Robotic liver transplantation surgery: A comprehensive review of minimally invasive techniques, surgical and educational advancements

Abstract

Robotic liver surgery as well as robotic liver transplantation surgery is gaining significant ground in modern minimally invasive liver surgery techniques with continuously improving surgical outcomes and multiple benefits for liver transplant recipients. The multiple benefits of robotic liver transplantation include sharper visualization of the anatomy and surgical approach for surgeons, reduced postoperative pain, and less hospital stay time for postoperative liver transplant recipients. In this review, recent surgical techniques and surgical innovations in the field of robotic liver transplantation are explored. Noteworthy is the attempt to explore the future implications in robotic liver transplant surgery as they are shaped in the modern era following the radical development of telemedicine and artificial intelligence in optimizing surgical techniques and learning procedures for the benefit of robotic liver surgeons and transplant patients.

Key Words: Liver surgery; Transplantation; Robotics; Artificial intelligence; Hepatectomy

Core Tip: Robotic liver transplantation represents a significant advancement in hepatobiliary surgery, combining minimally invasive techniques with enhanced precision, improved ergonomics, and superior intraoperative control. Robotic donor hepatectomy and graft implantation reduce morbidity, optimize vascular and biliary anastomoses, and support faster postoperative recovery. Integration of artificial intelligence and telemedicine offers real-time guidance, advanced surgical metrics, and predictive modeling, facilitating safer procedures and structured surgeon training. As robotic platforms evolve, they promise to redefine liver transplantation standards, emphasizing precision, safety, and improved patient outcomes.

INTRODUCTION

Living donor liver transplantation is one of the most modern therapeutic pillars in transplant surgery. Advances in minimally invasive liver surgery techniques tend to establish robotic liver transplantation as an important modern transplantation surgical approach with minimal short- and long-term complications unlike conventional techniques to date[1,2]. Minimally invasive surgery, predominantly laparoscopic and subsequently robotic surgery had a significant impact on donor hepatectomy by reducing surgical invasiveness[1]. With the development and optimization of different robotic systems worldwide, the scope and impact had contributed significantly in this direction by continuously improving surgical transplantation standards[1-3]. In this review, we examine recent surgical techniques and innovations in the field of robotic liver transplantation and explore new future horizons with the contribution of telemedicine and artificial intelligence (AI) in the optimization of surgical techniques and outcomes.

LITERATURE REVIEW

This narrative review was conducted using eligibility criteria structured according to the Population, Intervention, Comparator, and Outcome framework. A systematic electronic search was performed in PubMed, Scopus/MEDLINE, and Google Scholar for studies published between 2015 and 2025, initially in July 2025 and updated in December 2025. Search terms included combinations of “robotic surgery”, “liver transplantation”, “liver surgery”, “robotic liver transplantation”, “transplantation”, and “donor hepatectomy”. Only English-language studies involving human subjects were considered. Titles and abstracts were screened for relevance, followed by full-text review of studies reporting outcomes of robotic liver transplantation or robotic donor hepatectomy. Reference lists of eligible articles were manually screened to identify additional relevant studies, and duplicate records were removed. Studies lacking full-text availability or clear reporting of surgical approaches and postoperative outcomes were excluded. Eligible studies, primarily original and observational research, were qualitatively analyzed. This review provides an updated synthesis of surgical and postoperative outcomes in robotic liver transplantation, highlighting the potential benefits of minimally invasive techniques and discussing current practice, limitations, and future perspectives, including emerging applications of telemedicine and AI.

RESULTS

Robotic surgical techniques

Current developments in robotic liver transplantation have focused on optimizing surgical techniques to provide greater precision and lower complications. Robotic liver transplantation surgery is usually a fully robotic or hybrid technique and the Da Vinci surgical system is used for graft implantation, vascular anastomoses and biliary reconstruction. Important techniques include the use of 3D-imaging for increased anastomotic accuracy and robotic suturing for hepatic artery and portal vein anastomoses[3].

