Techniques for Penile Augmentation Surgery: A Systematic Review of Surgical Outcomes, Complications, and Quality of Life.

The increase in practices related to enhancing penile size can be attributed to the belief that an improved genital appearance contributes to a man's virility, coupled with an altered self-perception of his body. It is crucial to tailor interventions to meet the genuine needs of patients by thoroughly assessing their history, psychological state, and potential surgical benefits, all while considering the associated risks of complications. This systematic review aims to summarize the available evidence on outcomes, complications, and quality of life after penile augmentation surgery, examining both minimally invasive and more radical techniques. A search of the PubMed and Scopus databases, focusing on English-language papers published in the last 15 years, was performed in December 2023. Papers discussing surgery in animal models and case reports were excluded from the present study unless further evaluated in a follow-up case series. The primary outcomes were changes in penile dimensions, specifically in terms of length and girth, as well as the incidence of surgical complications and the impact on quality of life. A total of 1670 articles were retrieved from the search and 46 were included for analysis. Procedures for penile length perceived enhancements include lipoplasty, skin reconstruction plasty, V-Y and Z plasty, flap reconstruction, scrotoplasty, ventral phalloplasty, and suspensory ligament release; techniques for increasing corporal penile length include penile disassembly, total phalloplasty, and sliding elongation. Finally, penile girth enhancement may be performed using soft tissue fillers, grafting procedures, biodegradable scaffolds, and Penuma®. In conclusion, while penile augmentation surgeries offer potential solutions for individuals concerned about genital size, the risks and complexities need to be accounted for.

Visual extended reality tools in image-guided surgery in urology: a systematic review.

PURPOSE: The aim of this systematic review is to assess the clinical implications of employing various Extended Reality (XR) tools for image guidance in urological surgery. METHODS: In June 2023, a systematic electronic literature search was conducted using the Medline database (via PubMed), Embase (via Ovid), Scopus, and Web of Science. The search strategy was designed based on the PICO (Patients, Intervention, Comparison, Outcome) criteria. Study protocol was registered on PROSPERO (registry number CRD42023449025). We incorporated retrospective and prospective comparative studies, along with single-arm studies, which provided information on the use of XR, Mixed Reality (MR), Augmented Reality (AR), and Virtual Reality (VR) in urological surgical procedures. Studies that were not written in English, non-original investigations, and those involving experimental research on animals or cadavers were excluded from our analysis. The quality assessment of comparative and cohort studies was conducted utilizing the Newcastle-Ottawa scale, whilst for randomized controlled trials (RCTs), the Jadad scale was adopted. The level of evidence for each study was determined based on the guidelines provided by the Oxford Centre for Evidence-Based Medicine. RESULTS: The initial electronic search yielded 1,803 papers after removing duplicates. Among these, 58 publications underwent a comprehensive review, leading to the inclusion of 40 studies that met the specified criteria for analysis. 11, 20 and 9 studies tested XR on prostate cancer, kidney cancer and miscellaneous, including bladder cancer and lithiasis surgeries, respectively. Focusing on the different technologies 20, 15 and 5 explored the potential of VR, AR and MR. The majority of the included studies (i.e., 22) were prospective non-randomized, whilst 7 and 11 were RCT and retrospective studies respectively. The included studies that revealed how these new tools can be useful both in preoperative and intraoperative setting for a tailored surgical approach. CONCLUSIONS: AR, VR and MR techniques have emerged as highly effective new tools for image-guided surgery, especially for urologic oncology. Nevertheless, the complete clinical advantages of these innovations are still in the process of evaluation.

Ten-year functional and oncological outcomes of a prospective randomized controlled trial comparing laparoscopic versus robot-assisted radical prostatectomy.

