Introduction: Robotic liver resection has predominantly been performed using the da Vinci surgical system, with limited experience reported for alternative platforms. The Hugo™ Robotic-Assisted Surgery (RAS) system is a newly introduced modular robotic platform; however, its application in hepatic resection remains poorly documented. To our knowledge, we report the first clinical experience of robotic left lateral sectionectomy using the Hugo RAS system in a cirrhotic patient and describe its technical characteristics compared with the da Vinci Xi and single-port (SP) platforms. Case presentation: A 56-year-old woman with chronic hepatitis B–related cirrhosis presented with a 2.8-cm hepatocellular carcinoma in segment III. Robotic left lateral sectionectomy was successfully performed using the Hugo RAS system, with no intraoperative complications or blood transfusion. The operative time was 220 minutes. The postoperative course was unremarkable, apart from a Clavien–Dindo grade I wound hematoma, and the patient was discharged on postoperative day 6. Discussion: The modular arm architecture required meticulous setup and docking to minimize arm-to-arm interference, particularly in upper abdominal surgery. Nevertheless, the open-console design and laparoscopic-style hand controllers provided ergonomic advantages and facilitated adaptation for surgeons experienced in laparoscopic liver surgery. Conclusions: This initial experience suggests that the Hugo RAS system can be used safely and effectively for robotic left lateral sectionectomy in cirrhotic patients. Larger cohorts, refinement of liver-specific docking strategies, and expansion of the instrument portfolio are needed to better define the role of modular robotic platforms in minimally invasive liver surgery.
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Suk Kyun Hong
New Generation University College
Su young Hong
New Generation University College
YoungRok Choi
Seoul National University Hospital
International Journal of Surgery Case Reports
Seoul National University Hospital
New Generation University College
Online Technologies (United States)
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Hong et al. (Tue,) studied this question.
synapsesocial.com/papers/6a2117dfd499ed480b170b82 — DOI: https://doi.org/10.1097/rc9.0000000000000565