Donor hepatectomy (involves right lobe, left lateral lobe and liver positioning in adults and older children)[3,4] is now also minimally invasive, which has opened up robotic-assisted liver graft retrieval with more control of parenchymal transection and reduced donor morbidity[4,5]. Robotic liver transplantation has been shown to provide similar or superior results in vascular anastomoses due to the system’s ability to stabilize instruments and reduce tremor during microvascular suturing[4-6]. More details of current robotic surgical approaches are presented in Table 1[3-7].

Table 1 Current robotic surgical approaches for donor and recipient hepatectomy.

	Surgical approaches
Donor hepatectomy[3-7]	Minimally invasive approaches are increasingly applied to right lobe, left lateral lobe, and adult or paediatric grafts
	Robotic assistance allows improved control of parenchymal transection and may reduce donor morbidity
	Patient positioning: Trendelenburg position to enhance upper abdominal exposure
	Port placement: Five ports (one 12-mm camera port and four 8-mm robotic working ports) arranged in a semicircular or fan-shaped configuration for optimal triangulation
	Liver mobilization: Atraumatic robotic manipulation enables precise division of hepatic ligaments
	Intraoperative imaging: Robotic intraoperative ultrasound facilitates detailed vascular mapping
	Vessel and bile duct dissection: High precision achieved using robotic bipolar forceps and energy devices, minimizing thermal injury
	Parenchymal transection: Performed using ultrasound and bipolar energy devices, frequently guided by indocyanine green fluorescence to visualize bile ducts and vascular structures
Recipient hepatectomy[3-7]	Patient positioning: Supine with reverse Trendelenburg tilt to improve venous return and exposure
	Port placement: Similar to donor configuration, adjusted for patient anatomy and prior surgical history
	Native liver removal: Robotic mobilization with precise control of the hepatic artery, portal vein, and bile duct, minimizing blood loss
	IVC: Preservation of the retrohepatic IVC using the piggyback technique
Graft implantation[3-7]	Caval anastomosis: Performed robotically in side-to-side or end-to-end fashion
	Portal vein anastomosis: Completed under robotic visualization with fine sutures
	Hepatic artery anastomosis: Performed robotically using microsurgical techniques or via mini-laparotomy with a surgical microscope
	Biliary reconstruction: End-to-end anastomosis preferred; Roux-en-Y hepatojejunostomy used when necessary. Robotic suturing enhances precision and may reduce bile leak rates
Operative outcomes[3-7]	Robotic liver transplantation offers stable instrumentation and tremor reduction, facilitating high-quality vascular and biliary anastomoses
	Operative time is influenced by team experience, anatomical variability, and graft complexity
	Reported hospital length of stay is approximately 7.5 days

IVC: Inferior vena cava.

The significant advantages of robotic liver transplantation

Despite the longer intraoperative time compared to open transplantation, robotic hepatic transplantation has several advantages[1,8]. It seems that robotic access gives the surgeon more stable imaging with enhanced magnification, better ergonomics and a wider range of angles especially in movements to explore the anatomy of the area[1]. Furthermore, it allows greater integrity of the abdominal wall, better sutures and faster atraumatic liver mobilization[1]. In a 2015 study, the group of patients who underwent robotic technique had trauma-related complications, whereas liver-related complications (bile leakage, stenosis formation) were statistically insignificant in this study group[1,9,10]. In addition, in contrast to laparoscopic surgery, the reduction of postoperative pain, blood loss and hospital stay, as well as a tendency for lower morbidity are important advantages when using the robotic approach[1,2,11]. Similar results are also drawn from a recent study in a series of fully robotic liver transplants in a recipient from robotic living donors[12-14] with faster discharge and reduced intraoperative bleeding compared to laparoscopic and open approaches[14-18].