BACKGROUND: Among prostate cancer (PCa) treatment options, mini-invasive surgical approaches have gained a wide diffusion in the last decades. The aim of this study was to present oncological, functional, and quality of life data after 10 years of follow-up of a prospective randomized controlled trial (RCT) (ISRCTN11552140) comparing robot-assisted radical prostatectomy (RARP) versus laparoscopic radical prostatectomy (LRP) for the treatment of PCa. METHODS: Patients with localized PCa were randomized to undergo LRP or RARP between January 2010 and January 2011. Functional (continence and potency) and oncological (prostate-specific antigen, biochemical recurrence [BCR] and BCR-free survival [BCRFS]) variables were evaluated. BCRFS curves were estimated by the Kaplan-Meier method and compared using the log-rank test. Machine learning partial least square-discriminant analysis (PLS-DA) was used to identify the variables characterizing more the patients who underwent RARP or LRP. RESULTS: Seventy-five of the originally enrolled 120 patients remained on follow-up for 10 years; 40 (53%) underwent RARP and 35 (47%) LRP. Continence and potency recovery rates did not show significant differences (p = 0.068 and p = 0.56, respectively), despite a Δ12% for continence and Δ8% for potency in favor of the robotic approach. However, the quality of continence (in terms of International Consultation on Incontinence Questionnaire-Short Form [ICIQ-SF] score) and erection (in terms of International Index of Erectile Function-5 [IIEF-5] score) was significantly better after 10 years in the robotic group (p = 0.02 and p < 0.001). PLS-DA revealed that LRP was characterized by the worst functional-related outcomes analyzing the entire follow-up period. Four (10%) and six (17%) patients experienced BCR in RARP and LRP groups, respectively (p = 0.36), with an overall 10-year BCR-free survival of 88% and 78% (p = 0.16). CONCLUSIONS: Comparable continence and potency rates were observed between RARP and LRP after a 10-year follow-up. However, the RARP group exhibited superior totally dry rate and erection quality. No difference in terms of oncological outcomes was found.

Robotic Vena Cava Thrombectomy with Three-dimensional Augmented Reality Guidance.

Robotic surgery has recently been used for treatment of renal cell carcinoma (RCC) and neoplastic thrombus located in the renal vein or inferior vena cava (IVC). Accurate identification of the thrombus location is crucial, and three-dimensional augmented reality (3D AR) may be valuable in achieving this. We enrolled patients with nonmetastatic RCC and level 0-I venous thrombus (Mayo Clinic classification) for robot-assisted radical nephrectomy and thrombectomy with 3D AR guidance. Five patients were prospectively enrolled; three had a level 0 thrombus and two had a level I thrombus. The mean operative time was 123 ± 15 min, mean IVC clamping time was 9.4 ± 6.8 min, and mean estimated blood loss was 750 ± 150 ml. The AR system allowed precise estimation of the thrombus location in all cases. No intraoperative complications or postoperative Clavien-Dindo grade >2 complications occurred. Use of 3D AR guidance allowed correct estimation of the limits of the thrombus and guided the surgeon in selecting an appropriate surgical strategy.

Automatic 3D Augmented-Reality Robot-Assisted Partial Nephrectomy Using Machine Learning: Our Pioneer Experience.

The aim of "Precision Surgery" is to reduce the impact of surgeries on patients' global health. In this context, over the last years, the use of three-dimensional virtual models (3DVMs) of organs has allowed for intraoperative guidance, showing hidden anatomical targets, thus limiting healthy-tissue dissections and subsequent damage during an operation. In order to provide an automatic 3DVM overlapping in the surgical field, we developed and tested a new software, called "ikidney", based on convolutional neural networks (CNNs). From January 2022 to April 2023, patients affected by organ-confined renal masses amenable to RAPN were enrolled. A bioengineer, a software developer, and a surgeon collaborated to create hyper-accurate 3D models for automatic 3D AR-guided RAPN, using CNNs. For each patient, demographic and clinical data were collected. A total of 13 patients were included in the present study. The average anchoring time was 11 (6-13) s. Unintended 3D-model automatic co-registration temporary failures happened in a static setting in one patient, while this happened in one patient in a dynamic setting. There was one failure; in this single case, an ultrasound drop-in probe was used to detect the neoplasm, and the surgery was performed under ultrasound guidance instead of AR guidance. No major intraoperative nor postoperative complications (i.e., Clavien Dindo > 2) were recorded. The employment of AI has unveiled several new scenarios in clinical practice, thanks to its ability to perform specific tasks autonomously. We employed CNNs for an automatic 3DVM overlapping during RAPN, thus improving the accuracy of the superimposition process.

