Catalyzing Precision Medicine: Artificial Intelligence Advancements in Prostate Cancer Diagnosis and Management.

BACKGROUND: The aim was to analyze the current state of deep learning (DL)-based prostate cancer (PCa) diagnosis with a focus on magnetic resonance (MR) prostate reconstruction; PCa detection/stratification/reconstruction; positron emission tomography/computed tomography (PET/CT); androgen deprivation therapy (ADT); prostate biopsy; associated challenges and their clinical implications. METHODS: A search of the PubMed database was conducted based on the inclusion and exclusion criteria for the use of DL methods within the abovementioned areas. RESULTS: A total of 784 articles were found, of which, 64 were included. Reconstruction of the prostate, the detection and stratification of prostate cancer, the reconstruction of prostate cancer, and diagnosis on PET/CT, ADT, and biopsy were analyzed in 21, 22, 6, 7, 2, and 6 studies, respectively. Among studies describing DL use for MR-based purposes, datasets with magnetic field power of 3 T, 1.5 T, and 3/1.5 T were used in 18/19/5, 0/1/0, and 3/2/1 studies, respectively, of 6/7 studies analyzing DL for PET/CT diagnosis which used data from a single institution. Among the radiotracers, [68Ga]Ga-PSMA-11, [18F]DCFPyl, and [18F]PSMA-1007 were used in 5, 1, and 1 study, respectively. Only two studies that analyzed DL in the context of DT met the inclusion criteria. Both were performed with a single-institution dataset with only manual labeling of training data. Three studies, each analyzing DL for prostate biopsy, were performed with single- and multi-institutional datasets. TeUS, TRUS, and MRI were used as input modalities in two, three, and one study, respectively. CONCLUSION: DL models in prostate cancer diagnosis show promise but are not yet ready for clinical use due to variability in methods, labels, and evaluation criteria. Conducting additional research while acknowledging all the limitations outlined is crucial for reinforcing the utility and effectiveness of DL-based models in clinical settings.

Role of virtual reality in improving the spatial perception of the kidney during flexible ureteroscopy: A feasibility study using virtual reality simulators and 3D models.

Background: The aims were to describe a software-based reconstruction of the patient-specific kidney cavity intraluminal appearance via a head-mounted device and to estimate its feasibility for training novices. Materials and methods: In total, 15 novices were recruited. Each novice was shown a three-dimensional reconstruction of a patient's computed tomography scan, whose kidney was printed. They then joined the surgeon in the operating room and assisted them in detecting the stone during flexible ureteroscopy on the printed model. Then, each participant did a 7-day virtual reality (VR) study followed by virtual navigation of the printed kidney model and came to the operating room to help the surgeon with ureteroscope navigation. The length of the procedure and the number of attempts to find the targeted calyx were compared. Results: With VR training, the length of the procedure (p = 0.0001) and the number of small calyces that were incorrectly identified as containing stones were significantly reduced (p = 0.0001). All the novices become highly motivated to improve their endourological skills further. Participants noticed minimal values for nausea and for disorientation. However, oculomotor-related side effects were defined as significant. Five specialists noticed a good similarity between the VR kidney cavity representation and the real picture, strengthening the potential for the novice's education via VR training. Conclusions: Virtual reality simulation allowed for improved spatial orientation within the kidney cavity by the novices and could be a valuable option for future endourological training and curricula.

Oligometastatic carcinoma prostate - An overview of the last decade.

Introduction: Oligometastatic prostate cancer (OMPC) has gained profound interest lately due to its different tumor biology and our ability to use multimodality therapy for cure or prolonged survival. Selecting the appropriate patient for treatment has become the aim of treating urologists, medical oncologists, and radiation oncologists. Through this review, we try to highlight the management of OMPC in light of recent literature. Methods: Literature search was performed on Pubmed, Scopus and Embase using keywords "Oligometastatic", " Prostate Cancer" using operators such as "And" & "Or". Relevant articles were screened and all the latest articles on this emerging entity were included in this review. Results: All trials relevant to oligometastatic prostate cancer defining the role of surgery, radiotherapy and systemic therapy were included and appropriate inferences were drawn. Relevant studies were compiled in tabular form for this article. Conclusion: The current standard of care of management for OMPC remains systemic therapy on the lines of hormone-sensitive metastatic prostate cancer. The evolving role of surgery, and radiotherapy along with systemic therapy is highlighted in this article.