From a translational and training perspective, studies highlighted that the introduction of the robotic platform enables realistic simulation of open donor surgery, potentially contributing to reduced morbidity for both donors and recipients[1,2,13]. Most recently, other studies showed that while overall morbidity and mortality were comparable among open, laparoscopic, and robotic donor hepatectomy in both adult and paediatric recipients, robotic hepatectomy was associated with lower rates of major morbidity, particularly in paediatric recipients, supporting its role as a safe and potentially advantageous approach in selected settings[12,18]. Therefore, this study extols the better intraoperative outcomes of recipients despite undergoing open implantation[19]. In another study, after comparing 25 robotic laparoscopic liver surgery (LLS) donor hepatectomies with 50 laparoscopic LLS donor hepatectomies, they concluded that robotic LLS is a safe procedure with comparable results to the laparoscopic approach in terms of donor morbidity and overall recipient outcome[19,20], and it appears that postoperative aesthetic outcomes in the patient make robotics a safe and widely preferred option[15,16,21-24].

In a study by Broering et al[24], for the period of 2011-2023, a total of 1827 donor hepatectomies were performed, including 165 laparoscopic, 1016 robotic and 646 open, it was shown that robotic donor hepatectomy offers better surgical outcomes compared to laparoscopic and open approaches. In robotic transplant recipients, major morbidity rates were lower compared to traditional transplantation techniques, mainly related to in-hospital biliary complications[25]. To avoid such complications, the 2023 guidelines recommend a combination of robotic and indocyanine green fluoroscopy for optimal intraoperative biliary transection and suturing[25]. Robotic liver resection is associated with fewer complications, less advanced recurrence, and the highest quality-adjusted life years compared with laparoscopic and open approaches, supporting its value despite higher initial costs[24,26].

In terms of surgical technique, a recent study showed that liver grafts that were retrieved via robotic graft harvesting had fewer graft pores that required anastomosis[24]. In addition, robotic surgery demonstrated comparable graft survival and improved recipient survival[25-30]. Robotic donor hepatectomy has been associated with favorable postoperative outcomes when compared with open and conventional laparoscopic approaches[31-34]. Pooled analyses demonstrated significantly lower postoperative peak serum bilirubin levels following robotic procedures, indicating improved early postoperative liver function[28,34]. Similarly, it is reported that reduced postoperative mean peak alanine aminotransferase and aspartate aminotransferase levels, as well as lower total bilirubin values after robotic hepatectomy compared with open and laparoscopic techniques[30]. Beyond biochemical outcomes, reduced overall morbidity, shorter intensive care unit and hospital stays, and improved postoperative pain control related to pneumonia are observed in patients undergoing large robotic hepatectomy[30,31,34,35]. Robotic liver resection is associated with a significantly attenuated local and systemic inflammatory response and better preservation of immune competence compared with open liver resection[36], likely reflecting reduced tissue trauma and cytokine release in the perioperative and late postoperative period[37,38]. Studies from 2025-2026 indicate that robotic liver surgery achieves safety and clinical outcomes comparable to open and laparoscopic approaches, while offering reduced blood loss and shorter hospital stay without an increase in major complications[37-40] (Table 2).

Table 2 Key studies for robotic liver transplantation: Procedures and surgical outcomes.