The ERUS course on robot-assisted kidney transplantation.

PURPOSE: Robot-assisted kidney transplantation (RAKT) is being increasingly performed at selected referral institutions worldwide. Yet, surgical training in RAKT is still unstructured and not grounded into formal credentialing courses including simulation, lab facilities, and modular training with animal models. As such, developing standardized, modular training programs is warranted to provide surgeons with the RAKT-specific skillset needed for a "safe" learning curve. METHODS: The 3-day course on RAKT developed at the EAU Skills Center in Orsi Academy was designed as a standardized, modular, step-by-step approach aiming to provide theoretical and practical skills. The course is held by expert proctors with extensive experience in RAKT. To maximize the course's usefulness, a solid knowledge of robotics and transplantation is desirable for participants. RESULTS: From January 2016 to July 2023, 87 surgeons from 23 countries (of which 36% from extra-European countries) participated in the RAKT course performed at the EAU Skills Center in Orsi Academy. Of these, 58/87 (67%) were urologists, while 27/87 (31%) were general surgeons and 2/87 (2%) were vascular surgeons. To date, 18 participants (20.6%) are actively involved in RAKT programs at institutions included in the European Association of Urology (EAU) Robotic Urology Section (ERUS)-RAKT network. CONCLUSION: Leveraging the potential of simulation, wet-lab training, live porcine models, and experienced proctors, the RAKT course performed at the EAU Skills Center in Orsi Academy represents the first structured teaching effort aiming to offer surgeons a full immersion in RAKT to train the core technical skills.

Development of Machine Learning Algorithm to Predict the Risk of Incontinence After Robot-Assisted Radical Prostatectomy.

Introduction: Predicting postoperative incontinence beforehand is crucial for intensified and personalized rehabilitation after robot-assisted radical prostatectomy. Although nomograms exist, their retrospective limitations highlight artificial intelligence (AI)'s potential. This study seeks to develop a machine learning algorithm using robot-assisted radical prostatectomy (RARP) data to predict postoperative incontinence, advancing personalized care. Materials and Methods: In this propsective observational study, patients with localized prostate cancer undergoing RARP between April 2022 and January 2023 were assessed. Preoperative variables included age, body mass index, prostate-specific antigen (PSA) levels, digital rectal examination (DRE) results, Gleason score, International Society of Urological Pathology grade, and continence and potency questionnaires responses. Intraoperative factors, postoperative outcomes, and pathological variables were recorded. Urinary continence was evaluated using the Expanded Prostate cancer Index Composite questionnaire, and machine learning models (XGBoost, Random Forest, Logistic Regression) were explored to predict incontinence risk. The chosen model's SHAP values elucidated variables impacting predictions. Results: A dataset of 227 patients undergoing RARP was considered for the study. Post-RARP complications were predominantly low grade, and urinary continence rates were 74.2%, 80.7%, and 91.4% at 7, 13, and 90 days after catheter removal, respectively. Employing machine learning, XGBoost proved the most effective in predicting postoperative incontinence risk. Significant variables identified by the algorithm included nerve-sparing approach, age, DRE, and total PSA. The model's threshold of 0.67 categorized patients into high or low risk, offering personalized predictions about the risk of incontinence after surgery. Conclusions: Predicting postoperative incontinence is crucial for tailoring rehabilitation after RARP. Machine learning algorithm, particularly XGBoost, can effectively identify those variables more heavily, impacting the outcome of postoperative continence, allowing to build an AI-driven model addressing the current challenges in post-RARP rehabilitation.