Off-clamp Versus On-clamp Robot-assisted Partial Nephrectomy: A Propensity-matched Analysis.

BACKGROUND: Partial nephrectomy is the preferred treatment option for the management of small renal masses. On-clamp partial nephrectomy is associated with a risk of ischemia and a greater loss of postoperative renal function, while the off-clamp procedure decreases the duration of renal ischemia, leading to better renal function preservation. However, the efficacy of the off- versus on-clamp partial nephrectomy for renal function preservation remains debatable. OBJECTIVE: To compare perioperative and functional outcomes following off- and on-clamp robot-assisted partial nephrectomy (RAPN). DESIGN, SETTING, AND PARTICIPANTS: This study used the prospective multinational collaborative Vattikuti Collective Quality Initiative (VCQI) database for RAPN. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary objective of this study was the comparison of perioperative and functional outcomes between patients who underwent off- and on-clamp RAPN. Propensity scores were calculated for age, sex, body mass index (BMI), renal nephrometry score (RNS) and preoperative estimated glomerular filtration rate (eGFR). RESULTS AND LIMITATIONS: Of the 2114 patients, 210 had undergone off-clamp RAPN and others on-clamp procedure. Propensity matching was possible for 205 patients in a 1:1 ratio. After matching, the two groups were comparable for age, sex, BMI, tumor size, multifocality, tumor side, face of tumor, RNS, polar location of the tumor, surgical access, and preoperative hemoglobin, creatinine, and eGFR. There was no difference between the two groups for intraoperative (4.8% vs 5.3%, p = 0.823) and postoperative (11.2% vs 8.3%, p = 0.318) complications. Need for blood transfusion (2.9% vs 0, p = 0.030) and conversion to radical nephrectomy (10.2% vs 1%, p < 0.001) were significantly higher in the off-clamp group. At the last follow-up, there was no difference between the two groups for creatinine and eGFR. The mean fall in eGFR at the last follow-up compared with that at baseline was equivalent between the two groups (-16.0 vs -17.3 ml/min, p = 0.985). CONCLUSIONS: Off-clamp RAPN does not result in better renal functional preservation. Alternatively, it may be associated with increased rates of conversion to radical nephrectomy and need for blood transfusion. PATIENT SUMMARY: With this multicentric study, we noted that performing robotic partial nephrectomy without clamping the blood supply to the kidney is not associated with better preservation of renal function. However, off-clamp partial nephrectomy is associated with increased rates of conversion to radical nephrectomy and blood transfusion.

Trifecta and pentafecta outcomes following robot-assisted partial nephrectomy in a multi-institutional cohort of Indian patients.

