Download PDF
Review  |  Open Access  |  14 Apr 2023

Robotic vs. laparoscopic resection for hepatocellular carcinoma

Views: 607 |  Downloads: 597 |  Cited:  0
Mini-invasive Surg 2023;7:13.
10.20517/2574-1225.2022.112 |  © The Author(s) 2023.
Author Information
Article Notes
Cite This Article


Minimally invasive liver surgery (MILS) has become increasingly popular over the last two decades, with hepatocellular carcinoma (HCC) representing a common indication. While data has shown the benefits of a laparoscopic vs. an open approach, robotic liver surgery is rapidly emerging. In this context, among the two minimal access approaches [robotic (RLR) vs. laparoscopic liver resection (LLR)], a differential benefit is still under investigation. While the advantages of RLR include increased dexterity, reduction of physiological tremors, and wrist articulation, it currently has no haptic feedback or specialized liver parenchymal transection devices and is associated with increased operative time and cost. However, RLR has proved to be a safe and effective approach for select patients with HCC. Some benefits of RLR include similar oncological outcomes to open or laparoscopic surgery, possibly reduced conversion rates, and an easier transition from open surgery to a minimally invasive approach. Moreover, while already today RLR can facilitate resection for HCC in hard-to-reach anatomic locations (e.g., transthoracic approach to posterior-superior liver), the future of robotics with the development of advanced image processing technologies, haptic feedback, liver-specific devices, lower cost, and more robot choices seems even more promising.


Hepatocellular carcinoma, minimally invasive liver surgery, robotic surgery, robotic liver surgery, robotic liver resection


Liver resection (LR) can be performed through an open (OLR), laparoscopic (LLR), or robotic approach (RLR). Advantages of minimally invasive liver surgery (MILS) include reduction of perioperative blood loss, postoperative pain, morbidity, and hospital stay[1,2]. In this context, hepatocellular carcinoma (HCC) is currently one of the most common indications for MILS, ranging from 26% to 40% of all the indications in large MILS series[1,3,4]. For patients with HCC, literature has suggested that LLR can be superior to OLR[2,5]. in selected circumstances, leading to advantageous short-term results in both cirrhotic and non-cirrhotic patients[6-8]. The benefits specific to robotic surgery help to overcome several limitations associated with a laparoscopic approach. The recognized benefits of using robotics include consistent three-dimensional (3D) visualization (which is also an option for LLR), increased dexterity and wrist articulation (facilitating suturing and vessel dissection), reduction of physiological tremors, increased accessibility to challenging parts of the liver such as the caudate lobe and right posterior liver segments, and a reduced learning curve[9-11]. Comparative clinical outcomes are still under study. Between 2010 to 2016, the use of RLR increased by fivefold in the U.S. and it is associated with a shorter hospital length of stay compared to the open approach without compromising perioperative outcomes or survival[12]. Additionally, it has been noted that oncologic outcomes have been comparable between LLR and RLR[10,13].

In this paper, we discuss RLR for patients with HCC by focusing on its benefits and drawbacks compared to a traditional laparoscopic approach.


To find pertinent articles, three of the authors (E.P, A.M.C., and B.H) reviewed the literature and agreed to select the most relevant papers. In particular, the following keywords were used to conduct the research on PubMed, Google Scholar, and Scopus: “hepatocellular carcinoma” or “HCC” in association with “robotic hepatectomy”, “robotic liver resection”, or “robotic liver surgery”.



The surgical indications for LR using a laparoscopic or robotic approach tend to overlap significantly[14]. A crucial indication to sway towards RLR instead of LLR would be in cases of tumors residing in the posterior and/or superior segments or in cases where a transthoracic approach is planned. The increased degrees of freedom associated with robotic surgery may allow for a more effective resection in these patient populations[15-17].