Computer Vision and Machine-Learning Techniques for Automatic 3D Virtual Images Overlapping During Augmented Reality Guided Robotic Partial Nephrectomy.

OBJECTIVES: The research's purpose is to develop a software that automatically integrates and overlay 3D virtual models of kidneys harboring renal masses into the Da Vinci robotic console, assisting surgeon during the intervention. INTRODUCTION: Precision medicine, especially in the field of minimally-invasive partial nephrectomy, aims to use 3D virtual models as a guidance for augmented reality robotic procedures. However, the co-registration process of the virtual images over the real operative field is performed manually. METHODS: In this prospective study, two strategies for the automatic overlapping of the model over the real kidney were explored: the computer vision technology, leveraging the super-enhancement of the kidney allowed by the intraoperative injection of Indocyanine green for superimposition and the convolutional neural network technology, based on the processing of live images from the endoscope, after a training of the software on frames from prerecorded videos of the same surgery. The work-team, comprising a bioengineer, a software-developer and a surgeon, collaborated to create hyper-accuracy 3D models for automatic 3D-AR-guided RAPN. For each patient, demographic and clinical data were collected. RESULTS: Two groups (group A for the first technology with 12 patients and group B for the second technology with 8 patients) were defined. They showed comparable preoperative and post-operative characteristics. Concerning the first technology the average co-registration time was 7 (3-11) seconds while in the case of the second technology 11 (6-13) seconds. No major intraoperative or postoperative complications were recorded. There were no differences in terms of functional outcomes between the groups at every time-point considered. CONCLUSION: The first technology allowed a successful anchoring of the 3D model to the kidney, despite minimal manual refinements. The second technology improved kidney automatic detection without relying on indocyanine injection, resulting in better organ boundaries identification during tests. Further studies are needed to confirm this preliminary evidence.

ESRU-ESU-YAU_UROTECH Survey on Urology Residents Surgical Training: Are We Ready for Simulation and a Standardized Program?

Background: Currently, the landscape of surgical training is undergoing rapid evolution, marked by the initial implementation of standardized surgical training programs, which are further facilitated by the emergence of new technologies. However, this proliferation is uneven across various countries and hospitals. Objective: To offer a comprehensive overview of the existing surgical training programs throughout Europe, with a specific focus on the accessibility of simulation resources and standardized surgical programs. Design setting and participants: A dedicated survey was designed and spread in May 2022 via the European Association of Urology (EAU) mail list, to Young Urologist Office (YUO), Junior membership, European Urology Residents Education Program participants between 2014 and 2022, and other urologists under 40 yr, and via the EAU Newsletter. Intervention: A 64-item, online-based survey in accordance with the Checklist for Reporting Results of Internet E-Surveys (CHERRIES) using the platform of Survey Monkey (Portland, OR, USA) was realized. Outcome measurements and statistical analysis: The study involved an assessment of the demographic characteristics. Additionally, it explored the type of center, availability of various surgical approaches, presence of training infrastructure, participation in courses, organization of training, and participants' satisfaction with the training program. The level of satisfaction was evaluated using a Likert-5 scale. The subsequent sections delved into surgical training within the realms of open, laparoscopic, robotic, and endoscopic surgery, each explored separately. Finally, the investigation encompassed the presence of a structured training course and the availability of a duly validated final evaluation process. Results and limitations: There were 375 responders with a completion rate of 82%. Among them, 75% were identified as male, 50.6% were young urologists, 31.7% were senior residents, and 17.6% were junior residents. A significant majority of participants (69.6%) were affiliated with academic centers. Regarding the presence of dry lab training facilities, only 50.3% of respondents indicated its availability. Among these centers, 46.7% were primarily focused on laparoscopy training. The availability of virtual and wet lab training centers was even more limited, with rates of 31.5% and 16.2%, respectively. Direct patient involvement was reported in 80.5% of cases for open surgery, 58.8% for laparoscopy, 25.0% for robotics, and 78.6% for endourology. It is worth noting that in <25% of instances, training followed a well-defined standardized program comprising both preclinical and clinical modular phases. Finally, the analysis of participant feedback showed that 49.7% of respondents expressed a satisfaction rating of either 4 or 5 points with respect to the training program. The limitations of our study include the low response rate, predominance of participants from academic centers, and absence of responses from individuals not affiliated with the EAU network. Conclusions: The current distribution of surgical training centers falls short of ensuring widespread access to standardized training programs. Although dry lab facilities are relatively well spread, the availability of wet lab resources remains restricted. Additionally, it appears that many trainees' initial exposure to surgery occurs directly with patients. There is a pressing need for continued endeavors to establish uniform training routes and assessment techniques across various surgical methodologies. Patient summary: Nowadays, the surgical training landscape is heterogeneous across different countries. The implementation of a standardized training methodology to enhance the overall quality of surgical training and thereby improving patient outcomes is needed.