Introduction: The literature on studies reporting trifecta or pentafecta outcomes following robot-assisted partial nephrectomy (RAPN) in Indian patients is limited. The primary aim of this study was to report and evaluate the factors predicting trifecta and pentafecta outcomes following RAPN in Indian patients using the multicentric Vattikuti collective quality initiative (VCQI) database. Methods: From the VCQI database for patients who underwent RAPN, data for Indian patients were extracted and analyzed for factors predicting the achievement of trifecta and pentafecta following RAPN. Trifecta was defined as the absence of complications, negative surgical margins, and warm ischemia period shorter than 25 min or zero ischemia. Pentafecta covers all the trifecta criteria as well as >90% preservation of estimated glomerular filtration rate (eGFR) and no stage upgrade of chronic kidney disease at 12 months. Results: In this study, among 614 patients, the trifecta was achieved in 374 patients (60.9%) and pentafecta was achieved in 24.2% of the patients. Patients who achieved trifecta had significantly higher mean age (54.1 vs. 51.0 years, P = 0.005), body mass index (BMI) (26.7 vs. 26.03 kg/m2, P = 0.022), and smaller tumor size (38.6 vs. 41.4 mm, P = 0.028). The preoperative eGFR (84.2 vs. 91.9 ml/min, P = 0.012) and renal nephrometry score (RNS) (6.96 vs. 7.87, P ≤ 0.0001) were significantly lower in the trifecta group. Comparing patients who achieved pentafecta to those who did not, we noted a statistically significant difference between the two groups for tumor size (36.1 vs. 41.5 mm, P = 0.017) and RNS (6.6 vs. 7.7, P = 0.0001). On multivariate analysis, BMI and RNS were associated with trifecta outcomes. Similarly, only RNS was identified as an independent predictor of pentafecta. Conclusions: RNS and BMI were independent predictors of the trifecta. At the same time, RNS was identified as an independent predictor of pentafecta following RAPN.

The technological future of percutaneous nephrolithotomy: a Young Academic Urologists Endourology and Urolithiasis Working Group update.

PURPOSE OF REVIEW: With advancements in surgical technology along with procedural techniques, this article throws light on the latest developments and applications of artificial intelligence (AI), extended reality, 3D (three-dimensional) printing and robotics in percutaneous nephrolithotomy (PCNL). RECENT FINDINGS: This review highlights the applications of AI in PCNL over the past 2 years. Mostly studies have been reported on development of machine learning (ML) based predicting models and identification of stone composition using deep learning convolutional neural network (DL-CNN). But owing to the complexity of the models and lack of generalizability, it is still not incorporated in the routine clinical practice. Extended reality based simulation and training models have enabled trainees to enhance their skills and shorten the learning curve. Similar advantages have been reported with the use of 3D printed models when used to train young and novice endourologists to improve their skills in percutaneous access (PCA). Applications of robotics in PCNL look promising but are still in nascent stages. SUMMARY: Future research on PCNL should focus more on generalizability and adaptability of technological advancements in terms of training and improvement of patient outcomes.

Ambulatory Minimally Invasive Endoscopic Combined Intrarenal Surgery in Management of Large Impacted Proximal Ureteral Calculi: A Feasibility Study at a Tertiary Referral Center.

Aim: To conduct a comparative, nonrandomized study to assess the feasibility of mini-Endoscopic Combined Intrarenal Surgery (ECIRS) using supine Mini-percutaneous nephrolithotomy (PCNL) access (16F) in Galdakao-Modified Supine Valdivia position for managing proximal large-volume impacted ureteral calculi as ambulatory day-care surgery vis-a-vis standalone ureteroscopy (URS) with push-back PCNL, if needed. The primary aim was to study the outcomes and stone-free rates (SFRs). Secondary aim was to compare the intraoperative and short-term postoperative complications. Materials and Methods: Data of 60 patients undergoing ECIRS (Group 1) from January 2016 to December 2019 were collected prospectively in a nonrandomized fashion from a single center after Ethics Committee approval. A matched-paired analysis was performed with retrospectively collated data of 60 patients undergoing standard URS/pushback PCNL (Group 2) using analysis of variance, Fisher's exact test, and Chi-square test. p < 0.05 was considered statistically significant. Outcomes and Results: Group 1 patients had a significantly shorter procedure time vs Group 2 (42.1 ± 11.2 minutes vs 52.1 ± 13.7 minutes; p < 0.001). Group 1 (59/60) patients had an overall single stage SFR of 98.3%, which was significantly higher than single-stage SFR of 83% in Group 2 (50/60) (p < 0.002). Group 2 patients had a higher incidence of fever (10 vs 4, p = 0.01). However, there were no cases of sepsis in either group. Rest of the complications were comparable for both, as the need for ancillary procedures was significantly higher in Group 2 (10% vs 1.7%, p < 0.001). Patients were discharged on the same day in both groups. Conclusions: The findings of our study suggest that, in large and impacted proximal ureteric stones, combined minimally invasive endoscopic approach offers the best option to render the patient stone free by a single intervention. With better intra- and postoperative outcomes and safety profile, Mini-ECIRS may be considered as an ambulatory procedure in this setting.