Patient selection based on liver function

Patient selection for HCC resection can be initially classified into two major categories depending on liver functional status: cirrhotic vs. non-cirrhotic. The former comes with increased operative mortality and rate of recurrence and a decreased hepatic regenerative capacity. This creates a difficult clinical balance between resecting enough parenchyma to ensure good surgical margins and minimizing the risk of local recurrence but also conserving functional tissue to prevent postoperative liver failure[11]. Patients with known liver disease can be stratified further by examining liver function, notably by using the Child-Pugh Score. Traditionally, only patients with Child-Pugh A class are considered surgical candidates due to poor liver function and post-surgical prognosis of Child-Pugh B and C patients. Nevertheless, LLR proved to be beneficial in select patients with HCC over Child-Pugh B cirrhosis[18,19]. Additionally, a high Model for End-Stage Liver Disease (MELD) score and the presence of cirrhosis have an independent negative effect on mortality after liver resection, and the MELD score is associated with postoperative morbidity among patients selected for hepatectomy[20]. In this setting, the fact that MILS is associated with a lower risk of postoperative ascites should be considered[21]. This may be due to the reduced disruption of parietal collateral blood flow associated with MILS.

Preoperative preparation

Today, advanced liver surgery planning can be achieved by using preoperative three-dimensional (3D) liver modeling to perform a virtual hepatectomy. 3D reconstruction utilizes specialized software with stereoscopic data that aids surgeons in identifying correct anatomical relationships and assessing the future remnant liver volume before going to the operating room. This is especially useful in MILS , as it enables modeling of the spatial relationship of anatomic structures, assessing for variant anatomy, and ensuring that surgery can proceed as safely as possible[17]. Additionally, the simulation of the port sites to align the eye-port-instrument-target-monitor axis will optimize ergonomics for the surgical team.

A recent systematic review by Jiang et al.[22] examined 16 studies that elucidated the differences between the usage of 3D vascular reconstruction and navigation technologies vs. a surgical approach without 3D modeling for primary hepatic carcinomas. Their study revealed statistically significant improved operation time and intraoperative blood loss in the group that had modeling.

Patient positioning and robotic set-up

When performing an RLR, patients are positioned supine, in the reverse Trendelenburg position at an angle of 20-35 degrees, and can be slightly tilted to the left, if needed[23,24]. Four to five trocars are used based on the procedure performed, with one serving as a camera port. Two to three ports are occupied by robotic arms, while the remaining ones are used for surgical assistance. The surgical trocars are placed according to the liver segment to be resected in the upper right and left quadrants[25-27]. The da Vinci® robotic surgical system patient cart is located at the patient’s head, allowing for the robotic arms to be docked at the surgical site[23,27]. The surgeon sits at the surgeon console for the duration of the surgery, which has been reported to reduce physician fatigue. Further, the surgeon views the operative field in high-definition 3D images of the surgical site. The controls on the console have EndoWrist technology that provides seven degrees of motion. Both features can enhance precision and hand-eye coordination[28].

Intraoperative navigation

Utilizing the robot allows for the use of near-infrared fluorescence imaging with the fluorophore indocyanine green (ICG), which can help identify lymphatic structures, assess perfusion of parenchyma, and distinguish between healthy liver tissue vs. tumor tissue[17]. With this technology, surgeons can discern between the biliary tract and vasculature with greater detail, allowing for more precise dissection planes and resection margins while also minimizing the risk of intraoperative complications and remnant liver ischemia[29,30]. A panel of 13 experts in the Asia-Pacific region recommends fluorescence cholangiography to help identify extrahepatic biliary anatomy and recognize subcapsular tumors within 8 mm of the liver surface. This tool can also facilitate delineating segmental boundaries for MILS, while the concurrent use of IOUS is required in positive staining (Class IIb recommendation; Level II-2 evidence)[31].

For resection of deep HCC, the guidance of fluorescence imaging may reduce the risk of positive margins (Class IIa recommendation; Level II-3 evidence).

Augmented reality techniques can help not only in preoperative planning but also as intraoperative navigation tools. Today no robotic platform allows for augmented reality integration into the imaging platform. Volonté et al.[32] reported their experience with the OsiriX (Pixmeo, Geneva, Switzerland), an image processing software package dedicated to DICOM® images. In particular, OsiriX was helpful in allowing exact identification of the nodule position, helping in port placement and visual triangulation with laparoscopic instruments by projecting image overlays on the patient’s abdomen. This allowed for an optimal docking of the robot, which is crucial. Also, it enabled the fusion of 3D reconstructed images and stereoscopic vision for RLR. Similarly, Bijlstra et al.[33] developed and validated the 3DeliverS Software. The software creates virtual reality 3D models based on imaging segmentation, which are integrated into a multimodal image-guided robotic liver surgery cockpit, guiding LR with an accuracy of 93%.

