observer agreement was assessed using pairwise Cohen’s kappa for categorical evaluations and Kendall’s tau-b for the percentage of kidney involvement. Strong intra-observer agreement was observed across all four radiologists, with Cohen’s kappa values for renal scarring stages ranging from 0.704 to 0.955. Observer-4 consistently showed the highest agreement across all metrics. Inter-observer agreement varied substantially depending on observer pairs. Pairs excluding Observer-2 demonstrated moderate to substantial agreement (kappa up to 0.8268 and Kendall’s tau-b up to 0.7192), while pairs involving Observer-2 showed poor to slight agreement. Variability was particularly notable in assessing scarring severity and defect localization. While intra-observer consistency in interpreting DMSA scans is high, inter-observer variability remains a concern, especially in evaluating the severity and location of renal scarring. These findings underscore the need for standardized protocols and targeted training to enhance diagnostic accuracy. Moreover, the development of validated datasets could support the advancement of machine learning models for automated, precise detection of renal scarring, ultimately improving diagnostic reliability and patient outcomes.

Background The exact cause of penile curvature in hypospadias remains unknown. Resection of the dartos fascia has been observed to straighten the penis, indicating the involvement of the dartos fascia in the superficial chordee. However, the characteristics of dartos tissue in the distal territory of the ventral penile shaft may differ from those in the proximal aspect of the penile shaft. Objective This study aims to investigate the distinct histopathological profiles and expression of COL1A1 (collagen type 1), COL3A1 (collagen type 3), and ELN (elastin) in proximal and distal ventral dartos of patients with hypospadias compared to those without hypospadias. Methods This prospective case-control study compares the ventral dartos tissue of patients with hypospadias at different locations with that of patients without hypospadias. Dartos samples will be taken during surgery, with age matching. Histopathology examination uses hematoxylin and eosin and Masson’s trichrome stain. The mRNA expression of COL1A1, COL3A1, and ELN will be quantified using a 2-step reverse transcription–polymerase chain reaction analysis. Results Previous studies have documented different characteristics of dartos tissue between patients with hypospadias and those without hypospadias. Some studies even suggest resection of the dartos tissue during hypospadias repair. However, this is the first study to compare the characteristics of ventral dartos tissue in patients with hypospadias based on its location along the penile shaft, suggesting potential differences between the distal and proximal locations. We have obtained ethical approval to conduct a prospective case-control study aimed at elucidating these differences in dartos tissue characteristics. The findings of the study are anticipated to be available by 2025. Conclusions Differences in the characteristics of dartos fascia based on its location may require tailored surgical strategies. If the properties of distal dartos tissue closely mirror those of typical dartos tissue, the possibility of avoiding its excision during hypospadias surgery could be considered. International Registered Report Identifier (IRRID) DERR1-10.2196/70075

OBJECTIVE To objectively evaluate technical skill acquisition in hypospadias repair procedures during surgical training using noninvasive wearable sensor technology. METHODS We combined subjective video evaluations with objective electromyography (EMG) measurements in a hands-on hypospadias training course. Surgeons wore wireless EMG and accelerometer sensors on their dominant hand while performing tasks on ex-vivo cadaveric calf penises. The study focused on 4 skills as follows: urethral mobilization, dorsal inlay graft harvest/ implantation, meatal-based flap urethroplasty, and dorsal plication. Machine learning techniques analyzed muscle activation patterns and attributes for assessing surgical precision. RESULTS The course included 18 participants (10 female, 8 males; average age 40.18 +/- 8.46 years) categorized as novice (n = 10, < 3 years' experience), intermediate (n = 5, 3-5 years), and expert (n = 3, > 5 years). Video evaluations did not reveal significant differences due to short-term training. However, EMG measurements showed significant reductions in average EMG power, total time, dominant frequency, and cumulative muscle workload after training. Additionally, the mean power spectral density of the EMG signal decreased notably post-training. CONCLUSION This study presents a structured approach for hypospadias training and highlights the effectiveness of wearable sensor technology for objective skill assessment. While video evaluations did not detect significant changes, EMG data provided measurable differences in skill acquisition, suggesting that wearable sensors could enhance objective evaluations of surgical proficiency in residency programs.