Ref.	Procedures	Outcomes
Muttillo et al[37], 2025	Multicenter retrospective series of robotic liver resections for malignant tumors. Lesions stratified by vascular proximity: NCMV: No contact with major vessels; CMV: Contact with portal and/or hepatic veins without invasion. All resections performed with Da Vinci Xi by expert HPB surgeons. Comparable surgical complexity after PSM (anatomical resections, major hepatectomies, IWATE ≥ 7)	Intraoperative outcomes: (1) Operative time: No difference after PSM; (2) Blood loss/transfusions: Comparable; (3) Conversion rate: No difference after PSM; and (4) Pringle maneuver: More frequent in CMV 49.8% vs 31.2% (P = 0.001). Postoperative outcomes: (1) Overall morbidity: Comparable; (2) Major complications (CD III-IV): No difference; (3) Length of stay: Similar; (4) Reoperation, readmission, 90-day mortality: No differences; and (5) Oncological radicality (R0): Preserved
Broering et al[38], 2025	Single-center analysis of 339 living liver donors (comparative study). Left lobe donor hepatectomy performed via: (1) Robotic approach (n = 267); and (2) Open approach (n = 72). All cases derived from a prospectively maintained registry (2011-2023). Fully robotic technique used for donor hepatectomy focus on donor safety and perioperative outcomes	Donor outcomes: (1) Estimated blood loss: Robotic: 77 mL vs open: 316 mL (P < 0.001); (2) Overall donor morbidity: Robotic: 6% vs open: 18% (P = 0.003); (3) Length of hospital stay: Robotic: 3 days vs open: 5 days (P < 0.001); and (4) No increase in donor complications with robotic approach. Recipient outcomes. Overall recipient morbidity: Lower with robotic graft retrieval 40% vs 59% (P = 0.033)
Chiarella et al[39], 2025	Multicenter retrospective study of robotic liver resections. 10 European HPB centers, 1070 consecutive robotic liver resections. 921 resections for malignancy included in analysis. Patients stratified by parenchymal transection technique: (1) MAMBA technique: Clamp-crush method using double bipolar robotic forceps, no laparoscopic ultrasonic dissector; and (2) Robo-lap technique: Hybrid approach combining laparoscopic ultrasonic dissector, robotic energy devices for dissection and hemostasis. 1:1 PSM to balance baseline and surgical complexity	Intraoperative outcomes: (1) Operative time: No significant difference after PSM; (2) Estimated blood loss: Comparable between techniques; and (3) Conversion rate: No difference between groups. Postoperative outcomes: (1) Overall morbidity: Similar between MAMBA and Robo-lap; (2) Postoperative complications: No significant differences; and (3) No increase in adverse outcomes with fully robotic transection
Haruki et al[40], 2025	10025 donor hepatectomies (open/hybrid: 8310, laparoscopic: 1479, robotic: 236). Vanguard multicenter retrospective study (16 institutions, 2013-2022). Analysis focused on severe donor complications (Clavien-Dindo IIIb-V). Donor hepatectomies stratified by approach: Open/hybrid, MIS (laparoscopic, robotic). Complications recorded using standardized case report forms	Donor outcomes: (1) Overall severe complications: Grade IIIb: 1.17%, grade IV: 0.12%; (2) Donor mortality: 0%; and (3) Comparison by approach: Grade IIIb: Open 1.08% vs MIS 1.57% (P = 0.09), grade IV: Open 0.14% vs MIS 0% (P = 0.12), no significant difference in severe complication rates. Bleeding-related complications: (1) Postoperative bleeding: More frequent in MIS cases (P < 0.01); and (2) Bleeding source differed by approach: IVC bleeding: Higher in MIS (P = 0.05); abdominal wall bleeding: Higher in MIS (P < 0.01)

NCMV: No circumferential margin involvement; CMV: Circumferential margin involvement; HPB: Hepato-pancreato-biliary; PSM: Positive surgical margin; IWATE: Iwate difficulty scoring system; MAMBA: Moisture Assisted Multiple BipolAr; MIS: Minimally invasive surgery; IVC: Inferior vena cava.

Current approaches, limitations and future perspectives

Although surgical research on robotic hepatectomies for transplantation is expanding and gaining significant ground in modern liver transplantation access[41], however, some surgical limitations should be considered with special consideration. Despite the advantages offered by robotic surgical liver accesses[42-44] the disadvantages of robotic systems need to be further explored, as it seems that from a purely surgical point of view, they do not provide feedback on tissue tension[45].