Development and Validation of a Nomogram Predicting Intraoperative Adverse Events During Robot-assisted Partial Nephrectomy.

BACKGROUND: Ability to predict the risk of intraoperative adverse events (IOAEs) for patients undergoing partial nephrectomy (PN) can be of great clinical significance. OBJECTIVE: To develop and internally validate a preoperative nomogram predicting IOAEs for robot-assisted PN (RAPN). DESIGN, SETTING, AND PARTICIPANTS: In this observational study, data for demographic, preoperative, and postoperative variables for patients who underwent RAPN were extracted from the Vattikuti Collective Quality Initiative (VCQI) database. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: IOAEs were defined as the occurrence of intraoperative surgical complications, blood transfusion, or conversion to open surgery/radical nephrectomy. Backward stepwise logistic regression analysis was used to identify predictors of IOAEs. The nomogram was validated using bootstrapping, the area under the receiver operating characteristic curve (AUC), and the goodness of fit. Decision curve analysis (DCA) was used to determine the clinical utility of the model. RESULTS AND LIMITATIONS: Among the 2114 patients in the study cohort, IOAEs were noted in 158 (7.5%). Multivariable analysis identified five variables as independent predictors of IOAEs: RENAL nephrometry score (odds ratio [OR] 1.13, 95% confidence interval [CI] 1.02-1.25); clinical tumor size (OR 1.01, 95% CI 1.001-1.024); PN indication as absolute versus elective (OR 3.9, 95% CI 2.6-5.7) and relative versus elective (OR 4.2, 95% CI 2.2-8); Charlson comorbidity index (OR 1.17, 95% CI 1.05-1.30); and multifocal tumors (OR 8.8, 95% CI 5.4-14.1). A nomogram was developed using these five variables. The model was internally valid on bootstrapping and goodness of fit. The AUC estimated was 0.76 (95% CI 0.72-0.80). DCA revealed that the model was clinically useful at threshold probabilities >5%. Limitations include the lack of external validation and selection bias. CONCLUSIONS: We developed and internally validated a nomogram predicting IOAEs during RAPN. PATIENT SUMMARY: We developed a preoperative model than can predict complications that might occur during robotic surgery for partial removal of a kidney. Tests showed that our model is fairly accurate and it could be useful in identifying patients with kidney cancer for whom this type of surgery is suitable.

COVID-19 associated multisystemic mucormycosis from India: a multicentric retrospective study on clinical profile, predisposing factors, cumulative mortality and factors affecting outcome.

PURPOSE: The clinical course of COVID-19 has been complicated by secondary infections, including bacterial and fungal infections. The rapid rise in the incidence of invasive mucormycosis in these patients is very much concerning. COVID-19-associated mucormycosis was detected in huge numbers during the second wave of the COVID-19 pandemic in India, with several predisposing factors indicated in its pathogenesis. This study aimed to evaluate the epidemiology, predisposing factor, cumulative mortality and factors affecting outcomes among the coronavirus disease COVID-19-associated mucormycosis (CAM). METHODS: A multicenter retrospective study across three tertiary health care centers in Southern part of India was conducted during April-June 2021. RESULTS: Among the 217 cases of CAM, mucormycosis affecting the nasal sinuses was the commonest, affecting 95 (44%) of the patients, orbital extension seen in 84 (38%), pulmonary (n = 25, 12%), gastrointestinal (n = 6, 3%), isolated cerebral (n = 2) and disseminated mucormycosis (n = 2). Diabetes mellitus, high-dose systemic steroids were the most common underlying disease among CAM patients. The mucormycosis-associated case-fatality at 6 weeks was 14%, cerebral or GI or disseminated mucormycosis had 9 times higher risk of death compared to other locations. Extensive surgical debridement along with sequential antifungal drug treatment improved the survival in mucormycosis patients. CONCLUSION: Judicious and appropriate management of the predisposing factor and factors affecting mortality associated with CAM with multi-disciplinary approach and timely surgical and medical management can be much helpful in achieving a successful outcome.