INTRODUCTION:Artificial intelligence (AI) is increasingly being applied across pediatric urology. We provide a living scoping review and online repository developed by the AI in PEDiatric UROlogy (AI-PEDURO) collaborative that summarizes the current and emerging evidence on the AI models developed in pediatric urology. MATERIAL AND METHODS:The protocol was published a priori, and Preferred Reporting Items for Systematic Review and Meta-analysis Scoping Review (PRISMA-ScR) guidelines were followed. We conducted a comprehensive search of four electronic databases and reviewed relevant data sources from inception until June 2024 to identify studies that have implemented AI for prediction, classification, or risk stratification for pediatric urology conditions. Model quality was assessed by the APPRAISE-AI tool. RESULTS:Overall, 59 studies were included in this review from 1557 unique records. Of the 59 published studies, 44 studies (75 %) were published after 2019, with hydronephrosis and vesicoureteral reflux/urinary tract infection as the most common topics (17 studies, 28 % each). Studies originated from USA (22 studies, 37 %), Canada (10 studies, 17 %), China (8 studies, 14 %), and Turkey (7 studies, 12 %). Neural network (35 studies, 59 %), support-vector-machine (21 studies, 36 %), and tree-based models (19 studies, 32 %) were the most used machine learning algorithms, with 14 studies (24 %) providing useable repositories or applications. APPRAISE-AI assessed 12 studies (20 %) of studies as low quality, 39 studies (66 %) as moderate quality, and 8 studies (14 %) as high quality, with specific improvements noted in model robustness and reporting standards over time (p = 0.03). Findings were synthesized into an online repository (www.aipeduro.com). DISCUSSION:There is an increasing pace of AI model development in pediatric urology. Model topics are broad, algorithm choice is diverse, and the overall quality of models are improving over time. While there is still a lack of clinical translation of the AI models in pediatric urology, the usage of online repositories and reporting frameworks can facilitate sharing, improvement, and clinical implementation of future models. CONCLUSIONS:This living scoping review and online repository will highlight the current landscape of AI models in pediatric urology and facilitate their clinical translation and inform future research initiatives. From this work, we provide a summary of recommendations based on the current literature for future studies.

Tubularized incised plate (TIP) urethroplasty is widely used for distal hypospadias but may be suboptimal in patients with narrow or scarred urethral plates. Grafted TIP (GTIP), incorporating a dorsal inlay graft, is an emerging alternative to improve outcomes in such cases. To describe the indications, techniques, outcomes, and evolving perspectives on inlay graft use in distal hypospadias repair. A narrative review was conducted using published studies, prospective trials, and network meta-analyses comparing TIP and GTIP outcomes, with attention to complication rates, functional results, and decision-making tools. GTIP offers superior healing and reduced complications in patients with unfavorable urethral plates. While operative time is longer, uroflowmetry and cosmetic outcomes are comparable. Technical success relies on graft type, accurate incision, and tension-free multilayer closure. GTIP represents a valuable adaptation of TIP for selected patients with distal hypospadias. GTIP should be considered when urethral plate characteristics predict poor healing. Further prospective studies are warranted to validate its long-term outcomes.

Background/Objectives: Hypospadias, a common congenital anomaly in males, presents significant challenges in diagnosis, management, and long-term care. Despite its prevalence, research into the condition has been hampered by the lack of integrated biobank cohorts linking clinical, phenotypic, and surgical data with biological samples. This study aimed to establish the Hypospadias Biobank Cohort (HBC), a comprehensive resource designed to advance the understanding of hypospadias etiology and improve patient outcomes. Methods: The HBC was developed using a multi-phase approach, enrolling participants from specialized clinics between April 2022 and September 2024. Biological samples (blood and tissue) were collected under standardized protocols following informed consent. Detailed clinical data, including hypospadias severity, associated anomalies, and surgical outcomes, were systematically recorded and integrated into a robust database to support translational research. Results: The cohort included a diverse group of patients with varying severity of hypospadias, many of whom also presented with associated anomalies. Surgical outcomes were tracked, revealing important correlations between severity and postoperative complications. Preliminary biological analyses identified potential biomarkers associated with hypospadias severity and recovery. The full details of these results will be presented in a separate publication. The comprehensive database is continuously updated with longitudinal follow-up data, supporting future translational research. Conclusions: The Hypospadias Biobank Cohort represents a groundbreaking resource for translational research, offering unprecedented insights into the clinical and phenotypic spectrum of hypospadias. By enabling the refinement of classification systems and the development of evidence-based surgical techniques, the HBC has the potential to transform the management of this congenital condition. Ongoing research leveraging the HBC will further unravel the complex interplay among clinical presentation, surgical interventions, and patient outcomes, paving the way for personalized care strategies and improved long-term results.