Current practice and unmet training needs in robotic-assisted radical prostatectomy: investigation from the Junior ERUS/YAU working group.

PURPOSE: To access the current scenario of robotic-assisted radical prostatectomy training in multiple centers worldwide. METHODS: We created a multiple-choice questionnaire assessing all details of robotic-assisted radical prostatectomy training with 41 questions divided into three different categories (responder demography, surgical steps, and responder experience). The questionnaire was created and disseminated using the "Google Docs" platform. All responders had an individual invitation by direct message or Email. We selected urologists who had recently finished a postgraduation urologic robotic surgery training (fellowship) in the last five years. We sent 624 invitations to urologists from 138 centers, from January 10th to April 10th, 2022. The answers were reported as percentages and illustrated in pie charts. RESULTS: The response rate was 58% among all centers invited (138/81), 20% among all individual invitations (122/624 answers). Globally, we gathered responses from 23 countries. Most surgeons were older than 34 years, 71% trained in an academic center, and 64% performed less than ten full RARP cases. Transperitoneal is the most common access, and 63% routinely opens the endopelvic fascia. Almost 90% perform the Rocco's stitch, and 94% perform the anastomosis with barbed sutures. Finally, only 31% of surgeons assisted more than 100 cases before moving to the console, and most surgeons (63.9%) performed less than ten full RARP cases during their training. CONCLUSION: By assessing the robotic-assisted radical prostatectomy training status in 23 countries and 81 centers worldwide, we assessed the trainees' demography, step-by-step surgical technique, training perspectives, and impressions of surgeons who trained in the last five years. This data is crucial for a better understanding the trainee's standpoint, addressing potential deficiencies, and implementing improvements needed in the training process. Our study clearly indicates elements of current training modalities that are prone to major improvement.

Robot-Assisted Pyeloplasty with HUGO™ Robotic System: Initial Experience and Optimal Surgical Set-Up at a Tertiary Referral Robotic Center.

Background: In February 2021 Medtronic® (Minneapolis, MN) launched the HUGO™ Robot-Assisted Surgery (RAS) System in the global market. The aim of the current study is to describe the first case series and the optimal setup of robot-assisted pyeloplasty procedure, performed with HUGO RAS system in a tertiary referral robotic center. Methods: Data from consecutive patients who underwent robot-assisted pyeloplasty at Onze-Lieve-Vrouwziekenhuis Hospital (Aalst, Belgium) were recorded. Baseline characteristics, and perioperative and surgical outcomes were collected. Results: Overall, 10 robot-assisted pyeloplasties were performed (October 2022-September 2023). Based on our expertise, the following minor setting changes have been made, relative to the official setup guide: the endoscope port and, subsequently, the left and right-hand ports were positioned more laterally. Additionally, the reserve/4th port was placed more laterally and cranially, and adjusted the arm cart's tilt angle, reducing it from -30° to -15°. The median docking time was 8 (interquartile range [IQR]: 7.2-9.8) minutes, and the median active console time was 89.5 (80.0-95.8) minutes. No conversion to open/laparoscopic surgery or perioperative complications was encountered. A single technical problem was recorded in 1 (10%) procedure. Specifically, one arm was blocked, and the procedure was accomplished with three arms without compromising the procedure success. Conclusions: This study represents the first worldwide series of robot-assisted pyeloplasty performed with the HUGO RAS system and shows promising results. The procedure might be safely performed with this robotic platform achieving optimal perioperative outcomes.

