Indian Journal of Urology最新文献

{"title":"What's inside.","authors":"Abhishek Gajendra Singh","doi":"10.4103/iju.iju_366_24","DOIUrl":"https://doi.org/10.4103/iju.iju_366_24","url":null,"abstract":"","PeriodicalId":47352,"journal":{"name":"Indian Journal of Urology","volume":"40 4","pages":"218-220"},"PeriodicalIF":1.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567585/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142649302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond the horizon: Immune checkpoint inhibitors reshaping the landscape of urothelial cancer.","authors":"Ojas Patel","doi":"10.4103/iju.iju_51_24","DOIUrl":"10.4103/iju.iju_51_24","url":null,"abstract":"","PeriodicalId":47352,"journal":{"name":"Indian Journal of Urology","volume":"40 4","pages":"283-284"},"PeriodicalIF":1.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567570/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142649007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Challenges facing children with neurogenic lower urinary tract dysfunction in India.","authors":"Sanjay Sinha","doi":"10.4103/iju.iju_333_24","DOIUrl":"10.4103/iju.iju_333_24","url":null,"abstract":"","PeriodicalId":47352,"journal":{"name":"Indian Journal of Urology","volume":"40 4","pages":"213-214"},"PeriodicalIF":1.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567590/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142649016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The use of amniotic membrane injection as an adjunct in endoscopic urethral stricture management.","authors":"Nicholas Pryde, Jack Vercnocke, Jonathan Lutchka, Aron Liaw, Michael Sessine, Nivedita Dhar","doi":"10.4103/iju.iju_88_24","DOIUrl":"10.4103/iju.iju_88_24","url":null,"abstract":"<p><strong>Introduction: </strong>Endoscopic urethral stricture treatment has high recurrence rates. Due to research supporting amniotic membrane's (AMs) anti-inflammatory and anti-fibrotic properties reducing scar tissue formation, AM has generated interest in reconstructive urethral surgery. To the best of our knowledge, we performed the first investigation of the success rate of urethral dilation when combined with micronized AM injection for the treatment of urethral stricture.</p><p><strong>Methods: </strong>Eligible patients were adult males with anterior strictures meeting strict criteria for diameter, length, International Prostate Symptom Score (IPSS), and flow rate. Micronized AM was injected in the stricture region during urethral dilation. The primary study endpoint was an anatomical success (≥14Fr) at 6 months. Secondary endpoints were evaluated with the IPSS, urethral stricture surgery - patient-related outcome measure, International Index of Erectile Function, flow rate, and postvoid residual. Outcomes were assessed at baseline and multiple points postinjection. Injection safety was analyzed.</p><p><strong>Results: </strong>Ten men with a mean age of 52 years were included in the study. At 6 months, 7 of 10 patients demonstrated recurrence of the urethral stricture on cystoscopy. Improvements in secondary endpoints were noted in 10 of 10 patients at 3 months and 3 of 10 patients at 6 months. No adverse events were observed.</p><p><strong>Conclusions: </strong>To the best of our knowledge, this is the first study evaluating micronized AM injection as an adjunct treatment at the time of urethral dilation. The urethral stricture recurrence rate did not improve with the injection of AM despite the hypothesized benefits of anti-fibrotic and anti-inflammatory properties.</p>","PeriodicalId":47352,"journal":{"name":"Indian Journal of Urology","volume":"40 4","pages":"256-258"},"PeriodicalIF":1.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567591/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142649299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can artificial intelligence aid the urologists in detecting bladder cancer?","authors":"Antoninus Hengky, Stevan Kristian Lionardi, Christopher Kusumajaya","doi":"10.4103/iju.iju_39_24","DOIUrl":"10.4103/iju.iju_39_24","url":null,"abstract":"<p><strong>Introduction: </strong>The emergence of artificial intelligence (AI)-based support system endoscopy, including cystoscopy, has shown promising results by training deep learning algorithms with large datasets of images and videos. This AI-aided cystoscopy has the potential to significantly transform the urological practice by assisting the urologists in identifying malignant areas, especially considering the diverse appearance of these lesions.</p><p><strong>Methods: </strong>Four databases, the PubMed, ProQuest, EBSCOHost, and ScienceDirect were searched, along with a manual hand search. Prospective and retrospective studies, experimental studies, cross-sectional studies, and case-control studies assessing the utilization of AI for the detection of bladder cancer through cystoscopy and comparing with the histopathology results as the reference standard were included. The following terms and their variants were used: \"artificial intelligence,\" \"cystoscopy,\" and \"bladder cancer.\" The risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A random effects model was used to calculate the pooled sensitivity and specificity. The Moses-Littenberg model was used to derive the Summary Receiver Operating Characteristics (SROC) curve.