Factors Affecting the Usage of Wearable Device Technology for Healthcare among Indian Adults: A Cross-Sectional Study.

BACKGROUND: Wearable device technology has recently been involved in the healthcare industry substantially. India is the world's third largest market for wearable devices and is projected to expand at a compound annual growth rate of ~26.33%. However, there is a paucity of literature analyzing the factors determining the acceptance of wearable healthcare device technology among low-middle-income countries. METHODS: This cross-sectional, web-based survey aims to analyze the perceptions affecting the adoption and usage of wearable devices among the Indian population aged 16 years and above. RESULTS: A total of 495 responses were obtained. In all, 50.3% were aged between 25-50 years and 51.3% belonged to the lower-income group. While 62.2% of the participants reported using wearable devices for managing their health, 29.3% were using them daily. technology and task fitness (TTF) showed a significant positive correlation with connectivity (r = 0.716), health care (r = 0.780), communication (r = 0.637), infotainment (r = 0.598), perceived usefulness (PU) (r = 0.792), and perceived ease of use (PEOU) (r = 0.800). Behavioral intention (BI) to use wearable devices positively correlated with PEOU (r = 0.644) and PU (r = 0.711). All factors affecting the use of wearable devices studied had higher mean scores among participants who were already using wearable devices. Male respondents had significantly higher mean scores for BI (p = 0.034) and PEOU (p = 0.009). Respondents older than 25 years of age had higher mean scores for BI (p = 0.027) and Infotainment (p = 0.032). CONCLUSIONS: This study found a significant correlation with the adoption and acceptance of wearable devices for healthcare management in the Indian context.

Perioperative outcomes following robot-assisted partial nephrectomy for complex renal masses: A Vattikuti Collective Quality Initiative database study.

Introduction: Outcomes of robot-assisted partial nephrectomy (RAPN) depend on tumor complexity, surgeon experience and patient profile among other variables. We aimed to study the perioperative outcomes of RAPN for patients with complex renal masses using the Vattikuti Collective Quality Initiative (VCQI) database that allowed evaluation of multinational data. Methods: From the VCQI, we extracted data for all the patients who underwent RAPN with preoperative aspects and dimensions used for an anatomical (PADUA) score of ≥10. Multivariate logistic regression was conducted to ascertain predictors of trifecta (absence of complications, negative surgical margins, and warm ischemia times [WIT] <25 min or zero ischemia) outcomes. Results: Of 3,801 patients, 514 with PADUA scores ≥10 were included. The median operative time, WIT, and blood loss were 173 (range 45-546) min, 21 (range 0-55) min, and 150 (range 50-3500) ml, respectively. Intraoperative complications and blood transfusions were reported in 2.1% and 6%, respectively. In 8.8% of the patients, postoperative complications were noted, and surgical margins were positive in 10.3% of the patients. Trifecta could be achieved in 60.7% of patients. Clinical tumor size, duration of surgery, WIT, and complication rates were significantly higher in the group with a high (12 or 13) PADUA score while the trifecta was significantly lower in this group (48.4%). On multivariate analysis, surgical approach (retroperitoneal vs. transperitoneal) and high PADUA score (12/13) were identified as predictors of the trifecta outcomes. Conclusion: RAPN may be a reasonable surgical option for patients with complex renal masses with acceptable perioperative outcomes.

Perioperative outcomes following robot-assisted partial nephrectomy in elderly patients.