Robot-assisted Radical Prostatectomy Performed with Different Robotic Platforms: First Comparative Evidence Between Da Vinci and HUGO Robot-assisted Surgery Robots.

BACKGROUND: In the field of robotic surgery, there is a lack of comparative evidence on surgical and functional outcomes of different robotic platforms. OBJECTIVE: To assess the outcomes of patients receiving robot-assisted radical prostatectomy (RARP) at a high-volume robotic center with daVinci and HUGO robot-assisted surgery (RAS) surgical systems. DESIGN, SETTING, AND PARTICIPANTS: We analyzed the data of 542 patients undergoing RARP ± extended pelvic lymph node dissection at OLV hospital (Aalst, Belgium) between 2021 and 2023. All procedures were performed by six surgeons using daVinci or HUGO RAS robots; the use of one platform rather than the other did not follow any specific preference and/or indication. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Multivariable analyses investigated the association between robotic system (daVinci vs HUGO RAS) and surgical outcomes after adjustment for patient- and tumor-related factors. Urinary continence recovery was defined as the use of no/one safety pad. RESULTS AND LIMITATIONS: A total of 378 (70%) and 164 (30%) patients underwent RARP with daVinci and HUGO RAS surgical systems, respectively. Despite a higher rate of palpable disease in the HUGO RAS group (34% vs 25%), baseline characteristics did not differ between the groups (all p > 0.05). After adjusting for confounders, we did not find evidence of a difference between the groups with respect to operative time (estimate: 16.71; 95% confidence interval [CI]: -6.35, 39.78; p = 0.12), estimated blood loss (estimate: 3.12; 95% CI: -67.03, 73.27; p = 0.9), and postoperative Clavien-Dindo ≥2 complications (odds ratio [OR]: 1.66; 95% CI: 0.34, 8.15; p = 0.5). On final pathology, 55 (15%) and 20 (12%) men in, respectively, the daVinci and the HUGO RAS group had positive surgical margins (PSMs; p = 0.5). On multivariable analyses, we did not find evidence of an association between a robotic system and PSMs (OR: 1.08; 95% CI: 0.56, 2.07; p = 0.8). Similarly, the odds of recovering continence did not differ between daVinci and HUGO RAS cases after both 1 mo (OR: 0.78; 95% CI: 0.45, 1.38; p = 0.4) and 3 mo (OR: 1.17; 95% CI: 0.49, 2.79; p = 0.7). CONCLUSIONS: Among patients receiving RARP with daVinci or HUGO RAS surgical platforms, we did not find differences in surgical and functional outcomes between the robots. This may be a result of a standardized surgical technique that allowed surgeons to transfer their skills between robotic systems. Awaiting future investigations with longer follow-up, these results have important implications for patients, surgeons, and health care policymakers. PATIENT SUMMARY: We compared surgical and functional outcomes of patients receiving robot-assisted radical prostatectomy with daVinci versus HUGO robot-assisted surgery (RAS) robots. The two platforms were able to achieve similar outcomes, suggesting that the introduction of HUGO RAS is safe and allows for optimal outcomes after radical prostatectomy.

Metaverse Surgical Planning with Three-dimensional Virtual Models for Minimally Invasive Partial Nephrectomy.

