Background: The da Vinci Single-Port Robot System (DVSP) allows three robotic instruments and an articulated scope to be inserted through a single small incision. It received FDA approval in 2014 and was first introduced in 2018. The aim of this new system was to overcome the limitations of single-incision laparoscopic and robotic surgery. Since then, it has been approved for use only for urologic and transoral surgeries in some countries. It has been used as part of experimental protocols in general surgery. Objective: By obtaining the CE mark at the end of January 2024, DVSP will soon enter the European market. This review aims to comprehensively describe the applications of DVSP in general surgery. Design: A search of PubMed, Embase, and Ebsco databases up to March 2024 was conducted, with registration in PROSPERO (CRD42024536430), following the preferred reporting items for Systematic reviews and Meta-analyses for scoping review (PRISMA-Scr) guidelines. All the studies about the use of DVSP in general surgery were included. Results: Fifty-six studies were included. The following surgical areas of use were identified: transabdominal and transanal colorectal, cholecystectomy, abdominal wall repair, upper gastroesophageal tract, liver, pancreas, breast, and thyroid surgery. The reported surgical and short-term outcomes are promising; a wide range of procedures have been performed safely. Some groups have found advantages, such as faster discharge, shorter operative time, and less postoperative pain compared to multiport robotic surgery. Conclusion: Five years after its initial clinical applications, the use of the DVSP in general surgery procedures has demonstrated feasibility and safety. Hernia repair, cholecystectomy, and colorectal surgery emerge as the most frequently conducted interventions with this robotic system. Nevertheless, there is anticipation for further studies with larger sample sizes and extended follow-up periods to provide more comprehensive insights and data on the long-term outcomes, including the incidence of incisional hernia. Graphical

Background: With rectum-sparing protocols becoming more common for rectal cancer treatment, this study aimed to predict the pathological complete response (pCR) to preoperative chemoradiotherapy (pCRT) in rectal cancer patients using pre-treatment MRI and a radiomics-based machine learning approach. Methods: We divided MRI-data from 102 patients into a training cohort (n = 72) and a validation cohort (n = 30). In the training cohort, 52 patients were classified as non-responders and 20 as pCR based on histological results from total mesorectal excision. Results: We trained various machine learning models using radiomic features to capture disease heterogeneity between responders and non-responders. The best-performing model achieved a receiver operating characteristic area under the curve (ROC-AUC) of 73% and an accuracy of 70%, with a sensitivity of 78% and a positive predictive value (PPV) of 80%. In the validation cohort, the model showed a sensitivity of 81%, specificity of 75%, and accuracy of 80%. Conclusions: These results highlight the potential of radiomics and machine learning in predicting treatment response and support the integration of advanced imaging and computational methods for personalized rectal cancer management.

Background: Transabdominal pre-peritoneal inguinal hernia repair using the da Vinci Single-Port robot (SP-TAPP) is currently performed in few centers. We aimed to define the learning curve for SP-TAPP by analyzing operative times. Methods: The operative times of 122 SP-TAPP performed between 2019 and 2024 were retrospectively analyzed. The following phases were analyzed: docking time (DT); pre-robot time (PRT, from skin incision to side cart placement); flap closure time (FCT); console time (CT), and overall time (OT). Cumulative sum analysis (CUSUM) was used to analyze learning curves. Surgical and 30-day outcome were analyzed. Results: The DT has remained constant over time ( P > 0.9). PRT was divided into 3 phases with n1 = 5, n2 = 95 and n3 = 4, in which there was a progressive decrease in time (14.8 vs 11.9 vs 6.8 min; P = 0.08). In FCT and CT, 3 phases were identified in which times remained stable ( P > 0.9 and P = 0.7). CUSUM analysis of OT identified 3 phases consisting of n1 = 13, n2 = 100 and n3 = 9 in which there was a progressive decrease in times (82 vs 72 vs 62 min; P = 0.3). Analysis of complications and early surgical outcomes did not differ except for estimated blood loss, although this was a clinically insignificant finding. Conclusions: The learning curve for SP-TAPP is rapid and it shows how the technical skills are transferable between the multiport platform and the da Vinci Single Port robotic system for an experienced surgeon. An improvement is evident in PRT and OT, also compared to multiport systems, showing a potential for the platform to increase surgical activity.

Background: Minimally invasive surgery is recognized as the gold standard for cholecystectomy, with various approaches having been implemented over time. Since 2018, the da Vinci Single-Port (DVSP) robotic system (Intuitive) has been used in experimental surgical contexts, revitalizing interest in single-site surgical techniques. The authors’ aim is to describe the learning curve associated with single-port robotic cholecystectomy (SPRC). Methods: A prospective series of 266 consecutive off-label SPRC performed by a single surgeon experienced in laparoscopy, single-site surgery, and multiport robotic surgery was analyzed. These procedures were conducted under an Institutional Review Board–approved protocol. Preoperative, intraoperative, and postoperative data were collected and organized. Indications for SPRC included symptomatic cholelithiasis, acute cholecystitis, chronic cholecystitis, porcelain gallbladder, gallbladder polyps, choledocholithiasis, and gallstone pancreatitis. A learning curve was generated using the cumulative sum analysis (CUSUM) to assess changes in overall operation time, docking time, pre-console time, and surgeon console time. Results: Our analysis demonstrated a statistically significant reduction in docking time and pre-console time (P<0.001) in the 3 phases identified by the CUSUM analysis. The CUSUM analysis identified only 1 phase regarding the console time with a mean time of 20 (7 to 113) minutes. The average overall time was 59 (19 to 175) minutes. CUSUM analysis identified 3 phases for overall time, with reduction from 59 to 46 minutes (P<0.001). The general characteristics of the groups identified for OT were homogeneous. Analysis of early surgical outcomes did not differ between the groups. Conclusions: SPRC is a safe and feasible procedure, the docking time, pre-console time, and overall time were improving over time, meanwhile the console time was stable throughout the case series demonstrating a significant ability transfer between other mininvasive approaches and DVSP Platform.

Pouchitis is an idiopathic inflammatory disease that may occur in ileal pouches, and it can lead to ileal pouch failure. This was a single-center, randomized, double-blinded, placebo-controlled trial that assessed the effect of Lactobacillus casei (L. casei) DG®, a probiotic strain, on the ileal pouch mucosa to determine the crosstalk between microbiota and mucosal immune system. Fifty-two patients undergoing restorative proctocolectomy were recruited and randomly assigned to receive a daily oral supplementation of L. casei DG® (n = 26) or placebo (n = 26) for 8 weeks from the ileostomy closure (T0) to a pouch endoscopy after 8 weeks (T1) and 1 year (T2). Ileal pouch mucosa samples were collected at T0, T1, and T2. At T1, the L. casei DG®-supplemented group showed a significant reduction of inflammatory cytokines levels compared to T0 baseline levels in the pouch mucosa, whereas in the placebo group cytokines levels resulted stable. In conclusion, probiotic manipulation of mucosal microbiota by L. casei DG®-supplementation after stoma closure in patients who underwent restorative proctocolectomy has a beneficial impact on the ileal pouch microenvironment. Registration number: NCT03136419 (http://www.clinicaltrials.gov).