OBJECTIVE: To compare perioperative outcomes following robot-assisted partial nephrectomy (RAPN) in patients with age ≥ 70 years to age < 70 years. METHODS: Using Vattikuti Collective quality initiative (VCQI) database for RAPN we compared perioperative outcomes following RAPN between the two age groups. Primary outcome of the study was to compare trifecta outcomes between the two groups. Propensity matching using nearest neighbourhood method was performed with trifecta as primary outcome for sex, body mass index (BMI), solitary kidney, tumor size and Renal nephrometery score (RNS). RESULTS: Group A (age ≥ 70 years) included 461 patients whereas group B included 1932 patients. Before matching the two groups were statistically different for RNS and solitary kidney rates. After propensity matching, the two groups were comparable for baselines characteristics such as BMI, tumor size, clinical symptoms, tumor side, face of tumor, solitary kidney and tumor complexity. Among the perioperative outcome parameters there was no difference between two groups for operative time, blood loss, intraoperative transfusion, intraoperative complications, need for radical nephrectomy, positive margins and trifecta rates. Warm ischemia time was significantly longer in the younger age group (18.1 min vs. 16.3 min, p = 0.003). Perioperative complications were significantly higher in the older age group (11.8% vs. 7.7%, p = 0.041). However, there was no difference between the two groups for major complications. CONCLUSION: RAPN in well-selected elderly patients is associated with comparable trifecta outcomes with acceptable perioperative morbidity.

Role of three dimensional (3D) printing in endourology: An update from EAU young academic urologists (YAU) urolithiasis and endourology working group.

The management of nephrolithiasis has been complemented well by modern technological advancements like virtual reality, three-dimensional (3D) printing etc. In this review, we discuss the applications of 3D printing in treating stone disease using percutaneous nephrolithotomy (PCNL) and retrograde intrarenal surgery (RIRS). PCNL surgeries, when preceded by a training phase using a 3D printed model, aid surgeons to choose the proper course of action, which results in better procedural outcomes. The 3D printed models have also been extensively used to train junior residents and novice surgeons to improve their proficiency in the procedure. Such novel measures include different approaches employed to 3D print a model, from 3D printing the entire pelvicalyceal system with the surrounding tissues to 3D printing simple surgical guides.

Transforming healthcare through a digital revolution: A review of digital healthcare technologies and solutions.

The COVID-19 pandemic has put a strain on the entire global healthcare infrastructure. The pandemic has necessitated the re-invention, re-organization, and transformation of the healthcare system. The resurgence of new COVID-19 virus variants in several countries and the infection of a larger group of communities necessitate a rapid strategic shift. Governments, non-profit, and other healthcare organizations have all proposed various digital solutions. It's not clear whether these digital solutions are adaptable, functional, effective, or reliable. With the disease becoming more and more prevalent, many countries are looking for assistance and implementation of digital technologies to combat COVID-19. Digital health technologies for COVID-19 pandemic management, surveillance, contact tracing, diagnosis, treatment, and prevention will be discussed in this paper to ensure that healthcare is delivered effectively. Artificial Intelligence (AI), big data, telemedicine, robotic solutions, Internet of Things (IoT), digital platforms for communication (DC), computer vision, computer audition (CA), digital data management solutions (blockchain), digital imaging are premiering to assist healthcare workers (HCW's) with solutions that include case base surveillance, information dissemination, disinfection, and remote consultations, along with many other such interventions.

ALARA in Urology: Steps to Minimise Radiation Exposure During All Parts of the Endourological Journey.

PURPOSE OF THE REVIEW: The global burden of kidney stone disease (KSD) and its management relies on ionising radiation. This includes the diagnosis, treatment and follow-up of KSD patients. The concept 'As Low As Reasonably Achievable' (ALARA) developed in response to the radiation risks and the key principles include optimisation, justification and limitation of radiation. This article provides an overview of the topic including background to the risks and steps that can be taken during all stages of endourological management. RECENT FINDINGS: Our review suggests that ionising radiation is an invaluable tool in delineating the anatomy, localising disease, guiding manoeuvres and monitoring treatment in patients with KSD. It therefore plays an integral role in many stages of patient care; preoperatively, intraoperatively and postoperatively. The reduction of radiation pre- and post-surgical intervention relies on the use of low-radiation CT scan and ultrasound scan. It can also be achieved through various intraoperative techniques or fluoroless techniques in selected patients/procedures, customised to the patients and procedural complexity. There are many parts of the patient journey where exposure to radiation can take place. Urologists must be diligent to minimise and mitigate this wherever possible as they too face exposure risks. Implementation of strategies such as teaching programmes, fluoroscopy checklists and judicious use of CT imaging among other things is a step towards improving practice in this area.