Our group utilizes the Synapse Vincent software (Fujifilm, Tokyo, Japan) for preoperative computed tomography (CT) based reconstruction[34]. It is our policy to always obtain a 3D reconstruction before MILS. In particular, we demonstrated how simulation is pivotal in the identification of hepatic veins tributaries and anatomic relationships between portal pedicles when performing major hepatectomies[35,36].

Learning curve 

Regarding the learning curve for RLR, the standard practice involves preoperative mastery with simulation exercises to familiarize oneself with the robotic technology. It has been noted that 45 major hepatectomies, followed by 30 cases, are required to overcome the learning curve and have mastery of complex liver resections when performed laparoscopically[37]. When comparing the learning curve of a robot-assisted vs. laparoscopic surgery, there has been a reduced learning curve to mastery reported for RLR. Further, it was identified that 8-10 intermediate- and lower-level resections are required to be performed before difficult resections[26]. Nevertheless, a more recent report warrants caution, indicating an initial learning phase of 117 cases for LLR and 93 procedures for RLR, respectively[38]. An increase in blood transfusion, conversion, and operative time was noted during the learning phase, reaching a steady state subsequently after complexity-adjusted analysis.


One of the first case series reporting short-term outcomes after RLR for HCC[23] described the outcomes of 41 consecutive patients with HCC undergoing 42 resections, with 23.8% being major LR. The mean operating time and blood loss were 229.4 min and 412.6 mL, respectively. The R0 resection rate was 93%, and postoperative mortality and morbidity rates were 0% and 7.1%, respectively. The mean hospital stay was 6.2 days. The 2-year overall (OS) and disease-free survival (DFS) rates were 94% and 74%, respectively. The authors performed a subgroup analysis of minor (< 3 Couinaud segments) RLR vs. conventional minor LLR. They showed how the robotic group had similar blood loss (mean, 373.4 mL vs. 347.7 mL), morbidity (3% vs. 9%), mortality (0% vs. 0%), and R0 resection rate (90.9% vs. 90.9%). However, the robotic group had a significantly longer operative time (202.7 min vs. 133.4 min).

Further reports[13,39-50] confirmed similar outcomes in terms of operative time, surgical radicality, perioperative mortality and morbidity, and postoperative length of stay. More variability was noted in terms of major resection and conversion to laparotomy rates, and blood loss. However, all these early case series were small (the number of cases described ranged from 10 to 140) with different rates of cirrhotic patients (from 26.2% to 97.5%), as shown in Table 1.

Table 1

A summary of papers describing outcomes after robotic liver resection for hepatocellular carcinoma

AuthorNumber of resectionsChild-Pugh A (%)Cirrhosis (%)Major resections (%)Operative time (min)Blood loss (mL)Conversion to open approach (%)R0 (%)Mortality (%)Morbidity (%)Hospital stay (days)
Lai et al.[23]42NA82.923229.4 (m)412.6 (M)4.89307.16.2 (m)
Di Sandro et al.[39]10100NA0236 (M)220 (M)0100006.8 (M)
Lai and Tang[40]100NA8027207.4 (m)334.6 (m)4960147.3 (m)
Magistri et al.[13]2290.968.29.1318 (m)400 (m)095.5068.25.1 (m)
Chen et al.[41]81NA26.241.9343 (M)282 (M)1.610004.97.5 (M)
Wang et al.[42]6393.9NA4.8296 (m)206 (m)093.7011.16.2 (m)
Khan et al.[43]34NA31.432.3246 (M)125 (M)8.894035.24 (M)
Zhu et al.[44]140NA48.612.6NANA19100030.4NA
Lim et al.[45]4490.961.411.4252 (m)NA4.5NA036.49 (m)
Balzano et al.[46]40NA97.50217.5 (M)NA7.5900256 (M)
Zhang et al.[47]a11384.13137.2205 (M)150 (M)2.71001.88.86 (M)
Zhu et al.[48]5689.3NA10.7220 (M)200 (M)14.398.2012.56 (M)
Duong et al.[50]b123NANANANANA8.1NA0.8NA3 (M)

Several authors have compared the outcomes of RLR for HCC to those after OLR. After propensity scored matching, Chen et al.[41] demonstrated in comparable groups [major liver resections (41.9 vs. 39.5 %) and liver cirrhosis (45.7 vs.46.9 %)] that while the robotic group required longer operation times (343 vs. 220 min), RLR led to shorter hospital stays (7.5 vs. 10.1 days) and improved postoperative pain. The 3-year DFS and OS of the robotic group were comparable with that of the open group (72.2% vs. 58.0%; P = 0.062 and 92.6% vs. 93.7%; P = 0.431).