The recent integration of new virtual visualization modalities with artificial intelligence and high-speed internet connection has opened the door to the advent of the metaverse in medicine. In this totally virtual environment, three-dimensional virtual models (3DVMs) of the patient's anatomy can be visualized and discussed via digital avatars. Here we present for the first time a metaverse preoperative clinical case discussion before minimally invasive partial nephrectomy. The surgeons' digital avatars met in a virtual room and participated in a virtual consultation on the surgical strategy and clamping approach before the procedure. Robotic or laparoscopic procedures are then carried out according to the simulated surgical strategy. We demonstrate how this immersive virtual reality experience overcomes the barriers of distance and how the quality of surgical planning is enriched by a great sense of "being there", even if virtually. Further investigation will improve the quality of interaction with the models and among the avatars.

Atlas of Intracorporeal Orthotopic Neobladder Techniques After Robot-assisted Radical Cystectomy and Systematic Review of Clinical Outcomes.

BACKGROUND: Multiple and heterogeneous techniques have been described for orthotopic neobladder (ONB) reconstruction after robot-assisted radical cystectomy. Nonetheless, a systematic assessment of all the available options is lacking. OBJECTIVE: To provide the first comprehensive step-by-step description of all the available techniques for robotic intracorporeal ONB together with individual intraoperative, perioperative and functional outcomes based on a systematic review of the literature. DESIGN, SETTING, AND PARTICIPANTS: We performed a systematic review of the literature, and MEDLINE/PubMed, Embase, Scopus, and Web of Science databases were searched to identify original articles describing different robotic intracorporeal ONB techniques and reporting intra- and perioperative outcomes. Studies were categorized according to ONB type, providing a synthesis of the current evidence. Video material was provided by experts in the field to illustrate the surgical technique of each intracorporeal ONB. SURGICAL PROCEDURE: Nine different ONB types were identified: Studer, Hautmann, Y shape, U shape, Bordeaux, Pyramid, Shell, Florence Robotic Intracorporeal Neobladder, and Padua Ileal Neobladder. MEASUREMENTS: Continuous and categorical variables are presented as mean ± standard deviation and as frequencies and proportions, respectively. RESULTS AND LIMITATIONS: Of 2587 studies identified, 19 met our inclusion criteria. No cohort studies or randomized control trials comparing different neobladder types are available. Available techniques for intracorporeal robotic ONB reconstruction have similar operative time, estimated blood loss, intraoperative complications, and length of stay. Major variability exists concerning postoperative complications and functional outcomes, likely related to reporting bias. CONCLUSIONS: Several techniques are described for intracorporeal ONB during robot-assisted radical cystectomy with comparable perioperative outcomes. We provide the first step-by-step surgical atlas for robot-assisted ONB reconstruction. Further comparative studies are needed to assess any advantage of one technique over others. PATIENT SUMMARY: Patients elected for radical cystectomy should be aware that multiple techniques for robotic orthotopic neobladder are available, but that current evidence does not favor one type over the others.

Development of Bleeding Artificial Intelligence Detector (BLAIR) System for Robotic Radical Prostatectomy.

BACKGROUND: Addressing intraoperative bleeding remains a significant challenge in the field of robotic surgery. This research endeavors to pioneer a groundbreaking solution utilizing convolutional neural networks (CNNs). The objective is to establish a system capable of forecasting instances of intraoperative bleeding during robot-assisted radical prostatectomy (RARP) and promptly notify the surgeon about bleeding risks. METHODS: To achieve this, a multi-task learning (MTL) CNN was introduced, leveraging a modified version of the U-Net architecture. The aim was to categorize video input as either "absence of blood accumulation" (0) or "presence of blood accumulation" (1). To facilitate seamless interaction with the neural networks, the Bleeding Artificial Intelligence-based Detector (BLAIR) software was created using the Python Keras API and built upon the PyQT framework. A subsequent clinical assessment of BLAIR's efficacy was performed, comparing its bleeding identification performance against that of a urologist. Various perioperative variables were also gathered. For optimal MTL-CNN training parameterization, a multi-task loss function was adopted to enhance the accuracy of event detection by taking advantage of surgical tools' semantic segmentation. Additionally, the Multiple Correspondence Analysis (MCA) approach was employed to assess software performance. RESULTS: The MTL-CNN demonstrated a remarkable event recognition accuracy of 90.63%. When evaluating BLAIR's predictive ability and its capacity to pre-warn surgeons of potential bleeding incidents, the density plot highlighted a striking similarity between BLAIR and human assessments. In fact, BLAIR exhibited a faster response. Notably, the MCA analysis revealed no discernible distinction between the software and human performance in accurately identifying instances of bleeding. CONCLUSION: The BLAIR software proved its competence by achieving over 90% accuracy in predicting bleeding events during RARP. This accomplishment underscores the potential of AI to assist surgeons during interventions. This study exemplifies the positive impact AI applications can have on surgical procedures.