Modern minimally invasive surgeons are challenged to cope with robotic liver transplantation surgeries of extremely high technical complexity especially with regard to complex vascular and anatomical connections[45,46]. It is clear that such major surgeries require precise maneuvers, advanced surgical skills, clear surgical expertise exclusively in the field of robotic surgery[47,48]. In addition, robotic surgery and in particular liver transplantation surgery is quite costly, especially in the modern era where navigation systems and AI make robotic liver surgery very innovative but economically inaccessible for certain groups of liver transplant recipients[49]. The current efforts of the transplant surgery community should be directed towards the creation of standardised guidelines and protocols for minimally invasive transplant surgery[50] and the establishment of centres of excellence and national and international transplantation centres that provide significant training in this innovative surgical field[50-52].

The global trend in robotic surgery mandates the integration of telemedicine and AI. The future of hepato-pancreato-biliary surgery will require surgeons to master open, minimally invasive, and AI-assisted techniques through clearly defined procedures and structured training pathways[53]. The integration of AI into robotic liver transplant surgery platforms and practical robotic training of surgeons will ensure improved and safer access[2,9-13,53]. The recruitment of AI in robotic transplant surgery can contribute to liver graft preservation as well as optimize transplant conditions[53-56]. Understanding the function of AI in robotic surgery could be instrumental in better and more specialized training of surgical teams and introducing the relationship of cost-effectiveness and cost reduction concepts in surgery[44,45]. Furthermore, the use of AI combined with self-adaptive learning models will provide surgeons with advanced intraoperative metrics linked to donor outcomes[29,34] and allowing the automation of specific surgical tasks, including the introduction of a safety mechanism to avoid intraoperative survival complications[37,38] as well as alleviating the technical difficulties of liver transplant surgery[43-45]. Finally, in addition to the technical benefits, it is also important to consider the prospects for using AI in the quality assessment of liver transplants, as well as in the formal and direct assessment of organ quality to assist transplant surgeons in organ procurement[34,42].

The integration of AI into robotic liver transplantation holds great promise for enhancing surgical precision and decision-making. AI-based image analysis can provide real-time feedback on critical aspects of the procedure, such as graft placement and vascular anastomosis, thereby reducing the likelihood of human error. In addition, machine learning algorithms are being developed to predict the likelihood of intraoperative complications, allowing surgeons to make timely adjustments during surgery[53,54]. Robotic systems with AI offer improved motion scaling and tremor suppression, thereby enhancing the accuracy of fine suture techniques[55]. Additionally, robotically assisted vascular suturing, supported by AI, has shown promising results in reducing anastomotic procedure times without compromising patency rates. The application of augmented reality combined with AI allows for enhanced visualization of liver anatomy and assessment of blood flow dynamics in real time, optimizing graft perfusion and reducing the risk of ischemic injury[54-56]. As robotic liver transplantation continues to develop in practice, it is essential to implement specialized training programs to equip surgeons with the necessary skills[54,57]. AI-based surgical simulators are being developed to reproduce immersive, hands-on training experiences for robotic liver transplantation procedures[55-57]. Optimal outcomes, characterized by low rates of open conversion, major complications, and R1 resections, are primarily determined by meticulous patient selection rather than institutional volume[23,58]. These benchmarks serve as a formal framework for training and support the safe and effective implementation of robotic liver surgery[58].

Frequent and regular access to robotic platforms accelerates the learning curve in robotic liver resection, allowing surgeons to achieve proficiency in conversion rates and blood loss with fewer cases. Early competency is facilitated by high case volume, while structured training and equitable access are critical to minimizing postoperative complications and ensuring safe adoption of robotic liver resections[57,58] (Figure 1).

Figure 1 Advancements, challenges, limitations, artificial intelligence-driven surgical training and future perspectives in robotic liver transplantation surgery. Created in BioRender. AI: Artificial intelligence.

