Purpose: To summarize the scientific published literature on new robotic surgical platforms with potential use in the urological field, reviewing their evolution from presentation until the present day. Our goal is to describe the current characteristics and possible prospects for these platforms. Materials and Methods: A nonsystematic search of the PubMed, Cochrane library's Central, EMBASE, MEDLINE, and Scopus databases was conducted to identify scientific literature about new robotic platforms other than the Da Vinci ^® system, reviewing their evolution from inception until December 2020. Only English language publications were included. The following keywords were used: “new robotic platforms,” “Revo-I robot,” “Versius robot,” and “Senhance robot.” All relevant English-language original studies were analyzed by one author (R.F.) and summarized after discussion with an independent third party (E.M., S.Y., S.P., and M.A.). Results: Since 1995, Intuitive Surgical, Inc., with the Da Vinci surgical system, is the leading company in the robotic surgical market. However, Revo-I ^® , Versius ^® , and Senhance ^® are the other three platforms that recently appeared on the market with available articles published in peer-reviewed journals. Among these three new surgical systems, the Senhance robot has the most substantial scientific proof of its capacity to perform minimally invasive urological surgery and as such, it might become a contender of the Da Vinci robot. Conclusions: The Da Vinci surgical platform has allowed the diffusion of robotic surgery worldwide and showed the different advantages of this type of technique. However, its use has some drawbacks, especially its price. New robotic platforms characterized by unique features are under development. Of note, they might be less expensive compared with the Da Vinci robotic system. We found that these new platforms are still at the beginning of their technical and scientific validation. However, the Senhance robot is in a more advanced stage, with clinical studies supporting its full implementation.

Introduction and Hypothesis: Robotic sacropexy (RSC) emerged in the last years as a valid alternative to the laparoscopic technique. However, the robotic approach is still limited by platform availability and concerns about cost-effectiveness. Recently, new robotic platforms joined the market, lowering the costs and offering the possibility to expand the robotic approach. The aim of our study was to demonstrate the technical feasibility and safety of the procedure with this new platform along with the description of our surgical setting. Materials and Methods: We reported data on the first five consecutive patients who underwent RSC at Onze Lieve Vrouw Hospital (Aalst, Belgium), performed with the novel HUGO™ Robot-Assisted Surgery (RAS) System. The platform consists of four fully independent carts, an open console, and a system tower equipped for both laparoscopic and robotic surgery. We collected patients' characteristics, intraoperative data, intraoperative complications, and clashes of instruments. Results: All procedures were completed according to the same surgical setting and technique. No need for conversion to open/laparoscopic surgery and/or for additional port placement was required. No intraoperative complications, instrument clashes, or system failure that compromised the surgery's completion were recorded. Median interquartile range docking, operative, and console time were 8 (6–9), 130 (115–165), and 80 (80–115) minutes, respectively. Conclusion: This series represents the first worldwide report of a robot-assisted sacropexy executed with the novel HUGO RAS System. Awaiting future investigation, this preliminary experience provides relevant data in terms of operative room settings and perioperative outcomes that might be helpful for future adopters of this platform.

The prevalence of renal cell carcinoma (RCC) is increasing due to advanced imaging techniques. Surgical resection is the standard treatment, involving complex radical and partial nephrectomy procedures that demand extensive training and planning. Furthermore, artificial intelligence (AI) can potentially aid the training process in the field of kidney cancer. This review explores how artificial intelligence (AI) can create a framework for kidney cancer surgery to address training difficulties. Following PRISMA 2020 criteria, an exhaustive search of PubMed and SCOPUS databases was conducted without any filters or restrictions. Inclusion criteria encompassed original English articles focusing on AI’s role in kidney cancer surgical training. On the other hand, all non-original articles and articles published in any language other than English were excluded. Two independent reviewers assessed the articles, with a third party settling any disagreement. Study specifics, AI tools, methodologies, endpoints, and outcomes were extracted by the same authors. The Oxford Center for Evidence-Based Medicine’s evidence levels were employed to assess the studies. Out of 468 identified records, 14 eligible studies were selected. Potential AI applications in kidney cancer surgical training include analyzing surgical workflow, annotating instruments, identifying tissues, and 3D reconstruction. AI is capable of appraising surgical skills, including the identification of procedural steps and instrument tracking. While AI and augmented reality (AR) enhance training, challenges persist in real-time tracking and registration. The utilization of AI-driven 3D reconstruction proves beneficial for intraoperative guidance and preoperative preparation. Artificial intelligence (AI) shows potential for advancing surgical training by providing unbiased evaluations, personalized feedback, and enhanced learning processes. Yet challenges such as consistent metric measurement, ethical concerns, and data privacy must be addressed. The integration of AI into kidney cancer surgical training offers solutions to training difficulties and a boost to surgical education. However, to fully harness its potential, additional studies are imperative.