Outcomes of Salvage Robotic-assisted Radical Prostatectomy in the last decade: systematic review and perspectives of referral centers

ABSTRACT Purpose: Salvage robotic-assisted radical prostatectomy (S-RARP) has gained prominence in recent years for treating patients with cancer recurrence following non-surgical treatments of Prostate Cancer. We conducted a systematic literature review to evaluate the role and outcomes of S-RARP over the past decade. Materials and Methods: A systematic review was conducted, encompassing articles published between January 1st, 2013, and June 1st, 2023, on S-RARP outcomes. Articles were screened according to PRISMA guidelines, resulting in 33 selected studies. Data were extracted, including patient demographics, operative times, complications, functional outcomes, and oncological outcomes. Results: Among 1,630 patients from 33 studies, radiotherapy was the most common primary treatment (42%). Operative times ranged from 110 to 303 minutes, with estimated blood loss between 50 to 745 mL. Intraoperative complications occurred in 0 to 9% of cases, while postoperative complications ranged from 0 to 90% (Clavien 1-5). Continence rates varied (from 0 to 100%), and potency rates ranged from 0 to 66.7%. Positive surgical margins were reported up to 65.6%, and biochemical recurrence ranged from 0 to 57%. Conclusion: Salvage robotic-assisted radical prostatectomy in patients with cancer recurrence after previous prostate cancer treatment is safe and feasible. The literature is based on retrospective studies with inherent limitations describing low rates of intraoperative complications and small blood loss. However, potency and continence rates are largely reduced compared to the primary RARP series, despite the type of the primary treatment. Better-designed studies to assess the long-term outcomes and individually specify each primary therapy impact on the salvage treatment are still needed. Future articles should be more specific and provide more details regarding the previous therapies and S-RARP surgical techniques.

3D Model Artificial Intelligence-Guided Automatic Augmented Reality Images during Robotic Partial Nephrectomy.

More than ever, precision surgery is making its way into modern surgery for functional organ preservation. This is possible mainly due to the increasing number of technologies available, including 3D models, virtual reality, augmented reality, and artificial intelligence. Intraoperative surgical navigation represents an interesting application of these technologies, allowing to understand in detail the surgical anatomy, planning a patient-tailored approach. Automatic superimposition comes into this context to optimally perform surgery as accurately as possible. Through a dedicated software (the first version) called iKidney, it is possible to superimpose the images using 3D models and live endoscopic images during partial nephrectomy, targeting the renal mass only. The patient is 31 years old with a 28 mm totally endophytic right-sided renal mass, with a PADUA score of 9. Thanks to the automatic superimposition and selective clamping, an enucleoresection of the renal mass alone was performed with no major postoperative complication (i.e., Clavien-Dindo < 2). iKidney-guided partial nephrectomy is safe, feasible, and yields excellent results in terms of organ preservation and functional outcomes. Further validation studies are needed to improve the prototype software, particularly to improve the rotational axes and avoid human help. Furthermore, it is important to reduce the costs associated with these technologies to increase its use in smaller hospitals.