Importantly, all the studies comparing RLR to OLR reported similar oncological outcomes in terms of survival and negative margin rates while confirming the longer operative time and shorter length of stay after RLR[42,43,47,49].

Zhu et al.[48] prospectively collected data on 369 patients with BCLC stage 0-A HCC who underwent curative liver resection for HCC using OLR, LLR, or RLR and analyzed outcomes after propensity score matching. In both LLR and RLR, the operative time and duration of Pringle’s maneuver were significantly longer than those in the OLR group, while the length of stay was shorter. No significant differences in the 5-year DFS (63.8%, 54.4%, and 50.6%) or OS rates (80.8%, 78.6%, and 75.7%, respectively) were appreciated among the three groups.


A case-matched analysis by Di Sandro et al.[39] showed reduced blood loss (P = 0.03) and increased operative time (P = 0.04) among ten patients who underwent RLR for HCC vs. LLR, while short and long-term results were similar in the two groups.

Interesting results were published by Lai et al.[40], who noted a higher proportion of major hepatectomies (27% vs. 2.9%; P = 0.002) and tumors located in posterosuperior segments (29% vs. 0%; P < 0.001) in the RLR vs. LLR group. The robotic approach was associated with a significantly longer mean operative time (207.4 vs. 134.2 min;P = 0.001). Both groups had similar blood loss (334.6 vs. 336 mL; P = 0.99), morbidity (14% vs. 20%;P = 0.42), and mortality rates (0% vs. 0%). There was no difference in terms of R0 resection rate (96% vs. 91.4%;P = 0.72), 5-year OS (65% vs. 48%; P = 0.28), and DFS (42% vs.38%; P = 0.65). The main limitation of this study was the number of patients analyzed (100 RLRs vs. 35 LLRs).

Another retrospective study on HCC resection performed robotically and laparoscopically[13] demonstrated that there was an increase in Clavien-Dindo I-II level complications and pleural effusion among patients undergoing LLR (P = 0.03, P = 0.01, respectively). The open conversion rate was higher among LLR patients (P = 0.046), yet operative time was higher among RLR patients (P < 0.01). There was no difference in length of stay (P = 0.15).

Later it was reported[45] that there was a lower rate of R1 status and anatomical resection rate for patients who underwent RLR in comparison to LLR after propensity score matching (3% vs.15%, P = 0.09; 36% vs. 61%, P = 0.049). While there was an increase in 3-year OS and a decrease in recurrence among patients who underwent RHR for HCC, the results were not statistically significant (P = 0.27, P = 0.26, respectively).

A retrospective comparative analysis by Balzano et al.[46] showed a higher use of Pringle’s maneuver (32.7% vs. 20%;P = 0.23) and a shorter duration of surgery (median of 165.5 vs. 217.5 min; P = 0.04) in LLR vs. RLR. Incidence of complications (25% vs.32.7%; P = 0.49), blood transfusions (2.5% vs.9.6%; P = 0.21), and median length of stay (6 vs. 5; P = 0.54) were similar between RLR and LLR. One and 5-year OS and DFS were 100% and 79%, and 95% and 26% for RLR vs. 96.2% and 76.9%, and 84.6% and 26.9% for LLR (P = 0.65 for OS and 0.72 for DFS).

Finally, a matched analysis from the National Cancer Database found an improved OS after RLR vs. LLR (HR: 0.64 and 95%CI: 0.43%-0.96% for intent-to-treat; HR: 0.59 and 95%CI: 0.39%-0.90% for end-treatment). In this series, RLR had a significantly higher conversion rate and median hospital stay than LLR. Nevertheless, no data were available on underlying liver disease or type of surgery; thus, it was not included in the propensity score matching[50].