</p><p><strong>Results: </strong>Five studies were selected for the analysis. Pooled sensitivity and specificity were 0.953 (95% confidence interval [CI]: 0.908-0.976) and 0.957 (95% CI: 0.923-0.977), respectively. Pooled diagnostic odd ratio was 449.79 (95% CI: 12.42-887.17). SROC curve (area under the curve: 0.988, 95% CI: 0.982-0.994) indicated a strong discriminating power of AI-aided cystoscopy in differentiation normal or benign bladder lesions from the malignant ones.</p><p><strong>Conclusions: </strong>Although the utilization of AI for aiding in the detection of bladder cancer through cystoscopy remains questionable, it has shown encouraging potential for enhancing the detection rates. Future studies should concentrate on identification of the patients groups which could derive maximum benefit from accurate identification of the bladder cancer, such as those with intermediate or high-risk invasive tumors.</p>","PeriodicalId":47352,"journal":{"name":"Indian Journal of Urology","volume":"40 4","pages":"221-228"},"PeriodicalIF":1.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567573/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142649012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Creation and evaluation of a three-dimensional-printed synthetic vas deferens for microsurgical training.","authors":"Parth Joshi, Tamar Jacobsohn, Andrew Polis, Darshi Shah, Brian Gillette, Richard Schoor","doi":"10.4103/iju.iju_185_24","DOIUrl":"10.4103/iju.iju_185_24","url":null,"abstract":"<p><strong>Introduction: </strong>Individuals choose to undergo vasectomy reversal for a variety of reasons, including remarriage or due to the death of a child. To be proficient in this procedure, the surgeons need to be high volume and the trainees require a safe environment to develop their microsurgical skills. To overcome this challenge, we used three-dimensional (3D) printing to create a synthetic model of the vas deferens with properties similar to the human vas deferens. We distributed this model to experienced microsurgeons for evaluation.</p><p><strong>Methods: </strong>The vas deferens model was created using thermoplastic polyurethane filament. The filament was then infused with a foaming agent to allow for temperature-dependent tuning of the material's stiffness. The model's outer diameter was 1 mm and the inner lumen was 0.5 mm. Fellowship-trained male reproductive urologists were recruited from the Society for the Study of Male Reproduction website. They used our model and judged it on several factors by completing a 13-question survey.</p><p><strong>Results: </strong>We received completed evaluations from five microsurgeons. Eighty percent of the surgeons were able to complete a full anastomosis on the model using 9-0 and 10-0 sutures. The majority of the completed anastomoses were performed using the one-layer technique. The average responses for the model's usefulness as a practice tool, a training tool, and overall assessment ranged from 72 to 79 out of 100. Comments for the improvement included the need for a more flexible and softer model.</p><p><strong>Conclusions: </strong>We created a 3D-printed synthetic vas deferens that serves as a valuable training and practice tool.</p>","PeriodicalId":47352,"journal":{"name":"Indian Journal of Urology","volume":"40 4","pages":"250-255"},"PeriodicalIF":1.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567589/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142649025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors influencing urinary retention following freehand transperineal prostate biopsy: Insights from a tertiary care center study.","authors":"Shashank Agrawal, Vivek Dadasaheb Patil, Vishnu Prasad, Arun Ramadas Menon, Ginil Kumar Pooleri","doi":"10.4103/iju.iju_36_24","DOIUrl":"10.4103/iju.iju_36_24","url":null,"abstract":"<p><strong>Objectives: </strong>In this study, we evaluated the risk factors for urinary retention after freehand transrectal ultrasound (TRUS) guided transperineal prostate biopsy (TPB).</p><p><strong>Patients and methods: </strong>Data from 102 cases of freehand TPB at a single institution were retrospectively collected and analyzed. All patients underwent magnetic resonance imaging (MRI)-TRUS cognitive fusion TPB using a transperineal needle guide, with systematic biopsies from 10 prostate sectors and additional MRI-guided targeted biopsies. Exclusions comprised patients with coagulation abnormalities, prior prostate surgeries including biopsy, active urinary tract infection, or a lack of pre-biopsy multiparametric MRI.</p><p><strong>Results: </strong>14/102 (13.72%) had urinary retention and required urethral catheterization for voiding difficulty or discomfort along with a bladder volume of ≥500 ml. Patients with retention exhibited significantly larger prostate volumes (median 75 cc vs. 40 cc; <i>P</i> < 0.05). Receiver operating curve analysis revealed a prostate volume threshold of 57.5 cc and a core number cutoff of 23 for predicting post-TPB urinary retention, with sensitivities of 78.57% and 85.71%, specificities of 75% and 82.95%, positive predictive values of 33.33% and 44.44%, and negative predictive values of 95.75% and 97.33%, respectively, whereas the number of biopsy cores correlated positively with the development of urinary retention (median 25 vs. 22; <i>P</i> < 0.05). Urinary retention was independent of the patient's age, comorbidities, presenting prostate-specific antigen levels, prebiopsy severity of lower urinary tract symptoms, and use of alpha-blockers.</p><p><strong>Conclusion: </strong>Patients with larger prostates and higher number of biopsy cores are at a higher risk of postfreehand TPB urinary retention and should receive appropriate counselling. Targeted biopsies alone, rather than a full template, may help mitigate urinary retention in these high-risk groups.