Current Applications of Artificial Intelligence in Benign Prostatic Hyperplasia.

Artificial intelligence is used in predicting the clinical outcomes before minimally invasive treatments for benign prostatic hyperplasia, to address the insufficient reliability despite multiple assessment parameters, such as flow rates and symptom scores. Various models of artificial intelligence and its contemporary applications in benign prostatic hyperplasia are reviewed and discussed. A search strategy adapted to identify and review the literature on the application of artificial intelligence with a dedicated search string with the following keywords: "Machine Learning," "Artificial Intelligence," AND "Benign Prostate Enlargement" OR "BPH" OR "Benign Prostatic Hyperplasia" was included and categorized. Review articles, editorial comments, and non-urologic studies were excluded. In the present review, 1600 patients were included from 4 studies that used different classifiers such as fuzzy systems, computer-based vision systems, and clinical data mining to study the applications of artificial intelligence in diagnoses and severity prediction and determine clinical factors responsible for treatment response in benign prostatic hyperplasia. The accuracy to correctly diagnose benign prostatic hyperplasia by Fuzzy systems was 90%, while that of computer-based vision system was 96.3%. Data mining achieved sensitivity and specificity of 70% and 50%, respectively, in correctly predicting the clinical response to medical treatment in benign prostatic hyperplasia. Artificial intelligence is gaining attraction in urology, with the potential to improve diagnostics and patient care. The results of artificial intelligence-based applications in benign prostatic hyperplasia are promising but lack generalizability of results. However, in the future, we will see a shift in the clinical paradigm as artificial intelligence applications will find their place in the guidelines and revolutionize the decision-making process.

Role of Deep Learning in Prostate Cancer Management: Past, Present and Future Based on a Comprehensive Literature Review.

This review aims to present the applications of deep learning (DL) in prostate cancer diagnosis and treatment. Computer vision is becoming an increasingly large part of our daily lives due to advancements in technology. These advancements in computational power have allowed more extensive and more complex DL models to be trained on large datasets. Urologists have found these technologies help them in their work, and many such models have been developed to aid in the identification, treatment and surgical practices in prostate cancer. This review will present a systematic outline and summary of these deep learning models and technologies used for prostate cancer management. A literature search was carried out for English language articles over the last two decades from 2000-2021, and present in Scopus, MEDLINE, Clinicaltrials.gov, Science Direct, Web of Science and Google Scholar. A total of 224 articles were identified on the initial search. After screening, 64 articles were identified as related to applications in urology, from which 24 articles were identified to be solely related to the diagnosis and treatment of prostate cancer. The constant improvement in DL models should drive more research focusing on deep learning applications. The focus should be on improving models to the stage where they are ready to be implemented in clinical practice. Future research should prioritize developing models that can train on encrypted images, allowing increased data sharing and accessibility.

Telemedicine and Telehealth in Urology: Uptake, Impact and Barriers to Clinical Adoption.

Telemedicine has great potential in urology as a strong medium for providing patients with continuous high-quality urological care despite the hurdles involved in its implementation. Both clinicians and patients are crucial factors in determining the success of tele-consults in terms of simplicity of use and overall satisfaction. For it to be successfully incorporated into routine urological practice, rigorous training and evidence-based recommendations are lacking. If these issues are addressed, they can provide a significant impetus for future tele-consults in urology and their successful deployment, even beyond the pandemic, to assure safer and more environment-friendly patient management.