Table 2 summarizes the studies comparing RLR and LLR for HCC. To try to assess if there is an actual advantage in RHR over LRR, Murtha-Lemekhova et al.[51] performed a review of the literature and meta-analysis, comparing a total of 324 RLRs and 613 LRRs. The rate of major liver resections was higher in the RLR group (P = 0.006), and no differences were noted in terms of operative (P = 0.49) and Pringle (P = 0.11) time and length of stay (P = 0.77). While there was no difference in the overall rate of postoperative complications (P = 0.28), Clavien-Dindo III-IV level complications were more frequent after LLR (P = 0.05). The odds of developing postoperative liver failure (P = 0.24), ascites (P = 0.35), bile leak (P = 0.78), hemorrhages (P = 0.66), and infections (P = 0.84) were similar in both groups. R0 was more frequently achieved with RLR (P = 0.041), but recurrence rates (P = 0.12) and OS (P = 0.769) were comparable. The authors summarized how RLR is non-superior to LLR, with no proven advantage in cirrhotic patients.

Table 2

A summary of papers comparing outcomes after robotic and laparoscopic liver resection for hepatocellular carcinoma. The table shows whether outcomes were statistically significantly higher, lower, or equal when the robotic approach was compared to the laparoscopic one, considering several parameters

AuthorChild-Pugh ACirrhosisMajor resectionsOperative timeBlood lossConversion to an open approachR0MortalityMorbidityHospital stayRFSOS
Lai et al.[23]aNANANA=NA===NANANA
Di Sandro et al.[39]=NA=NA====NANA
Lai et al.[40]NA=========
Magistri et al.[13]======NANA
Lim et al.[45]===========
Balzano et al.[46]NA==========
Zhu et al.[48]=NA===NA======
Duong et al.[50]bNANANANANANA=NANA


When comparing RLR to other surgical approaches, the main limitation is the lack of randomized clinical trials, a small number of patients analyzed in the available studies, heterogeneity of reported results, and inconsistent use of propensity score matching. Secondarily, none of the reviewed papers mentioned outcomes such as functional activity, pain levels, quality of life, costs, and financial burden. Nevertheless, it must be noted how limited data regarding cost is controversial. While a study on RLR (not specifically focused on HCC) reported an overall economic advantage[52] and no differences in terms of total surgical supply[53], a later report found higher costs with RLR[54].

Today, some of the remaining challenges with robotics are as follows:

(1) Specialized robotic training is required for surgeons and the assisting healthcare team to perform a RLR properly and safely. While simulation and virtual reality training have been proven to prepare surgeons with robotic skills, there is limited standardization in training within surgical residency programs[27,55];

(2) Devices specific to parenchymal transection of the liver are limited, and sophisticated suction devices that the operators can control by themselves are lacking[27,56];

(3) RLR frequently requires increased intraoperative time, as demonstrated, which may contribute to increased hospital costs[54].


In this review, the role of robotic surgery for HCC is detailed. The evidence consistently demonstrates overall comparable short- and long-term results to LLR. Achieving R0 resection in hard-to-reach anatomic locations, increased intraoperative maneuverability, and the ability to utilize surgical-enhancing technologies - like 3D reconstruction and ICG - to achieve safe and effective resection are important driving factors in the adoption of robotic techniques in HCC surgery. Moreover, the current innovations under development will lead to a wider diffusion of RLR, the development of advanced image processing technologies, haptic feedback, liver-specific devices, lower cost, and more robot choices. These innovations cumulatively will lead to safer RLR for our patients.


Authors’ contributions

Made substantial contributions to the conception and design of the study: Panettieri E

Made significant contributions to the writing of the manuscript: Chirban A, Hansen B

Contributed to the production of the final draft and gave administrative, technical, and material support: Vega EA, Conrad C

Availability of data and materials

Not applicable.

Financial support and sponsorship


Conflicts of interest

All authors declared that there are no conflicts of interest.

Ethical approval and consent to participate

Not applicable.

Consent for publication

Not applicable.


© The Author(s) 2023.


1. Ciria R, Cherqui D, Geller DA, Briceno J, Wakabayashi G. Comparative short-term benefits of laparoscopic liver resection: 9000 cases and climbing. Ann Surg 2016;263:761-77.

2. Abu Hilal M, Aldrighetti L, Dagher I, et al. The Southampton consensus guidelines for laparoscopic liver surgery: from indication to implementation. Ann Surg 2018;268:11-8.

3. Nguyen KT, Gamblin TC, Geller DA. World review of laparoscopic liver resection-2,804 patients. Ann Surg 2009;250:831-41.