DISCUSSION

According to all the studies above, the robotic approach shows significant advantages with lower percentage of complications. Reduced overall morbidity, shorter intensive care unit stay and fewer patients with bilirubin leakage may be due to the more precise and more atraumatic movements, that robotic liver surgery provides. Furthermore, this technique attempts to improve liver function earlier after transplantation surgery, thus with lower hepatic enzymes values, as proved by many included studies. Recent developments in AI and telemedicine are beginning to transform the field of robotic liver transplantation from theoretical potential to practical application. AI-based computer vision algorithms are being trialed to provide real-time intraoperative guidance, including vascular mapping, tissue differentiation, and perfusion assessment, which can optimize graft handling and improve surgical precision. Beyond imaging, machine-learning models are also being explored to predict intraoperative complications and provide decision support tailored to donor and recipient characteristics. Telemedicine platforms complement these advances by enabling remote mentoring and proctoring, allowing experienced surgeons to guide complex procedures from a distance, review real-time performance metrics, and provide targeted feedback to trainees. By integrating AI and telemedicine, these innovations not only enhance surgical outcomes and graft preservation but also help standardize training, accelerate the learning curve, and expand access to expertise in transplant centers worldwide, illustrating a concrete shift from conceptual discussion to actionable advancements in the field.

Despite the multiple advantages offered by robotic systems, such as improved ergonomics, better intraoperative management and reduced surgeon fatigue, several limitations and concomitant challenges seem to be identified. Robotic systems are prohibitively expensive, and this is a primary barrier to their universal implementation. Besides, the limited number of centers that can perform robotic liver transplantation limits access to this technique. The increased learning time and the need for professional training are additional difficulties that need to be addressed in the near future.

The extensive experience in open hepatectomies significantly enhances the learning curve and outcomes for surgeons transitioning to robotic liver transplantation. This vast experience is dictated by his deep knowledge of liver segment anatomy, vascular structures and anatomical variations- a prerequisite for safe and accurate robotic dissection. Intraoperative confidence in handling complex liver dissections, mobilization of the caudal lobe and exposure of the retrohepatic inferior vena cava translates directly into robotic proficiency. Importantly, in tactical decision making and crisis and safety situations, they will be better able to predict bleeding, plan resection levels and meet intraoperative challenges during robotic liver procedures. Structured training pathways are essential for the safe adoption of robotic liver transplantation. Modern AI-enhanced simulators enable objective assessment of surgical performance through metrics such as instrument path length, economy of motion, precision, error rate, and task completion time. These platforms can also compare trainee performance with expert benchmarks and provide targeted feedback, supporting competency-based training and helping standardize the learning curve in complex hepatobiliary and transplant procedures.

A limitation of this review is the limited availability of data on the training of liver transplant surgeons, the technical challenges they face, and the learning curve associated with robotic liver transplantation. Nevertheless, our review represents the most recent and comprehensive synthesis of the literature in this area, uniquely integrating aspects of robotic liver transplantation with AI and telemedicine. Nevertheless, further research is warranted - particularly focusing on current limitations - to address critical questions such as the length of training time required for a surgeon to become proficient in robotic-assisted liver transplantation and strategies to minimize intraoperative errors. Through such targeted research can we achieve a more accurate and thorough understanding of the potential benefits of robotic surgery in the context of liver transplantation.

CONCLUSION

Robotic liver transplantation marks a major evolution in hepatobiliary surgery, offering superior imaging, refined dexterity and improved intraoperative control compared to conventional laparoscopic and open approaches. Improving the learning curve for robotic liver transplant surgeons is a complex but achievable goal involving a combination of structured surgical training and simulation, mentoring, technology integration and institutional support. For transplant surgeons, the integration of robotic platforms not only facilitates safer and more accurate donor and recipient procedures, but also minimizes perioperative morbidity. Since AI is increasingly integrated into surgical systems, it will provide structured, data-driven feedback, optimize training protocols and enable real-time intraoperative support. The convergence of robotics and AI is poised to elevate the technical standards and outcomes of liver transplantation, enhancing a surgical future based on precision, safety and continuous improvement in operational performance.