The advent of robotic surgical systems had a significant impact on every surgical area, especially urology, gynecology, and general and cardiac surgery. The aim of this article is to delineate robotic surgery, particularly focusing on its historical background, its evolution, its present status, and its future perspectives. A comprehensive literature review was conducted upon PubMed/MEDLINE, using the keywords “robotic surgical system”, “robotic surgical device”, “robotics AND urology”. Additionally, the retrieved articles’ reference lists were investigated. Analysis concentrated on urological surgical systems for laparoscopic surgery that have been given regulatory approval for use on humans. From the late 1980s, before daVinci^® Era in 2000s, ancestor platform as Probot^® and PUMA 560 were described to outline historical perspective. Thus, new robotic competitors of Intuitive Surgical such as Senhance^®, Revo-I^®, Versius^®, Avatera^®, Hinotori^®, and Hugo^TM RAS were illustrated. Although daVinci^® had high level competitiveness, and for many years represented the most plausible option for robotic procedures, several modern platforms are emerging in the surgical market. Growing competition through unique features of the new robotic technologies might extend applications fields, improve diffusion, and increase cost-effectiveness procedures. More experiences are needed to identify the role of these new advancements in surgical branches and in healthcare systems.

Since its introduction in the early 2000s, robotic surgery has represented a significative innovation within a minimally invasive surgery approach. A variety of robotic platforms have been made available throughout the years, and the outcomes related to those platforms have been described in the literature for many types of surgeries. Medtronic’s Hugo^TM RAS system is one of the newest robotic generations launched, but because of its recent placing on the field, comprehensive clinical data are still lacking. The aim of the present state of the art is to address the current literature concerning the use of the Hugo^TM RAS robot in order to report its feasibility, safety and clinical applications in different surgical branches. Two reviewers independently conducted a search on the “PubMed” electronic database, using the keywords “Hugo” and “Hugo RAS”. After the initial screening of 35 results, a total of 15 articles concerning the Hugo RAS system were selected for the review, including both oncological and benign surgery. Patients’ demographic and baseline data were compared including, when available, docking system times, complications and oncological outcomes in the fields of urologic, gynecologic and general surgery. With reference to urological procedures, a total of 156 robot-assisted radical prostatectomies, 10 robot-assisted partial nephrectomies, and 5 robot-assisted adrenalectomies were performed, involving a total of 171 patients. The surgical branch in which the Hugo system found its major application was urology, which was followed by gynecology and general surgery. The Hugo RAS system by Medtronic represents an innovative and safe surgical platform, with excellent perspective for the future and different clinical applications in many surgical branches. More studies are needed to validate the safety and results from this new robotic platform.

The current literature relating to the novel Hugo^TM RAS System lacks consistent data concerning the bedside features of robot-assisted partial nephrectomy (RAPN). To describe the trocar placement and docking settings for RAPN with a three-arm configuration to streamline the procedure with Hugo^TM RAS, between October 2022 and April 2023, twenty-five consecutive off-clamp RAPNs for renal tumors with the Hugo^TM RAS System were performed. We conceived a trouble-free three-arm setting to ease and standardize RAPN trocar placement and docking settings with Hugo^TM RAS. Perioperative data were collected. Post-operative complications were reported according to the Clavien–Dindo classification. The eGFR was calculated according to the CKD–EPI formula. Continuous variables were presented as the median and IQR, while frequencies were reported as categorical variables. Off-clamp RAPNs were successfully performed in all cases without the need for conversion or additional port placement. The median age and BMI were 69 years (IQR, 60–73) and 27.3 kg/m² (IQR, 25.7–28.1), respectively. The median tumor size and R.E.N.A.L. score were 32.5 mm (IQR, 26–43.7) and 6 (IQR, 5–7), respectively. Two patients were affected by cT2 renal tumors. The median docking and console time were 5 (IQR, 5–6) and 90 min (IQR, 68–135.75 min), respectively, with slightly progressive improvements in the docking time achieved. No intraoperative complications occurred alongside clashes between instruments or with the bed assistant. In experienced hands, this simplified three-instrument configuration of the Hugo^TM RAS System for off-clamp RAPN resulted in feasible and safe practice, providing patient-tailored trocar placement and docking with non-inferior peri-perioperative outcomes to other robotic platforms.

Background: The aim of our study was to develop a radiomic tool for the prediction of clinically significant prostate cancer. Methods: From September 2020 to December 2021, 91 patients who underwent magnetic resonance imaging prostate fusion biopsy at our institution were selected. Prostate cancer aggressiveness was assessed by combining the three orthogonal planes-Llocal binary pattern the 3Dgray level co-occurrence matrix, and other first order statistical features with clinical (semantic) features. The 487 features were used to predict whether the Gleason score was clinically significant (≥7) in the final pathology. A feature selection algorithm was used to determine the most predictive features, and at the end of the process, nine features were chosen through a 10-fold cross validation. Results: The feature analysis revealed a detection accuracy of 83.5%, with a clinically significant precision of 84.4% and a clinically significant sensitivity of 91.5%. The resulting area under the curve was 80.4%. Conclusions: Radiomic analysis allowed us to develop a tool that was able to predict a Gleason score of ≥7. This new tool may improve the detection rate of clinically significant prostate cancer and overcome the limitations of the subjective interpretation of magnetic resonance imaging, reducing the number of useless biopsies.

Background: A correct approach to recurrent urinary tract infections (rUTIs) is an important pillar of antimicrobial stewardship. We aim to define an Artificial Neural Network (ANN) for predicting the clinical efficacy of the empiric antimicrobial treatment in women with rUTIs. Methods: We extracted clinical and microbiological data from 1043 women. We trained an ANN on 725 patients and validated it on 318. Results: The ANN showed a sensitivity of 87.8% and specificity of 97.3% in predicting the clinical efficacy of empirical therapy. The previous use of fluoroquinolones (HR = 4.23; p = 0.008) and cephalosporins (HR = 2.81; p = 0.003) as well as the presence of Escherichia coli with resistance against cotrimoxazole (HR = 3.54; p = 0.001) have been identified as the most important variables affecting the ANN output decision predicting the fluoroquinolones-based therapy failure. A previous isolation of Escherichia coli with resistance against fosfomycin (HR = 2.67; p = 0.001) and amoxicillin-clavulanic acid (HR = 1.94; p = 0.001) seems to be the most influential variable affecting the output decision predicting the cephalosporins- and cotrimoxazole-based therapy failure. The previously mentioned Escherichia coli with resistance against cotrimoxazole (HR = 2.35; p < 0.001) and amoxicillin-clavulanic acid (HR = 3.41; p = 0.007) seems to be the most influential variable affecting the output decision predicting the fosfomycin-based therapy failure. Conclusions: ANNs seem to be an interesting tool to guide the antimicrobial choice in the management of rUTIs at the point of care.