4. Xiong JJ, Altaf K, Javed MA, et al. Meta-analysis of laparoscopic vs open liver resection for hepatocellular carcinoma. World J Gastroenterol 2012;18:6657-68.

5. Sposito C, Battiston C, Facciorusso A, et al. Propensity score analysis of outcomes following laparoscopic or open liver resection for hepatocellular carcinoma. Br J Surg 2016;103:871-80.

6. Shehta A, Han HS, Yoon YS, Cho JY, Choi Y. Laparoscopic liver resection for hepatocellular carcinoma in cirrhotic patients: 10-year single-center experience. Surg Endosc 2016;30:638-48.

7. Yoon YI, Kim KH, Kang SH, et al. Pure laparoscopic versus open right hepatectomy for hepatocellular carcinoma in patients with cirrhosis: a propensity score matched analysis. Ann Surg 2017;265:856-63.

8. Tsilimigras DI, Bagante F, Sahara K, et al. Prognosis after resection of barcelona clinic liver cancer (BCLC) stage 0, A, and B hepatocellular carcinoma: a comprehensive assessment of the current BCLC classification. Ann Surg Oncol 2019;26:3693-700.

9. Labadie KP, Park JO, Sham JG. Robotic-assisted laparoscopic liver resection in hepatocellular carcinoma. Hepatoma Res 2020;6:65.

10. Magistri P, Tarantino G, Assirati G, et al. Robotic liver resection for hepatocellular carcinoma: a systematic review. Int J Med Robot 2019;15:e2004.

11. Lai ECH, Chung DTM, Chan OCY, Tang CN. Robotic hepatectomy for hepatocellular carcinoma: a clinical review. Hepatoma Res 2017;3:278-83.

12. Kamel MK, Tuma F, Keane CA, Blebea J. National trends and perioperative outcomes of robotic-assisted hepatectomy in the USA: a propensity-score matched analysis from the national cancer database. World J Surg 2022;46:189-96.

13. Magistri P, Tarantino G, Guidetti C, et al. Laparoscopic versus robotic surgery for hepatocellular carcinoma: the first 46 consecutive cases. J Surg Res 2017;217:92-9.

14. Ayabe RI, Azimuddin A, Tran Cao HS. Robot-assisted liver resection: the real benefit so far. Langenbecks Arch Surg 2022;407:1779-87.

15. Salloum C, Lim C, Malek A, Compagnon P, Azoulay D. Robot-assisted laparoscopic liver resection: a review. J Visc Surg 2016;153:447-56.

16. Benedetto F, Tarantino G, Magistri P. Chasing the right path: tips, tricks and challenges of robotic approach to posterior segments. Hepatobiliary Surg Nutr 2019;8:512-4.

17. Wang Y, Cao D, Chen SL, Li YM, Zheng YW, Ohkohchi N. Current trends in three-dimensional visualization and real-time navigation as well as robot-assisted technologies in hepatobiliary surgery. World J Gastrointest Surg 2021;13:904-22.

18. Berardi G, Morise Z, Sposito C, et al. Development of a nomogram to predict outcome after liver resection for hepatocellular carcinoma in Child-Pugh B cirrhosis. J Hepatol 2020;72:75-84.

19. Troisi RI, Berardi G, Morise Z, et al. Laparoscopic and open liver resection for hepatocellular carcinoma with Child-Pugh B cirrhosis: multicentre propensity score-matched study. Br J Surg 2021;108:196-204.

20. Zaydfudim VM, Turrentine FE, Smolkin ME, Bauer TB, Adams RB, McMurry TL. The impact of cirrhosis and MELD score on postoperative morbidity and mortality among patients selected for liver resection. Am J Surg 2020;220:682-6.

21. Levi Sandri GB, de Werra E, Mascianà G, et al. Laparoscopic and robotic approach for hepatocellular carcinoma-state of the art. Hepatobiliary Surg Nutr 2016;5:478-84.

22. Jiang J, Pei L, Jiang R. Clinical efficacy and safety of 3D vascular reconstruction combined with 3D navigation in laparoscopic hepatectomy: systematic review and meta-analysis. J Gastrointest Oncol 2022;13:1215-23.