</p>","PeriodicalId":47352,"journal":{"name":"Indian Journal of Urology","volume":"40 4","pages":"229-234"},"PeriodicalIF":1.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567580/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142649055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The grimacing face of adverse upper tract urothelial carcinoma can now POUT with adjuvant chemotherapy!","authors":"Sumit Mandal","doi":"10.4103/iju.iju_87_24","DOIUrl":"10.4103/iju.iju_87_24","url":null,"abstract":"","PeriodicalId":47352,"journal":{"name":"Indian Journal of Urology","volume":"40 4","pages":"281-282"},"PeriodicalIF":1.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567576/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142649288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence in prostate cancer: The potential of machine learning models and neural networks to predict biochemical recurrence after robot-assisted radical prostatectomy.","authors":"Gurpremjit Singh, Mayank Agrawal, Gagandeep Talwar, Sanket Kankaria, Gopal Sharma, Puneet Ahluwalia, Gagan Gautam","doi":"10.4103/iju.iju_75_24","DOIUrl":"10.4103/iju.iju_75_24","url":null,"abstract":"<p><strong>Introduction: </strong>This study aimed to evaluate the usefulness of machine learning (ML) and neural network (NN) models versus traditional statistical methods for estimating biochemical recurrence (BCR) in men following robot-assisted radical prostatectomy (RARP).</p><p><strong>Methods: </strong>Patients who underwent RARP from November 2011 to July 2022 were taken in the study. Patients with BCR were assigned to Group 2, whereas those without BCR were placed in Group 1. Preoperative and postoperative parameters, together with demographic data, were recorded in the database. This study used one NN, the radial basis function NN (RBFNN), and two ML approaches, the K-nearest neighbor and XGboost ML models, to predict BCR.</p><p><strong>Results: </strong>Following the application of exclusion criteria, 516 patients were deemed eligible for the study. Of those, 234 (45.3%) developed BCR, and 282 (54.7%) did not. The results showed that the median follow-up period was 24 (15-42) months, and the median BCR diagnosis was 12.23 ± 15.58 months. The area under the curve (AUC) for the Cox proportional hazard analysis was 0.77. The receiver-operating characteristic curves (AUCs) for the XGBoost and K closest neighbor models were 0.82 and 0.69, respectively. The RBFNN's AUC was 0.82.</p><p><strong>Conclusions: </strong>The classical statistical model was outperformed by XGBoost and RBFNN models in predicting BCR.</p>","PeriodicalId":47352,"journal":{"name":"Indian Journal of Urology","volume":"40 4","pages":"260-265"},"PeriodicalIF":1.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567574/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142648986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preoperative prostate magnetic resonance imaging does not impact surgical outcomes of radical prostatectomy.","authors":"Christopher K Bozorgmehr, Johnny Wang, James T Gross, Nicholas A Pickersgill, Joel M Vetter, Joseph E Ippolito, Eric H Kim","doi":"10.4103/iju.iju_115_24","DOIUrl":"10.4103/iju.iju_115_24","url":null,"abstract":"<p><strong>Objective: </strong>We reviewed our institutional experience of radical prostatectomy with and without preoperative multiparametric magnetic resonance imaging (mpMRI) to assess the impact of preoperative prostate mpMRI on surgical outcomes of radical prostatectomy.</p><p><strong>Methods: </strong>We identified patients at our institution who underwent radical prostatectomy for prostate cancer (PCa) between January 2012 and December 2017 (<i>n</i> = 1044). Using propensity scoring analysis, patients who underwent preoperative mpMRI (<i>n</i> = 285) were matched 1:1 to patients who did not receive preoperative mpMRI (<i>n</i> = 285). Multivariable regression analysis was performed to identify factors predictive of operative time, estimated blood loss (EBL), lymph node yield, rates of complications within 30 days, and positive surgical margin (PSM).</p><p><strong>Results: </strong>There were no significant differences in operative time, EBL, PSM, lymph node yield, or complication rates between the two cohorts. Multivariable analysis demonstrated that preoperative mpMRI was not predictive of the measured perioperative outcomes. Significant comorbidity (Charlson Comorbidity Index ≥3) was the sole predictor of perioperative complications (<i>P</i> = 0.015). Increasing biopsy Gleason score predicted increased lymph node yield (<i>P</i> < 0.001). The probability of PSM was associated with increasing preoperative prostate-specific antigen (odds ratio 1.036, <i>P</i> = 0.009). Body mass index was a predictor of operative time (<i>P</i> = 0.016) and EBL (<i>P</i> = 0.001).</p><p><strong>Conclusions: </strong>Although preoperative mpMRI has an important role in the diagnosis and staging of PCa, it does not impact perioperative radical prostatectomy outcomes. Our findings do not support the routine use of preoperative mpMRI for surgical planning in patients already diagnosed with clinically localized PCa.</p>","PeriodicalId":47352,"journal":{"name":"Indian Journal of Urology","volume":"40 4","pages":"266-271"},"PeriodicalIF":1.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567587/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142649111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}