Hybrid operating room applications for precision hepatobiliary surgery: A narrative review.

This review summarizes the key applications of a hybrid operating room (HOR) in hepatobiliary surgery and explores the advantages, limitations, and future directions of its utilization. A comprehensive literature search was conducted in PubMed to identify articles reporting on the utilization of HORs in liver surgery. So far, the HOR has been limitedly applied in hepatobiliary surgery. It can offer an optimal environment for combining radiological and surgical interventions and for performing image-guided surgical navigation.

Training in robotic-assisted surgery: a systematic review of training modalities and objective and subjective assessment methods.

INTRODUCTION: The variety of robotic surgery systems, training modalities, and assessment tools within robotic surgery training is extensive. This systematic review aimed to comprehensively overview different training modalities and assessment methods for teaching and assessing surgical skills in robotic surgery, with a specific focus on comparing objective and subjective assessment methods. METHODS: A systematic review was conducted following the PRISMA guidelines. The electronic databases Pubmed, EMBASE, and Cochrane were searched from inception until February 1, 2022. Included studies consisted of robotic-assisted surgery training (e.g., box training, virtual reality training, cadaver training and animal tissue training) with an assessment method (objective or subjective), such as assessment forms, virtual reality scores, peer-to-peer feedback or time recording. RESULTS: The search identified 1591 studies. After abstract screening and full-texts examination, 209 studies were identified that focused on robotic surgery training and included an assessment tool. The majority of the studies utilized the da Vinci Surgical System, with dry lab training being the most common approach, followed by the da Vinci Surgical Skills Simulator. The most frequently used assessment methods included simulator scoring system (e.g., dVSS score), and assessment forms (e.g., GEARS and OSATS). CONCLUSION: This systematic review provides an overview of training modalities and assessment methods in robotic-assisted surgery. Dry lab training on the da Vinci Surgical System and training on the da Vinci Skills Simulator are the predominant approaches. However, focused training on tissue handling, manipulation, and force interaction is lacking, despite the absence of haptic feedback. Future research should focus on developing universal objective assessment and feedback methods to address these limitations as the field continues to evolve.

Artificial intelligence-aided ultrasound imaging in hepatopancreatobiliary surgery: where are we now?

BACKGROUND: Artificial intelligence (AI) models have been applied in various medical imaging modalities and surgical disciplines, however the current status and progress of ultrasound-based AI models within hepatopancreatobiliary surgery have not been evaluated in literature. Therefore, this review aimed to provide an overview of ultrasound-based AI models used for hepatopancreatobiliary surgery, evaluating current advancements, validation, and predictive accuracies. METHOD: Databases PubMed, EMBASE, Cochrane, and Web of Science were searched for studies using AI models on ultrasound for patients undergoing hepatopancreatobiliary surgery. To be eligible for inclusion, studies needed to apply AI methods on ultrasound imaging for patients undergoing hepatopancreatobiliary surgery. The Probast risk of bias tool was used to evaluate the methodological quality of AI methods. RESULTS: AI models have been primarily used within hepatopancreatobiliary surgery, to predict tumor recurrence, differentiate between tumoral tissues, and identify lesions during ultrasound imaging. Most studies have combined radiomics with convolutional neural networks, with AUCs up to 0.98. CONCLUSION: Ultrasound-based AI models have demonstrated promising accuracies in predicting early tumoral recurrence and even differentiating between tumoral tissue types during and after hepatopancreatobiliary surgery. However, prospective studies are required to evaluate if these results will remain consistent and externally valid.

Robotic hepaticojejunostomy training in novices using robotic simulation and dry-lab suturing (ROSIM): randomized controlled crossover trial.

BACKGROUND: Robotic suturing training is in increasing demand and can be done using suture-pads or robotic simulation training. Robotic simulation is less cumbersome, whereas a robotic suture-pad approach could be more effective but is more costly. A training curriculum with crossover between both approaches may be a practical solution. However, studies assessing the impact of starting with robotic simulation or suture-pads in robotic suturing training are lacking. METHODS: This was a randomized controlled crossover trial conducted with 20 robotic novices from 3 countries who underwent robotic suturing training using an Intuitive Surgical® X and Xi system with the SimNow (robotic simulation) and suture-pads (dry-lab). Participants were randomized to start with robotic simulation (intervention group, n = 10) or suture-pads (control group, n = 10). After the first and second training, all participants completed a robotic hepaticojejunostomy (HJ) in biotissue. Primary endpoint was the objective structured assessment of technical skill (OSATS) score during HJ, scored by two blinded raters. Secondary endpoints were force measurements and a qualitative analysis. After training, participants were surveyed regarding their preferences. RESULTS: Overall, 20 robotic novices completed both training sessions and performed 40 robotic HJs. After both trainings, OSATS was scored higher in the robotic simulation-first group (3.3 ± 0.9 vs 2.5 ± 0.8; p = 0.049), whereas the median maximum force (N) (5.0 [3.2-8.0] vs 3.8 [2.3-12.8]; p = 0.739) did not differ significantly between the groups. In the survey, 17/20 (85%) participants recommended to include robotic simulation training, 14/20 (70%) participants preferred to start with robotic simulation, and 20/20 (100%) to include suture-pad training. CONCLUSION: Surgical performance during robotic HJ in robotic novices was significantly better after robotic simulation-first training followed by suture-pad training. A robotic suturing curriculum including both robotic simulation and dry-lab suturing should ideally start with robotic simulation.

Healthcare cost expenditure for robotic versus laparoscopic liver resection: a bottom-up economic evaluation.

BACKGROUND: Minimally invasive liver surgery (MILS) is increasingly performed via the robot-assisted approach but may be associated with increased costs. This study is a post-hoc comparison of healthcare cost expenditure for robotic liver resection (RLR) and laparoscopic liver resection (LLR) in a high-volume center. METHODS: In-hospital and 30-day postoperative healthcare costs were calculated per patient in a retrospective series (October 2015-December 2022). RESULTS: Overall, 298 patients were included (143 RLR and 155 LLR). Benefits of RLR were lower conversion rate (2.8% vs 12.3%, p = 0.002), shorter operating time (167 min vs 198 min, p = 0.044), and less blood loss (50 mL vs 200 mL, p < 0.001). Total per-procedure costs of RLR (€10260) and LLR (€9931) were not significantly different (mean difference €329 [95% bootstrapped confidence interval (BCI) €-1179-€2120]). Lower costs with RLR due to shorter surgical and operating room time were offset by higher disposable instrumentation costs resulting in comparable intraoperative costs (€5559 vs €5247, mean difference €312 [95% BCI €-25-€648]). Postoperative costs were similar for RLR (€4701) and LLR (€4684), mean difference €17 [95% BCI €-1357-€1727]. When also considering purchase and maintenance costs, RLR resulted in higher total per-procedure costs. DISCUSSION: In a high-volume center, RLR can have similar per-procedure cost expenditure as LLR when disregarding capital investment.