23. Lai EC, Yang GP, Tang CN. Robot-assisted laparoscopic liver resection for hepatocellular carcinoma: short-term outcome. Am J Surg 2013;205:697-702.

24. Benedetto F, Petrowsky H, Magistri P, Halazun KJ. Robotic liver resection: hurdles and beyond. Int J Surg 2020;82S:155-62.

25. Nota CL, Rinkes IHB, Hagendoorn J. Setting up a robotic hepatectomy program: a Western-European experience and perspective. Hepatobiliary Surg Nutr 2017;6:239-45.

26. Efanov M, Alikhanov R, Tsvirkun V, et al. Comparative analysis of learning curve in complex robot-assisted and laparoscopic liver resection. HPB 2017;19:818-24.

27. Giulianotti PC, Bianco FM, Daskalaki D, Gonzalez-Ciccarelli LF, Kim J, Benedetti E. Robotic liver surgery: technical aspects and review of the literature. Hepatobiliary Surg Nutr 2016;5:311-21.

28. Spiegelberg J, Iken T, Diener MK, Fichtner-Feigl S. Robotic-assisted surgery for primary hepatobiliary tumors-possibilities and limitations. Cancers 2022;14:265.

29. Cho JY, Han HS, Choi Y, et al. Association of remnant liver ischemia with early recurrence and poor survival after liver resection in patients with hepatocellular carcinoma. JAMA Surg 2017;152:386-92.

30. Yamashita S, Venkatesan AM, Mizuno T, et al. Remnant liver ischemia as a prognostic factor for cancer-specific survival after resection of colorectal liver metastases. JAMA Surg 2017;152:e172986.

31. Wang X, Teh CSC, Ishizawa T, et al. Consensus guidelines for the use of fluorescence imaging in hepatobiliary surgery. Ann Surg 2021;274:97-106.

32. Volonté F, Pugin F, Bucher P, Sugimoto M, Ratib O, Morel P. Augmented reality and image overlay navigation with OsiriX in laparoscopic and robotic surgery: not only a matter of fashion. J Hepatobiliary Pancreat Sci 2011;18:506-9.

33. Bijlstra OD, Broersen A, Oosterveer TTM, et al. Integration of three-dimensional liver models in a multimodal image-guided robotic liver surgery cockpit. Life 2022;12:667.

34. Ohshima S. Volume analyzer synapse Vincent for liver analysis. J Hepatobiliary Pancreat Sci 2014;21:235-8.

35. Ogiso S, Okuno M, Shindoh J, et al. Conceptual framework of middle hepatic vein anatomy as a roadmap for safe right hepatectomy. HPB 2019;21:43-50.

36. Joechle K, Vega EA, Okuno M, et al. Middle hepatic vein roadmap for a safe laparoscopic right hepatectomy. Ann Surg Oncol 2019;26:296.

37. Hamad A, Tsung A, Ejaz A. Learning curve and pitfalls in establishing a new robotic liver surgery program. Laparosc Surg 2019;3:41-41.

38. Krenzien F, Benzing C, Feldbrügge L, et al. Complexity-adjusted learning curves for robotic and laparoscopic liver resection: a word of caution. Ann Surg Open 2022;3:e131.

39. Di Sandro S, Lauterio A, Giacomoni A, et al. Totally robotic liver resection for hepatocellular carcinoma in cirrhotic patients: safety and feasibility. J Robotic Surg 2014;8:357-64.

40. Lai EC, Tang CN. Long-term survival analysis of robotic versus conventional laparoscopic hepatectomy for hepatocellular carcinoma: a comparative study. Surg Laparosc Endosc Percutan Tech 2016;26:162-6.

41. Chen PD, Wu CY, Hu RH, et al. Robotic versus open hepatectomy for hepatocellular carcinoma: a matched comparison. Ann Surg Oncol 2017;24:1021-8.

42. Wang WH, Kuo KK, Wang SN, Lee KT. Oncological and surgical result of hepatoma after robot surgery. Surg Endosc 2018;32:3918-24.

43. Khan S, Beard RE, Kingham PT, et al. Long-term oncologic outcomes following robotic liver resections for primary hepatobiliary malignancies: a multicenter study. Ann Surg Oncol 2018;25:2652-60.

44. Zhu P, Liao W, Ding ZY, et al. Learning curve in robot-assisted laparoscopic liver resection. J Gastrointest Surg 2019;23:1778-87.

45. Lim C, Goumard C, Salloum C, et al. Outcomes after 3D laparoscopic and robotic liver resection for hepatocellular carcinoma: a multicenter comparative study. Surg Endosc 2021;35:3258-66.

46. Balzano E, Bernardi L, Tincani G, et al. Implementing a robotic liver resection program does not always require prior laparoscopic experience. Surg Endosc 2022;36:3317-22.

47. Zhang XP, Xu S, Hu MG, et al. Short- and long-term outcomes after robotic and open liver resection for elderly patients with hepatocellular carcinoma: a propensity score-matched study. Surg Endosc 2022;36:8132-43.

48. Zhu P, Liao W, Zhang WG, et al. A prospective study using propensity score matching to compare long-term survival outcomes after robotic-assisted, laparoscopic, or open liver resection for patients with BCLC stage 0-A hepatocellular carcinoma. Ann Surg 2023;277:e103-11.

49. Pesi B, Bencini L, Moraldi L, et al. Robotic versus open liver resection in hepatocarcinoma: surgical and oncological outcomes. Surg Laparosc Endosc Percutan Tech 2021;31:468-74.

50. Duong LM, Cai H, Shrubsole MJ, Bailey CE, Idrees K, Shu XO. Outcomes of robotic-assisted liver surgery versus laparoscopic liver surgery for treatment of stage I hepatocellular carcinoma. Cancer 2022;128:762-9.

51. Murtha-Lemekhova A, Fuchs J, Hoffmann K. Innovation for the sake of innovation? Cancers 2022;14:3359.

52. Mejia A, Cheng SS, Vivian E, Shah J, Oduor H, Archarya P. Minimally invasive liver resection in the era of robotics: analysis of 214 cases. Surg Endosc 2020;34:339-48.

53. Cortolillo N, Patel C, Parreco J, Kaza S, Castillo A. Nationwide outcomes and costs of laparoscopic and robotic vs. open hepatectomy. J Robot Surg 2019;13:557-65.

54. Miller HP, Hakim A, Kellish A, et al. Cost-benefit analysis of robotic vs. laparoscopic hepatectomy: a propensity-matched retrospective cohort study of American college of surgeons national surgical quality improvement program database. Am Surg 2022;88:2886-92.

55. Barriga M, Rojas A, Roggin KK, Talamonti MS, Hogg ME. Development of a two-week dedicated robotic surgery curriculum for general surgery residents. J Surg Educ 2022;79:861-6.

56. Choi GH, Chong JU, Han DH, Choi JS, Lee WJ. Robotic hepatectomy: the Korean experience and perspective. Hepatobiliary Surg Nutr 2017;6:230-8.

Cite This Article

Export citation file: BibTeX | EndNote | RIS

OAE Style

Panettieri E, Chirban AM, Hansen B, Vega EA, Conrad C. Robotic vs. laparoscopic resection for hepatocellular carcinoma. Mini-invasive Surg 2023;7:13.

AMA Style

Panettieri E, Chirban AM, Hansen B, Vega EA, Conrad C. Robotic vs. laparoscopic resection for hepatocellular carcinoma. Mini-invasive Surgery. 2023; 7: 13.

Chicago/Turabian Style

Elena Panettieri, Ariana M. Chirban, Bryar Hansen, Eduardo A. Vega, Claudius Conrad. 2023. "Robotic vs. laparoscopic resection for hepatocellular carcinoma" Mini-invasive Surgery. 7: 13.

ACS Style

Panettieri, E.; Chirban AM.; Hansen B.; Vega EA.; Conrad C. Robotic vs. laparoscopic resection for hepatocellular carcinoma. Mini-invasive. Surg. 2023, 7, 13.

About This Article

Special Issue

This article belongs to the Special Issue Current and Future Treatment of Hepatocellular Carcinoma
© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License (, which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Data & Comments




Comments must be written in English. Spam, offensive content, impersonation, and private information will not be permitted. If any comment is reported and identified as inappropriate content by OAE staff, the comment will be removed without notice. If you have any queries or need any help, please contact us at

Download PDF
Share This Article
Scan the QR code for reading!
See Updates
Mini-invasive Surgery
ISSN 2574-1225 (Online)
Follow Us


All published articles are preserved here permanently:


All published articles are preserved here permanently: