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. Author manuscript; available in PMC: 2025 Jan 1.
Published in final edited form as: Eur J Surg Oncol. 2023 Nov 8;50(1):107252. doi: 10.1016/j.ejso.2023.107252

Impact of liver cirrhosis, severity of cirrhosis and portal hypertension on the difficulty of laparoscopic and robotic minor liver resections for primary liver malignancies in the anterolateral segments

Junhao Zheng 1, Xiao Liang 1, Andrew G R Wu 2, Tousif Kabir 3, Olivier Scatton 4, Chetana Lim 4, Kiyoshi Hasegawa 5, Jasper P Sijberden 6, Davit L Aghayan 7, Tiing Foong Siow 8, Safi Dokmak 9, Paulo Herman 10, Marco V Marino 11, Vincenzo Mazzaferro 12, Adrian K H Chiow 13, Iswanto Sucandy 14, Arpad Ivanecz 15, Sung Hoon Choi 16, Jae Hoon Lee 17, Mikel Prieto 18, Marco Vivarelli 19, Felice Giuliante 20, Andrea Ruzzenente 21, Chee-Chien Yong 22, Mengqiu Yin 23, Zewei Chen 23, Constantino Fondevila 24, Mikhail Efanov 25, Zenichi Morise 26, Fabrizio Di Benedetto 27, Raffaele Brustia 28, Raffaele Dalla Valle 29, Ugo Boggi 30, David Geller 31, Andrea Belli 32, Riccardo Memeo 33, Salvatore Gruttadauria 34, Alejandro Mejia 35, James O Park 36, Fernando Rotellar 37, Gi-Hong Choi 38, Ricardo Robles-Campos 39, Xiaoying Wang 40, Robert P Sutcliffe 41, Johann Pratschke 42, Eric C H Lai 43, Charing C N Chong 44, Mathieu D’Hondt 45, Kazuteru Monden 46, Santiago Lopez-Ben 47, T Peter Kingham 48, Alessandro Ferrero 49, Giuseppe Maria Ettorre 50, Daniel Cherqui 51, Federica Cipriani 52, Olivier Soubrane 53, Wanguang Zhang 54, Go Wakabayashi 55, Roberto I Troisi 56, Tan-To Cheung 57, Yutaro Kato 58, Atsushi Sugioka 58, Tran Cong duy Long 59, Rong Liu 60, Bjørn Edwin 7, David Fuks 53, Mohammad Abu Hilal 6,61, Kuo-Hsin Chen 8, Luca Aldrighetti 52, Ho-Seong Han 62, Brian K P Goh 63,64; International robotic and laparoscopic liver resection study group investigators
PMCID: PMC11293421  NIHMSID: NIHMS2003762  PMID: 37984243

Abstract

Introduction:

We performed this study in order to investigate the impact of liver cirrhosis (LC) on the difficulty of minimally invasive liver resection (MILR), focusing on minor resections in anterolateral (AL) segments for primary liver malignancies.

Methods:

This was an international multicenter retrospective study of 3,675 patients who underwent MILR across 60 centers from 2004 to 2021.

Results:

1312 (35.7%) patients had no cirrhosis, 2118 (57.9%) had Child A cirrhosis and 245 (6.7%) had Child B cirrhosis. After propensity score matching (PSM), patients in Child A cirrhosis group had higher rates of open conversion (p = 0.024), blood loss >500 mls (p = 0.001), blood transfusion (p < 0.001), postoperative morbidity (p = 0.004), and in-hospital mortality (p = 0.041). After coarsened exact matching (CEM), Child A cirrhotic patients had higher open conversion rate (p = 0.05), greater median blood loss (p = 0.014) and increased postoperative morbidity (p = 0.001). Compared to Child A cirrhosis, Child B cirrhosis group had longer postoperative stay (p = 0.001) and greater major morbidity (p = 0.012) after PSM, and higher blood transfusion rates (p = 0.002), longer postoperative stay (p <0.001), and greater major morbidity (p = 0.006) after CEM. After PSM, patients with portal hypertension experienced higher rates of blood loss >500 mls (p = 0.003) and intraoperative blood transfusion (p = 0.025).

Conclusion:

The presence and severity of LC affect and compound the difficulty of MILR for minor resections in the AL segments. These factors should be considered for inclusion into future difficulty scoring systems for MILR.

Keywords: laparoscopic liver, laparoscopic hepatectomy, minimally-invasive liver, minimally-invasive hepatectomy, cirrhosis, difficulty score

Introduction

Minimally invasive liver resection (MILR) has been increasingly adopted worldwide due to its widely reported short-term benefits such as lower blood loss, reduced post-operative morbidity and shorter hospitalisation stay, with no compromise in oncologic outcomes compared to the traditional approach [1,2]. Despite its many purported advantages, it remains a technically challenging undertaking requiring expertise in both liver resection as well as minimally invasive surgery. As such, consensus guidelines emphasize the need for stepwise progression along the learning curve in order to ensure patient safety [3,4]. To this end, several Difficulty Scoring Systems (DSS) [5] have been developed to facilitate preoperative objective stratification of surgical complexity, so as to enable appropriate case selections for surgeons according to their expertise level, proper risk counselling of patients, as well as fair audit of surgical outcomes [5–9].

Primary liver malignancies often arise on a background of liver cirrhosis (LC), which compounds the difficulty of resection [10]. The cirrhotic liver parenchyma is often stiff and less amenable to transection, and bleeding tendency is increased especially when there is concomitant portal hypertension, thrombocytopenia and coagulopathy[11]. Patients are also at greater risk of post-operative complications such as post-hepatectomy liver failure and death[12]. A recent multicentre study demonstrated that LC was associated with adverse outcomes in laparoscopic liver resections (LLR) [13]. Not surprisingly, a recent survey of surgeons also revealed that most surgeons considered LC has a major factor impacting the outcomes of LLR [14]. Nonetheless to date, none of the DSS have considered the presence of cirrhosis in the calculation of the final difficulty score [5]. In the Iwate score only 1 difficulty point is accorded for the presence Child-Pugh B cirrhosis, but no points are given for Child-Pugh A cirrhosis. To date, the presence of portal hypertension is not included in any DSS, likely because it was traditionally considered a contraindication for LR.

Although, previous studies had demonstrated the detrimental impact of LC on the outcomes of LLR, these studies were associated with several limitations such as including all types/ extents of LLR including difficult and simple resections and including various pathologies such as liver metastases and benign tumors which could potentially confound the study result [15]. Some authors had also reported that the impact of LC on the outcomes of LLR correlated with the extent and difficulty of LLR [16]. LC resulted in poorer outcomes in patients undergoing more complex [Institut Mutualiste Montsouris (IMM) II/III] but not simpler IMM I LLR [16].

Hence, with these previous limitations in mind, we performed this matched-controlled study to analyze the impact of the presence and severity of LC as well as portal hypertension (PHT) on the difficulty of MILR focusing specifically on patients with primary liver malignancies undergoing minor resection in the anterolateral segments.

Methods

This was a retrospective review of 9064 patients who underwent minor MILR of the anterolateral segments (segment 2/3/4b/5/6) across 60 international centers between 2004–2021. Of these, 4,363 MILR were performed for hepatocellular carcinoma, cholangiohepatoma or intrahepatic cholangiocarcinoma. All institutions obtained their respective approvals according to their local center’s requirements. This study was approved by the Singapore General Hospital Institution Review Board and the need for patient consent was waived. The deidentified data were collected in the individual centers. These were collated and analyzed centrally at the Singapore General Hospital.

Only patients who underwent totally laparoscopic or robotic liver resections were included. Hand-assisted or laparoscopic-assisted cases were excluded. 428 patients who had previous liver surgery were excluded. Of the remaining 3935 patients, 177 with concomitant multiple liver resections were excluded and a further 83 patients who underwent concomitant major operations such as bilio-enteric anastomoses, colectomies, stoma reversal, gastrectomies, splenectomies and vascular resections were excluded. Finally, 3675 cases were included in this study. Of note, patients who underwent concomitant minor operations such as hernia repair, local ablation and hilar lymph node dissection were included.

Definitions

Liver resections were defined according to the 2000 Brisbane classification[17]. Anterolateral segments included segments 2/3/4b/5/6. Only minor resections were included and these were classified as segmentectomy or wedge/partial resections. Notably, left lateral sectionectomies were excluded. Traditional major resections classified as resection of 3 or more segments were excluded. Additionally, right anterior and right posterior sectionectomies were also considered as major resections in this study and excluded [18,19]. Diameter of the largest lesion was used in the cases of multiple tumors.

Difficulty of resections were graded according to the Iwate score [9]. Post-operative complications were classified according to the Clavien-Dindo classification and recorded for up to 30 days or during the same hospitalization [20]. Clinically significant portal hypertension (PHT) was defined as the presence of ascites, varices or splenomegaly with a platelet count of less than 100 × 109/L [15, 21]. Information on the presence of splenomegaly was obtained from an individual center’s preoperative radiologic reports.

Statistical analyses

Propensity score matching (PSM) [22] and Coarsened Exact Matching (CEM) [23] were used to estimate the effect of varying degrees of liver cirrhosis on minimally invasive minor anterolateral hepatectomy. For propensity score matching, the propensity score was estimated with logistic regression. The factors used in calculating the propensity score are the baseline variables stated in Table 1 – age at operation, gender, robotic or laparoscopic approach, previous abdominal operations, year of operation, ASA status, tumor type, tumor size, multifocality of tumor, concomitant minor operations or hilar lymph node dissection, type of resection, Iwate score and Iwate difficulty grade. For comparison in patients with or without portal hypertension, an additional variable of Child Pugh level was used in the matching. A random-effects parameter was also included in the model to account for between center variations.

Table 1.

Comparison between baseline characteristics of MILR if the anterolateral segments in Childs A cirrhosis v non-cirrhosis

Entire unmatched cohort 1:1 PSM (nearest neighbour matching) 1:1 CEM
All (N = 3430) Child A Cirrhosis (N = 2118) Non-cirrhosis (N = 1312) P-value Child A Cirrhosis (N = 991) Non-cirrhosis (N = 991) P-value (paired) Child A Cirrhosis (N = 518) Non-cirrhosis (N = 518) P-value (paired)
Median age (IQR), yrs 64.00 [55.00, 72.00] 63.00 [55.00, 71.00] 64.00 [55.00, 73.00] 0.122 63.00 [55.00, 70.79] 64.00 [55.00, 72.00] 0.445 64.00 [56.00, 71.00] 64.00 [56.00, 71.00] 0.878
Male sex, n (%) 2468 (72.0) 1567 (74.0) 901 (68.7) 0.001 721 (72.8) 717 (72.4) 0.880 424 (81.9) 424 (81.9) NA
Median BMI (IQR) 24.60 [22.21, 27.44] 24.70 [22.24, 27.52] 24.41 [22.20, 27.25] 0.076 24.60 [22.32, 27.62] 24.30 [22.03, 26.99] 0.072 24.60 [22.21, 27.00] 24.20 [22.10, 26.82] 0.338
Robotic, n (%) 400 (11.7) 221 (10.4) 179 (13.6) 138 (13.9) 128 (12.9) 24 (4.6) 24 (4.6)
Laparoscopic, n (%) 3030 (88.3) 1897 (89.6) 1133 (86.4) 0.005 853 (86.1) 863 (87.1) 0.555 494 (95.4) 494 (95.4) NA
Previous abdominal surgery, n (%) 670 (20.2) 399 (19.8) 271 (20.8) 0.508 194 (19.6) 202 (20.4) 0.694 63 (12.2) 63 (12.2) NA
Year of surgery, n (%)
2004–2009 193 (5.6) 132 (6.2) 61 (4.6) 61 (6.2) 53 (5.3) 19 (3.7) 19 (3.7)
2010–2015 968 (28.2) 617 (29.1) 351 (26.8) 279 (28.2) 279 (28.2) 127 (24.5) 127 (24.5)
2016–2021 2269 (66.2) 1369 (64.6) 900 (68.6) 0.028 651 (65.7) 659 (66.5) 0.325 372 (71.8) 372 (71.8) NA
ASA score, n (%)
 1/2 2356 (68.7) 1454 (68.7) 902 (68.8) 688 (69.4) 682 (68.8) 391 (75.5) 391 (75.5)
 3/4 1071 (31.3) 662 (31.3) 409 (31.2) 0.987 303 (30.6) 309 (31.2) 0.807 127 (24.5) 127 (24.5) NA
Tumor type, n (%)
 HCC 3026 (88.4) 1989 (94.0) 1037 (79.5) 926 (93.4) 923 (93.1) 514 (99.2) 514 (99.2)
 ICC/ cholangiohepatoma 396 (11.6) 128 (6.0) 268 (20.5) <0.001 65 (6.6) 68 (6.9) 0.815 4 (0.8) 4 (0.8) NA
Median tumor size, mm (IQR) 29.00 [20.00, 40.00] 26.00 [20.00, 37.00] 30.00 [21.00, 45.00] <0.001 30.00 [20.00, 40.00] 30.00 [20.00, 40.00] 0.564 25.00 [20.00, 33.00] 25.00 [19.00, 35.00] 0.417
Multiple tumors, n (%) 302 (8.8) 206 (9.7) 96 (7.3) 0.019 68 (6.9) 75 (7.6) 0.597 9 (1.7) 9 (1.7) NA
Wedge/partial, n (%) 2004 (58.4) 1319 (62.3) 685 (52.2) 554 (55.9) 558 (56.3) 314 (60.6) 314 (60.6)
Segmentectomy, n (%) 1426 (41.6) 799 (37.7) 627 (47.8) <0.001 437 (44.1) 433 (43.7) 0.888 204 (39.4) 204 (39.4) NA
Concomitant minor surgery excluding cholecystectomy, n (%) 113 (3.3) 86 (4.1) 27 (2.1) 0.002 22 (2.2) 21 (2.1) 1.000 2 (0.4) 2 (0.4) NA
Hilar lymph node dissection, n (%) 112 (3.3) 9 (0.4) 103 (7.9) <0.001 9 (0.9) 13 (1.3) 0.453 1 (0.2) 1 (0.2) NA
Median Iwate difficulty score, [IQR](range) 4.00 [3.00, 6.00] (1, 9) 4.00 [2.00, 6.00] (1, 9) 4.00 [3.00, 7.00] (1, 9) <0.001 4.00 [3.00, 6.00] (1, 9) 4.00 [3.00, 6.00] (1, 9) 0.870 4.00 [3.00, 6.00] (1, 8) 4.00 [3.00, 6.00] (1, 8) NA
Iwate difficulty, n (%)
 Low 1533 (44.7) 1053 (49.7) 480 (36.6) 418 (42.2) 406 (41.0) 249 (48.1) 249 (48.1)
 Intermediate 1253 (36.6) 758 (35.8) 495 (37.8) 364 (36.7) 383 (38.6) 182 (35.1) 182 (35.1)
 High 642 (18.7) 306 (14.5) 336 (25.6) <0.001 209 (21.1) 202 (20.4) 0.856 87 (16.8) 87 (16.8) NA
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For PSM of comparison of Child A cirrhotic against non-cirrhotic liver in Table 1 and 2, patients of one strata were matched 1:1, using nearest neighbour matching without replacement or discard, utilizing logit link, to patients of the other strata. To improve matching, a small caliper was used to achieve good balance of < 0.1 across all variables after matching. During matching, any patient with missing data in any of the variables used for matching would be discarded. Similar methodology was employed for PSM comparison in table 3–6, comparing Child A to Child B, and cirrhosis with portal hypertension to cirrhosis without portal hypertension.

Table 2.

Comparison between perioperative outcomes of MILR in Child’s A cirrhosis vs non-cirrhosis

Entire unmatched cohort 1:1 PSM (nearest neighbour) 1:1 CEM
All (N = 3430) Childs A Cirrhosis (N = 2118) Non-cirrhosis (N = 1312) P-value Childs A Cirrhosis (N = 991) Non-cirrhosis (N = 991) P-value (paired) Childs A Cirrhosis (N = 518) Non-cirrhosis (N = 518) P-value (paired)
Open conversion, n (%) 183 (5.3) 127 (6.0) 56 (4.3) 0.035 62 (6.3) 39 (3.9) 0.024 32 (6.2) 18 (3.5) 0.050
Median operating time (IQR), min 190.00 [135.00, 253.75] 190.00 [134.00, 250.00] 195.00 [140.00, 260.00] 0.062 192.00 [130.00, 260.00] 190.00 [135.00, 252.00] 0.479 190.00 [135.00, 250.00] 185.00 [130.00, 245.50] 0.532
Median blood loss (IQR), ml 150.00 [50.00, 300.00] 150.00 [50.00, 300.00] 150.00 [50.00, 300.00] 0.538 170.00 [50.00, 350.00] 150.00 [50.00, 300.00] <0.001 150.00 [50.00, 300.00] 100.00 [50.00, 255.00] 0.014
Blood loss > 500 mls, n (%) 343 (10.4) 232 (11.4) 111 (8.8) 0.018 132 (13.9) 81 (8.5) 0.001 51 (10.3) 44 (8.7) 0.380
Intraoperative blood transfusion, n (%) 216 (6.3) 157 (7.4) 59 (4.5) 0.001 77 (7.8) 39 (3.9) <0.001 33 (6.4) 22 (4.2) 0.178
Pringle maneuver applied, n (%) 1626 (48.0) 942 (45.1) 684 (52.8) <0.001 474 (48.5) 495 (50.6) 0.295 258 (50.2) 257 (50.1) 1.000
Median postoperative stay, d (IQR), mean (SD) 5.00 [4.00, 7.00], 6.56 (6.80) 5.00 [4.00, 7.00], 6.74 (7.47) 5.00 [4.00, 7.00], 6.28 (5.53) 0.001 5.00 [4.00, 7.00], 6.87 (9.51) 5.00 [4.00, 7.00], 6.31 (4.81) 0.114 6.00 [4.00, 8.00], 6.84 (5.68) 5.00 [4.00, 7.00], 6.55 (5.10) 0.104
Postoperative morbidity, n (%) 517 (15.1) 349 (16.5) 168 (12.8) 0.004 162 (16.4) 116 (11.7) 0.004 84 (16.3) 48 (9.3) 0.001
Major morbidity (Clavien-Dindo grade> 2), n (%) 120 (3.5) 75 (3.6) 45 (3.4) 0.940 36 (3.6) 30 (3.0) 0.525 17 (3.3) 15 (2.9) 0.855
Reoperation, n (%) 12 (0.3) 10 (0.5) 2 (0.2) 0.147 7 (0.7) 1 (0.1) 0.077 3 (0.6) 1 (0.2) 0.617
30-day readmission, n (%) 65 (1.9) 45 (2.1) 20 (1.5) 0.260 24 (2.4) 17 (1.7) 0.349 9 (1.7) 6 (1.2) 0.606
30-day mortality, n (%) 6 (0.2) 6 (0.3) 0 (0.0) 0.089 2 (0.2) 0 (0.0) 0.480 1 (0.2) 0 (0.0) 1.000
In-hospital mortality, n (%) 12 (0.3) 12 (0.6) 0 (0.0) 0.005 6 (0.6) 0 (0.0) 0.041 1 (0.2) 0 (0.0) 1.000
90-day mortality, n (%) 11 (0.3) 11 (0.5) 0 (0.0) 0.009 4 (0.4) 0 (0.0) 0.134 1 (0.2) 0 (0.0) 1.000
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Table 3.

Comparison between baseline characteristics of MILR in 2118 Childs A vs 245 Childs B cirrhosis

Entire unmatched cohort 1:1 PSM (nearest neighbour matching) 1:1 CEM
All (N = 2363) Childs A (N =2118) Childs B (N = 245) P-value Childs A (N = 215) Childs B (N = 215) P-value (paried) Childs A (N = 191) Childs B (N = 191) P-value (paired)
Median age (IQR), yrs 63.00 [55.00, 71.00] 63.00 [55.00, 71.00] 61.00 [51.00, 69.00] 0.002 59.00 [52.10, 68.00] 61.00 [51.00, 70.00] 0.791 61.00 [53.00, 69.00] 60.00 [51.00, 68.95] 0.068
Male sex, n (%) 1760 (74.5) 1567 (74.0) 193 (78.8) 0.121 172 (80.0) 171 (79.5) 1.000 156 (81.7) 156 (81.7) NA
BMI 24.70 [22.28, 27.50] 24.70 [22.24, 27.52] 24.94 [22.48, 27.33] 0.873 24.16 [22.05, 26.65] 24.77 [22.43, 27.12] 0.275 24.72 [23.01, 27.19] 24.40 [22.15, 26.97] 0.113
Robotic, n (%) 260 (11.0) 221 (10.4) 39 (15.9) 36 (16.7) 33 (15.3) 23 (12.0) 23 (12.0)
Laparoscopic, n (%) 2103 (89.0) 1897 (89.6) 206 (84.1) 0.013 179 (83.3) 182 (84.7) 0.787 168 (88.0) 168 (88.0) NA
Previous abdominal surgery, n (%) 440 (19.5) 399 (19.8) 41 (17.2) 0.385 33 (15.3) 38 (17.7) 0.603 27 (14.1) 27 (14.1) NA
Year of surgery, n (%)
2004–2009 148 (6.3) 132 (6.2) 16 (6.5) 14 (6.5) 14 (6.5) 11 (5.8) 11 (5.8)
2010–2015 702 (29.7) 617 (29.1) 85 (34.7) 71 (33.0) 70 (32.6) 65 (34.0) 65 (34.0)
2016–2021 1513 (64.0) 1369 (64.6) 144 (58.8) 0.174 130 (60.5) 131 (60.9) 0.873 115 (60.2) 115 (60.2) NA
ASA score, n (%)
 1/2 1621 (68.7) 1454 (68.7) 167 (68.2) 138 (64.2) 147 (68.4) 135 (70.7) 135 (70.7)
 3/4 740 (31.3) 662 (31.3) 78 (31.8) 0.918 77 (35.8) 68 (31.6) 0.342 56 (29.3) 56 (29.3) NA
Tumor type, n (%)
 HCC 2225 (94.2) 1989 (94.0) 236 (96.3) 213 (99.1) 213 (99.1) 191 (100.0) 191 (100.0)
 ICC/ cholangiohepatoma 137 (5.8) 128 (6.0) 9 (3.7) 0.174 2 (0.9) 2 (0.9) 1.000 0 (0.0) 0 (0.0) NA
Median tumor size, mm (IQR) 26.00 [20.00, 38.00] 26.00 [20.00, 37.00] 30.00 [20.00, 45.00] 0.026 28.00 [20.00, 45.00] 30.00 [20.00, 45.00] 0.839 30.00 [20.00, 43.50] 30.00 [20.00, 45.00] 0.259
Multiple tumors, n (%) 230 (9.7) 206 (9.7) 24 (9.8) 1.000 15 (7.0) 17 (7.9) 0.855 5 (2.6) 5 (2.6) NA
Wedge/ partial liver resection, n (%) 1444 (61.1) 1319 (62.3) 125 (51.0) 99 (46.0) 116 (54.0) 97 (50.8) 97 (50.8)
Segmentectomy, n (%) 919 (38.9) 799 (37.7) 120 (49.0) 0.001 116 (54.0) 99 (46.0) 0.068 94 (49.2) 94 (49.2) NA
Concomitant minor surgery excluding cholecystectomy, n (%) 100 (4.2) 86 (4.1) 14 (5.7) 0.289 10 (4.7) 12 (5.6) 0.823 6 (3.1) 6 (3.1) NA
Hilar lymph node dissection, n (%) 10 (0.4) 9 (0.4) 1 (0.4) 1.000 2 (0.9) 1 (0.5) 1.000 0 (0.0) 0 (0.0) NA
Median Iwate difficulty score excluding Child score, [IQR] (range) 4.00 [2.00, 6.00] (1, 9) 4.00 [2.00, 6.00] (1, 9) 4.00 [2.00, 6.00] (1, 8) 0.046 4.00 [3.00, 6.00] (1, 8) 4.00 [2.00, 6.00] (1, 8) 0.293 4.00 [3.00, 6.00] (1, 8) 4.00 [3.00, 6.00] (1, 8) NA
Iwate difficulty exclude Child score, n (%)
 Low 1157 (49.0) 1055 (49.8) 102 (41.6) 87 (40.5) 94 (43.7) 80 (41.9) 80 (41.9)
 Intermediate 859 (36.4) 760 (35.9) 99 (40.4) 79 (36.7) 81 (37.7) 71 (37.2) 71 (37.2)
 High 346 (14.6) 302 (14.3) 44 (18.0) 0.043 49 (22.8) 40 (18.6) 0.507 40 (20.9) 40 (20.9) NA
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For CEM, continuous variables were coarsened using an automatic binning algorithm based on Sturge’s rule into bins. Patients were 1:1 matched using with nearest neighbour matching without replacement within each stratum, any unmatched units in the stratum would be dropped. This methodology was applied to all 3 CEM models.

After matching, balance was checked via standardized mean difference across the covariates, with a threshold of 0.1 being indicative of tight match. Love plot of each match’s covariate balance was plotted and presented below (Supplementary data S1–S6).

For unpaired comparisons of frequencies of categorical variables, Chi squared was used. For the unpaired comparisons of median values and interquartile ranges, Mann-Whitney U test was used, and for the comparisons of mean values and standard deviations, one-way test was used. For paired sample tests, McNemar’s test was used for categorical variables and Wilcoxon Signed-Rank test was used for continuous. The statistical analyses were performed with RStudio version 1.4.1717, R version 4.1.0.

Results

A total of 3675 patients were included for final analysis (Figure 1). Of these, 1312 had no cirrhosis, 2118 had Child A cirrhosis and 245 patients had Child B cirrhosis.

Figure 1.

Figure 1.

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Selection of patients meeting study inclusion criteria.

Non-cirrhotic vs. Child A cirrhosis patients

A total of 3430 patients were enrolled in this cohort, including 2118 patients with Child A cirrhosis and 1312 patients without cirrhosis. The baseline characteristics are shown in Table 1. We conducted PSM and CEM to offset potential confounding factors. Before matching, gender (p = 0.001), year of surgery (p = 0.028), tumor type (p < 0.001), median tumor size (p < 0.001), multiple tumours (p = 0.019), surgical type (p < 0.001), concomitant minor surgery (p = 0.002), hilar lymph node dissection (p < 0.001), median difficulty score (p < 0.001), and IWATE difficulty score (p < 0.001) were statistically different between two groups. After 1:1 PSM, 991 matched pairs were included for further analysis. All the baseline characteristics of the two groups reached statistical equilibrium. Similarly, after 1:1 CEM matching, 518 matched pairs were included for further analysis and all baseline indicators reached equilibrium.

The perioperative outcomes are summarized in Table 2. In the entire unmatched cohort, the Child A cirrhosis group had a higher rate of open conversion (6.0% VS 4.3%, p = 0.035), blood loss > 500 mls (11.4% VS 8.8%, p = 0.018), intraoperative blood transfusion (7.4% VS 4.5%, p = 0.001), rate of pringle maneuver application (p < 0.001), median postoperative stay (p = 0.001), postoperative morbidity (p = 0.004), in-hospital mortality (p = 0.005), and 90-day mortality (p = 0.009) compared to non-cirrhotics. After 1:1 PSM, rate of open conversion (p = 0.024), median blood loss (p < 0.001), blood loss >500 mls (p = 0.001), intraoperative blood transfusion (p < 0.001), postoperative morbidity (p = 0.004), and in-hospital mortality (p = 0.041) were higher in the Child A cirrhosis group. In the 1:1 CEM cohort, the Child A cirrhosis group had higher rate of open conversion (p = 0.05), greater median blood loss (p = 0.014) and increased postoperative morbidity (p = 0.001).

Child A vs. Child B cirrhosis patients

In the entire unmatched cohort (2118 Child A group versus 245 Child B), there were some differences in median age, proportion of robotic versus laparoscopic approach, extent of surgery and median Iwate difficulty score excluding Child score (Table 3). After 1:1PSM and 1:1 CEM, 215 and 191 pairs of patients were included for further comparison, respectively. All baseline differences disappeared in the matched patient cohorts.

Table 4 summarizes the perioperative outcomes. After 1:1PSM, the Child B cirrhosis group had a longer postoperative stay (p = 0.001) and a higher rate of major morbidity (p = 0.012). In the 1:1CEM cohort, Child B patients had higher rates of blood transfusion (p = 0.002), longer postoperative stay (p < 0.001), and greater major morbidity (p = 0.006).

Table 4.

Comparison between perioperative outcomes of MILR in Child’s A vs B cirrhosis

Entire unmatched cohort 1:1 PSM (nearest neighbour) 1:1 CEM
All (N = 2363) Childs A (N=2118) Childs B (N = 245) P-value Childs A (N = 215) Childs B (N = 215) P-value (paried) Childs A (N = 191) Childs B (N = 191) P-value (paired)
Open conversion, n (%) 138 (5.8) 127 (6.0) 11 (4.5) 0.419 10 (4.7) 8 (3.7) 0.803 10 (5.2) 9 (4.7) 1.000
Median operating time (IQR), min 190.00 [135.00, 250.00] 190.00 [134.00, 250.00] 201.50 [144.00, 260.00] 0.164 200.00 [143.00, 269.50] 194.00 [143.00, 260.00] 0.469 200.00 [145.00, 258.00] 200.50 [149.25, 260.00] 0.737
Median blood loss (IQR), ml 150.00 [50.00, 300.00] 150.00 [50.00, 300.00] 150.00 [50.00, 350.00] 0.078 200.00 [52.50, 400.00] 150.00 [60.00, 350.00] 0.738 150.00 [100.00, 350.00] 180.00 [84.50, 400.00] 0.482
Blood loss > 500 mls, n (%) 270 (11.9) 232 (11.4) 38 (15.9) 0.056 26 (12.4) 32 (15.2) 0.568 26 (13.9) 32 (17.2) 0.451
Intraoperative blood transfusion, n (%) 200 (8.5) 157 (7.4) 43 (17.6) <0.001 29 (13.5) 37 (17.2) 0.332 15 (7.9) 37 (19.4) 0.002
Pringle maneuver applied, n (%) 1045 (44.8) 942 (45.1) 103 (42.9) 0.571 93 (44.3) 97 (46.2) 0.766 94 (50.3) 82 (43.6) 0.213
Median postoperative stay, d (IQR), mean (SD) 6.00 [4.00, 8.00], 7.05 (7.60) 5.00 [4.00, 7.00], 6.74 (7.47) 7.00 [5.00, 13.00], 9.66 (8.21) <0.001 6.00 [4.00, 10.00], 9.07 (18.02) 7.00 [5.00, 13.00], 9.53 (7.11) 0.001 6.00 [4.00, 8.00], 7.09 (6.42) 8.00 [5.00, 13.00], 9.70 (7.67) <0.001
Postoperative morbidity, n (%) 408 (17.3) 349 (16.5) 59 (24.1) 0.004 40 (18.6) 50 (23.3) 0.282 37 (19.4) 45 (23.6) 0.374
Major morbidity (Clavien-Dindo grade> 2), n (%) 100 (4.2) 75 (3.6) 25 (10.2) <0.001 7 (3.3) 20 (9.3) 0.012 4 (2.1) 18 (9.4) 0.006
Reoperation, n (%) 12 (0.5) 10 (0.5) 2 (0.8) 0.358 0 (0.0) 2 (0.9) 0.480 0 (0.0) 0 (0.0) NA
30-day readmission, n (%) 50 (2.1) 45 (2.1) 5 (2.0) 1.000 4 (1.9) 4 (1.9) 1.000 7 (3.7) 3 (1.6) 0.343
30-day mortality, n (%) 10 (0.4) 6 (0.3) 4 (1.6) 0.014 1 (0.5) 3 (1.4) 0.617 0 (0.0) 2 (1.0) 0.480
In-hospital mortality, n (%) 14 (0.6) 12 (0.6) 2 (0.8) 0.650 1 (0.5) 1 (0.5) 1.000 0 (0.0) 2 (1.0) 0.480
90-day mortality, n (%) 16 (0.7) 11 (0.5) 5 (2.0) 0.019 2 (0.9) 3 (1.4) 1.000 0 (0.0) 2 (1.0) 0.480
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Cirrhotic patients (all Child grades) without vs. with PHT

The entire unmatched cohort contained 626 patients with cirrhosis and PHT, and 1701 patients with cirrhosis but without PHT (Table 5). After 1:1 PSM and 1:1 CEM, 450 and 290 matched pair were included in each group, respectively, and all baseline characteristics were balanced (Table 5).

Table 5.

Comparison between baseline characteristics of MILR in 2361 cirrhosis patients with and without portal hypertension ()

Entire unmatched cohort 1:1 PSM (nearest neighbour matching) 1:1 CEM
All (N = 2327) Cirrhosis PHT (N = 626) Cirrhosis NPHT (N = 1701) P-value Cirrhosis PHT (N = 450) Cirrhosis NPHT (N = 450) P-value Cirrhosis PHT (N = 290) Cirrhosis NPHT (N = 290) P-value (paired)
Median age (IQR), yrs 63.00 [55.00, 71.00] 63.00 [55.00, 71.00] 63.00 [55.00, 71.00] 0.734 62.00 [54.00, 70.00] 64.00 [55.00, 70.00] 0.217 61.00 [54.00, 69.00] 62.00 [55.00, 69.00] 0.607
Male sex, n (%) 1731 (74.4) 468 (74.8) 1263 (74.3) 0.844 339 (75.3) 335 (74.4) 0.822 230 (79.3) 230 (79.3) NA
Median BMI (IQR) 24.68 [22.22, 27.45] 25.08 [22.84, 28.00] 24.50 [22.10, 27.25] <0.001 24.93 [22.50, 27.70] 25.00 [22.49, 27.68] 0.826 24.80 [22.70, 27.40] 24.34 [22.16, 27.24] 0.426
Robotic, n (%) 260 (11.2) 56 (8.9) 204 (12.0) 43 (9.6) 41 (9.1) 12 (4.1) 12 (4.1)
Laparoscopic, n (%) 2067 (88.8) 570 (91.1) 1497 (88.0) 0.046 407 (90.4) 409 (90.9) 0.907 278 (95.9) 278 (95.9) NA
Previous abdominal surgery, n (%) 436 (19.7) 142 (22.7) 294 (18.5) 0.028 98 (21.8) 97 (21.6) 1.000 36 (12.4) 36 (12.4) NA
Childs A, n (%) 2082 (89.5) 1581 (92.9) 501 (80.0) 392 (87.1) 398 (88.4) 280 (96.6) 280 (96.6)
Childs B, n (%) 245 (10.5) 120 (7.1) 125 (20.0) 0.028 58 (12.9) 52 (11.6) 0.561 10 (3.4) 10 (3.4) NA
Year of surgery, n (%)
2004–2009 144 (6.2) 48 (7.7) 96 (5.6) 33 (7.3) 37 (8.2) 10 (3.4) 10 (3.4)
2010–2015 692 (29.7) 173 (27.6) 519 (30.5) 121 (26.9) 118 (26.2) 92 (31.7) 92 (31.7)
2016–2021 1491 (64.1) 405 (64.7) 1086 (63.8) 0.113 296 (65.8) 295 (65.6) 0.939 188 (64.8) 188 (64.8) NA
ASA score, n (%)
 1/2 1604 (69.0) 393 (62.8) 1211 (71.3) 298 (66.2) 297 (66.0) 205 (70.7) 205 (70.7)
 3/4 721 (31.0) 233 (37.2) 488 (28.7) <0.001 152 (33.8) 153 (34.0) 1.000 85 (29.3) 85 (29.3) NA
Tumor type, n (%)
 HCC 2194 (94.3) 613 (97.9) 1581 (93.0) 441 (98.0) 440 (97.8) 288 (99.3) 288 (99.3)
 ICC/ cholangiohepatoma 132 (5.7) 13 (2.1) 119 (7.0) <0.001 9 (2.0) 10 (2.2) 1.000 2 (0.7) 2 (0.7) NA
Median tumor size, mm (IQR) 26.00 [20.00, 38.00] 25.00 [18.00, 35.00] 27.00 [20.00, 40.00] <0.001 25.00 [18.00, 35.00] 25.00 [20.00, 35.00] 0.620 23.50 [18.00, 32.00] 25.00 [19.25, 30.00] 0.748
Multiple tumors, n (%) 228 (9.8) 50 (8.0) 178 (10.5) 0.088 35 (7.8) 32 (7.1) 0.807 4 (1.4) 4 (1.4) NA
Wedge/ partial liver resection, n (%) 1420 (61.0) 410 (65.5) 1010 (59.4) 291 (64.7) 293 (65.1) 199 (68.6) 199 (68.6)
Segmentectomy, n (%) 907 (39.0) 216 (34.5) 691 (40.6) 0.008 159 (35.3) 157 (34.9) 0.942 91 (31.4) 91 (31.4) NA
Concomitant minor surgery excluding cholecystectomy, n (%) 95 (4.1) 31 (5.0) 64 (3.8) 0.242 22 (4.9) 21 (4.7) 1.000 5 (1.7) 5 (1.7) NA
Hilar lymph node dissection, n (%) 9 (0.4) 5 (0.8) 4 (0.2) 0.065 0 (0.0) 1 (0.2) 1.000 0 (0.0) 0 (0.0) NA
Median Iwate difficulty score, [IQR] (range) 4.00 [3.00, 6.00] (1, 9) 4.00 [2.00, 6.00] (1, 9) 4.00 [3.00, 6.00] (1, 9) 0.008 3.00 [2.00, 6.00] (1, 8) 3.00 [2.00, 5.00] (1, 9) 0.704 3.00 [2.00, 5.00] (1, 9) 3.00 [2.00, 5.00] (1, 9) NA
Iwate difficulty, n (%)
 Low 1097 (47.2) 309 (49.4) 788 (46.4) 232 (51.6) 233 (51.8) 169 (58.3) 169 (58.3)
 Intermediate 841 (36.2) 236 (37.7) 605 (35.6) 152 (33.8) 164 (36.4) 97 (33.4) 97 (33.4)
 High 388 (16.7) 81 (12.9) 307 (18.1) 0.013 66 (14.7) 53 (11.8) 0.533 24 (8.3) 24 (8.3) NA
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Perioperative outcomes are summarised in Table 6. In the 1:1PSM cohort, patients with PHT experienced higher rates of blood loss > 500 mls (p = 0.003) and intraoperative blood transfusion (p = 0.025). There were no differences in other outcomes. After 1:1 CEM, the two groups had no significant differences in outcomes.

Table 6.

Comparison between perioperative outcomes of MILR in cirrhosis patients with and without PHT

Entire unmatched cohort 1:1 PSM (nearest neighbour) 1:1 CEM
All (N = 2327) Cirrhosis PHT (N = 626) Cirrhosis NPHT (N = 1701) P-value Cirrhosis PHT (N = 450) Cirrhosis NPHT (N = 450) P-value Cirrhosis PHT (N = 290) Cirrhosis NPHT (N = 290) P-value (paired)
Open conversion, n (%) 137 (5.9) 49 (7.8) 88 (5.2) 0.021 38 (8.4) 25 (5.6) 0.118 25 (8.6) 13 (4.5) 0.067
Median operating time (IQR), min 190.00 [136.00, 252.00] 180.00 [124.00, 245.00] 195.00 [140.00, 255.00] 0.010 180.00 [124.50, 250.00] 185.00 [134.00, 240.00] 0.872 180.00 [124.25, 240.00] 180.00 [130.00, 243.00] 0.563
Median blood loss (IQR), ml 150.00 [50.00, 300.00] 200.00 [50.00, 350.00] 110.00 [50.00, 300.00] <0.001 200.00 [100.00, 400.00] 120.00 [50.00, 300.00] <0.001 200.00 [100.00, 327.50] 150.00 [50.00, 300.00] 0.046
Blood loss > 500 mls, n (%) 262 (11.7) 89 (14.8) 173 (10.6) 0.008 70 (15.9) 39 (9.0) 0.003 36 (13.0) 34 (12.5) 0.787
Intraoperative blood transfusion, n (%) 198 (8.5) 65 (10.4) 133 (7.8) 0.061 51 (11.3) 31 (6.9) 0.025 24 (8.3) 17 (5.9) 0.296
Pringle maneuver applied, n (%) 1033 (45.0) 281 (45.4) 752 (44.8) 0.850 199 (44.5) 186 (41.6) 0.446 127 (43.9) 113 (39.6) 0.298
Median postoperative stay, d (IQR), mean (SD) 6.00 [4.00, 8.00], 7.09 (7.65) 5.00 [4.00, 8.00], 7.08 (6.96) 6.00 [4.00, 8.00], 7.09 (7.89) 0.231 5.77 [4.00, 8.00], 7.01 (6.21) 5.00 [4.00, 7.00], 6.98 (12.59) 0.141 5.00 [4.00, 7.00], 7.04 (7.23) 5.00 [4.00, 8.00], 6.82 (5.29) 0.887
Postoperative morbidity, n (%) 402 (17.3) 128 (20.5) 274 (16.2) 0.017 78 (17.4) 73 (16.3) 0.721 54 (18.6) 42 (14.5) 0.201
Major morbidity (Clavien-Dindo grade> 2), n (%) 98 (4.2) 33 (5.3) 65 (3.8) 0.155 23 (5.1) 15 (3.3) 0.243 11 (3.8) 10 (3.4) 1.000
Reoperation, n (%) 12 (0.5) 3 (0.5) 9 (0.5) 1.000 2 (0.4) 2 (0.4) 1.000 1 (0.3) 1 (0.3) 1.000
30-day readmission, n (%) 50 (2.2) 12 (1.9) 38 (2.2) 0.754 11 (2.4) 14 (3.1) 0.663 6 (2.1) 8 (2.8) 0.789
30-day mortality, n (%) 9 (0.4) 2 (0.3) 7 (0.4) 1.000 1 (0.2) 2 (0.4) 1.000 2 (0.7) 1 (0.3) 1.000
In-hospital mortality, n (%) 13 (0.6) 2 (0.3) 11 (0.6) 0.533 1 (0.2) 1 (0.2) 1.000 2 (0.7) 2 (0.7) 1.000
90-day mortality, n (%) 15 (0.6) 2 (0.3) 13 (0.8) 0.380 1 (0.2) 3 (0.7) 0.617 2 (0.7) 3 (1.0) 1.000
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Discussion

Minor resections (wedge and segmentectomy) in AL segments are often considered the ‘easiest’ technical resections in MILR by almost all existing DSS. Both the Ban DSS [6] and its later modification, the Iwate criteria [9], allocate fewer difficulty points to lesions in superficial, anterolateral segments. In the Hasegawa score, lesions in anterolateral segments 2/3/4 are accorded lower scores (0 points) versus lesions in S5/6 (1 point) and S7/8 (2 points) [24]. The Southampton score assigns 0 difficulty points for minor resections, versus 2 points for technically major and 4 points for anatomically major resections respectively [7]. Finally, in the IMM score, wedge resection and left lateral sectionectomies are considered to be the simplest resections, while anterolateral segmentectomies are intermediate level [8]. As such, these cases are thought to be suitable for novice surgeons in the early stages of their learning curve for LLR.

In this large multicentre study, we found that patient with CP A cirrhosis who underwent minor LLR in the AL segments experienced higher rates of open conversion, blood loss and greater post-operative morbidity compared to patients with no cirrhosis. Although patient cohorts were matched to ensure there were no differences in preoperative baseline characteristics, the group with CP A cirrhosis had inferior perioperative outcomes. This implies that the presence of underlying LC does in fact, increase the complexity of LLR, even for technically ‘easy’ LLRs.

Previous studies had suggested that LC increased the complexity of LLR. Hobeika et al analyzed 282 matched pairs of patients with and without cirrhosis who underwent LLR across 27 centers [13]. The LC group experienced higher rates of severe complications (odds ratio (OR) 1.74, 95 percent confidence interval (CI) 0.92 to 3.41; p = 0.096), PHLF (OR 7.13, 0.91 to 323.10; p = 0.068), and a higher risk of death (OR 5.13, 1.08 to 48.61; p = 0.039) versus non-cirrhotics. Similarly, Goh et al reported a single-center matched study compared MILR in patients with LC versus without, and found that the LC group had greater blood loss, higher blood transfusion rates, increased conversion and postoperative morbidity, as well as longer operation times and postoperative hospital stay [16]. In the aforementioned study, 41% of lesions were located in ‘difficult segments (I, IVa, VII, VIII). Hence, a major difference from our study was that both the Hobeika et al and Goh et al studies contained a mixture of major and minor LLRs. Interestingly, Goh et al found that upon subset analyses, LC only significantly impacted outcomes of more complex resection [Institut Mutualiste Montsouris (IMM) II/III] and not simpler IMM I resections [16].

Hence, in contrast to these previous studies; the present study focused exclusively on “technically simple” minor resections in the AL segments, so as to minimise the confounding effect of tumour location and extent of resection on perioperative outcomes. Furthermore, only patients with primary malignancies were included unlike previous studies [13,16], as a major confounding factor in these studies was the inclusion of patients with other pathologies including benign lesions and colorectal liver metastases which occurred more frequently in the non-cirrhotic cohort. In the present analysis, despite controlling for various factors the LC cohort was associated with significantly poorer outcomes compared to the non-cirrhotic arm. These results suggest that there is room to further refine existing DSS for MILR by incorporating the presence of cirrhosis as a variable into the computation of scores. This will facilitate a more accurate preoperative estimation of technical difficulty, so as to allow appropriate case selection according to the expertise level of individual surgeons.

In the second part of this study, we compared outcomes following LLR for patients with CP B versus CP A. Major morbidity rates were higher in CP B cirrhosis, and this ultimately resulted in longer LOS as well. It is worthwhile to note, however, that intraoperative outcomes (operating time, blood loss, transfusion, conversion rates) were similar. These results were similar to Watanabe’s study [25], where 357 LLR patients were divided into three cohorts as follows: Child-Pugh A (n=280), Child-Pugh B7 (n=42) and Child-Pugh B8/9 (n=35)(22). 14% of patients in the Child-Pugh A cohort underwent anatomic resection while all patients in the advanced cirrhosis group had non-anatomical resections. Patients with Child-Pugh B cirrhosis had significantly more post-operative complications versus Child-Pugh A (P=0.033), with no differences in operative time and blood loss. Furthermore, the Child-Pugh B8/9 group had significantly higher complication rate than other two groups (Child-Pugh A vs. B7 vs. B8/9: 8.2% vs. 9.6% vs. 26%, respectively; p = 0.010). Troisi et al performed a multicenter PSM study for patients with Child-Pugh B cirrhosis who underwent open versus LLR for hepatocellular carcinoma [26]. Amongst the LLR cohort, patients with Child-Pugh B9 developed more complications compared to those with B8 and B7 cirrhosis. From this, we can infer that although the severity of cirrhosis might not directly impact the conduct of surgery, patients with severe liver disease are more systemically unwell and hence they are at greater risk of post-operative complications. One important application of DSS for MILR is to enable appropriate preoperative risk counselling for patients. To this end, the inclusion of the presence of cirrhosis as well as its severity into future DSS would enhance its effectiveness.

Finally, we found that patients with cirrhosis as well as PHT had slightly higher rates of blood loss (P<0.001) and blood transfusion (P=0.025) on PSM compared to their counterparts with no PHT, although the differences did not persist on CEM. This suggests that the MIS approach may partially mitigate the risks of LR in this group of patients, particularly that of bleeding. The magnified laparoscopic view in MILR allows precise dissection of vasculobiliary structures, which may be ligated by surgical clips and energy devices [26], while continuous pneumoperitoneum pressure tamponades venous ooze from the liver surface.

A key strength of this study is that it contains one of the largest multicentre patient cohorts to date, from both Eastern and Western units and focussed on a specific subset of patients undergoing MILR. However, there are several limitations that must be highlighted. The retrospective nature of this study, as well as the inclusion of patients over a relatively long period meant that information and selection biases are inherent despite the utilization of two robust statistical matching techniques. Most cases were performed in high-volume centers and the results may not be readily generalizable. However, the recent move to centralise complex surgical procedures to specialty units may mean that this is a realistic portrayal of surgical practises in the near future. Almost 40% of resections in this study were segmentectomies. As such, the median Iwate score was 4, places them in the ‘intermediate’ difficulty category, hence cases were slightly more complex despite being in the ‘easy’ anterolateral segments. The proportion of patients with CP B cirrhosis and PHT were also relatively small. Furthermore, although the measurement of hepatic venous-portal gradient is the gold standard for the diagnosis of portal hypertension, this invasive method is not routinely used in most centers prior to liver resection. Hence, a simple definition was used for the presence of clinically-significant PHT due to the limitations of this study. Finally, as an international multicenter study, there would be heterogeneity in each individual center’s surgical technique, selection process and postoperative management.

Conclusion

This study demonstrated that the presence and severity of LC affected and compounded the difficulty of LLR even for ‘simple’ minor resections in AL segments, resulting in higher rates of open conversion, blood loss and greater post-operative morbidity. Inclusion of cirrhosis into future DSS would be important for case selection and would allow more accurate benchmarking of cases for surgical audits.

Supplementary Material

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Acknowledgement

Funding

Dr T. P. Kingham was partially supported by the US National Cancer Institute MSKCC Core Grant number P30 CA008748 for this study

Dr M. Yin was partially funded by the Research Project of Zhejiang Provincial Public Welfare Fund project in the Field of Social development (LGF20H160028)

Dr B.K.P. Goh was partially funded by a grant from the Intuitive Foundation for this work. Any research findings, conclusions, or recommendations expressed in this work are those of the authors and not of the Intuitive Foundation

Collaborators

International robotic and laparoscopic liver resection study group investigators

  1. Nicholas Syn (Yong Loo Lin School of Medicine, National University of Singapore)

  2. Mikel Gastaca (Hepatobiliary Surgery and Liver Transplantation Unit, Biocruces Bizkaia Health Research Institute, Cruces University Hospital, University of the Basque Country, Bilbao, Spain)

  3. Celine De Meyere (Department of Digestive and Hepatobiliary/Pancreatic Surgery, Groeninge Hospital, Kortrijk, Belgium)

  4. Juul Meurs,(Department of Digestive and Hepatobiliary/Pancreatic Surgery, Groeninge Hospital, Kortrijk, Belgium)

  5. Kelvin K. Ng (Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, New Territories, Hong Kong SAR, China)

  6. Kit-Fai Lee (Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, New Territories, Hong Kong SAR, China)

  7. Pavel Tarakanov (Department of Hepato-Pancreato-Biliary Surgery, Moscow Clinical Scientific Center, Moscow, Russia)

  8. Ruslan Alikhanov (Department of Hepato-Pancreato-Biliary Surgery, Moscow Clinical Scientific Center, Moscow, Russia)

  9. Nita Thiruchelvam (Hepatopancreatobiliary Unit, Department of Surgery, Changi General Hospital, Singapore)

  10. Jae Young Jang (Department of General Surgery, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea)

  11. Masayuki Kojima (Department of Surgery, Fujita Health University School of Medicine, Aichi, Japan)

  12. Jaime Arthur Pirola Kruger (Liver Surgery Unit, Department of Gastroenterology, University of Sao Paulo School of Medicine, Sao Paulo, Brazil)

  13. Fabricio Ferreira Coelho (Liver Surgery Unit, Department of Gastroenterology, University of Sao Paulo School of Medicine, Sao Paulo, Brazil)

  14. Victor Lopez-Lopez (Department of General, Visceral and Transplantation Surgery, Clinic and University Hospital Virgen de la Arrixaca, IMIB-ARRIXACA, El Palmar, Murcia, Spain)

  15. Margarida Casellas I Robert (Hepatobiliary and Pancreatic Surgery Unit, Department of Surgery, Dr. Josep Trueta Hospital, IdIBGi, Girona, Spain)

  16. Roberto Montalti (Department of Clinical Medicine and Surgery, Division of HPB, Minimally Invasive and Robotic Surgery, Federico II University Hospital Naples, Naples, Italy)

  17. Mariano Giglio (Department of Clinical Medicine and Surgery, Division of HPB, Minimally Invasive and Robotic Surgery, Federico II University Hospital Naples, Naples, Italy)

  18. Boram Lee (Department of Surgery, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul, Korea)

  19. Mizelle D’Silva, (Department of Surgery, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul, Korea)

  20. Hao-Ping Wang Department of Surgery, Chang Gung Memorial Hospital, Kaohsiung

  21. Franco Pascual (Department of Hepatobiliary Surgery, Assistance Publique Hopitaux de Paris, Centre Hepato-Biliaire, Paul-Brousse Hospital, Villejuif, France)

  22. Mansour Saleh (Department of Hepatobiliary Surgery, Assistance Publique Hopitaux de Paris, Centre Hepato-Biliaire, Paul-Brousse Hospital, Villejuif, France)

  23. Shian Yu (Department of Hepatobiliary Surgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, China)

  24. Simone Vani (Hepatobiliary Surgery Unit, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Catholic University of the Sacred Heart, Rome, Italy)

  25. Francesco Ardito, (Hepatobiliary Surgery Unit, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Catholic University of the Sacred Heart, Rome, Italy)

  26. Ugo Giustizieri (HPB Surgery, Hepatology and Liver Transplantation, Fondazione IRCCS Istituto Nazionale Tumori di Milano, Milan, Italy)

  27. Davide Citterio (HPB Surgery, Hepatology and Liver Transplantation, Fondazione IRCCS Istituto Nazionale Tumori di Milano, Milan, Italy)

  28. Federico Mocchegiani (HPB Surgery and Transplantation Unit, United Hospital of Ancona, Department of Experimental and Clinical Medicine Polytechnic University of Marche)

  29. Marco Colasanti (Division of General Surgery and Liver Transplantation, San Camillo Forlanini Hospital, Rome, Italy)

  30. Giammauro Berardi (Division of General Surgery and Liver Transplantation, San Camillo Forlanini Hospital, Rome, Italy)

  31. Yoelimar Guzmán (General & Digestive Surgery, Hospital Clínic, Barcelona, Spain)

  32. Kevin P. Labadie (Department of Surgery, University of Washington Medical Center. Seattle, USA)

  33. Maria Conticchio (Unit of Hepato-Pancreatc-Biliary Surgery, “F. Miulli” General Regional Hospital, Acquaviva delle Fonti, Bari, Italy)

  34. Epameinondas Dogeas (Department of Surgery, Division of Hepatobiliary and Pancreatic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA)

  35. Emanuele F. Kauffmann (Division of General and Transplant Surgery, University of Pisa, Pisa, Italy)

  36. Mario Giuffrida (Hepatobiliary Surgery Unit, Department of Medicine and Surgery, University of Parma, Parma, Italy)

  37. Daniele Sommacale (Department of Digestive and Hepatobiliary and Pancreatic Surgery, AP-HP, Henri-Mondor Hospital, Creteil, France)

  38. Alexis Laurent, (Department of Digestive and Hepatobiliary and Pancreatic Surgery, AP-HP, Henri-Mondor Hospital, Creteil, France)

  39. Paolo Magistri (HPB Surgery and Liver Transplant Unit, University of Modena and Reggio Emilia, Modena, Italy)

  40. Kohei Mishima (Center for Advanced Treatment of Hepatobiliary and Pancreatic Diseases, Ageo Central General Hospital, Saitama, Japan)

  41. Moritz Schmelzle, (Department of Surgery, Campus Charité Mitte and Campus Virchow-Klinikum, Charité-Universitätsmedizin, Corporate Member of Freie Universität Berlin, and Berlin Institute of Health, Berlin, Germany)

  42. Felix Krenzien (Department of Surgery, Campus Charité Mitte and Campus Virchow-Klinikum, Charité-Universitätsmedizin, Corporate Member of Freie Universität Berlin, and Berlin Institute of Health, Berlin, Germany)

  43. Prashant Kadam (Department of Hepatopancreatobiliary and Liver Transplant Surgery, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom)

  44. Chung-Ngai Tang (Department of Surgery, Pamela Youde Nethersole Eastern Hospital, Hong Kong SAR, China)

  45. Jacob Ghotbi (The Intervention Centre and Department of HPB Surgery, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway)

  46. Åsmund Avdem Fretland (The Intervention Centre and Department of HPB Surgery, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway)

  47. Fabio Forchino (Department of General and Oncological Surgery. Mauriziano Hospital, Turin, Italy)

  48. Bernardo Dalla Valle (General and Hepatobiliary Surgery, Department of Surgery, Dentistry, Gynecology and Pediatrics University of Verona, GB Rossi Hospital, Verona, Italy)

  49. Alessandro Mazzotta (Department of Digestive, Oncologic and Metabolic Surgery, Institute Mutualiste Montsouris, Universite Paris Descartes, Paris, France)

  50. Phan Phuoc Nghia (Department of Hepatopancreatobiliary Surgery, University Medical Center, University of Medicine and Pharmacy, Ho Chi Minh City, Vietnam)

  51. Francois Cauchy (Department of HPB Surgery and Liver Transplantation, Beaujon Hospital, Clichy, France)

  52. Qu Liu, (Faculty of Hepatopancreatobiliary Surgery, the First Medical Center of Chinese People’s Liberation Army (PLA) General Hospital, Beijing, China)

  53. Yoshikuni Kawaguchi (Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan)

Footnotes

Conflicts of interest
  1. Dr Goh BK has received travel grants, honorarium and research grants from Johnson and Johnson, Olympus and Intuitive Surgery.
  2. Dr Marino MV is a consultant for CAVA robotics LLC.
  3. Johann Pratschke reports a research grant from Intuitive Surgical Deutschland GmbH and personal fees or non-financial support from Johnson & Johnson, Medtronic, AFS Medical, Astellas, CHG Meridian, Chiesi, Falk Foundation, La Fource Group, Merck, Neovii, NOGGO, pharma-consult Peterson, and Promedicis.
  4. Moritz Schmelzle reports personal fees or other support outside of the submitted work from Merck, Bayer, ERBE, Amgen, Johnson & Johnson, Takeda, Olympus, Medtronic, Intuitive.
  5. Fernando Rotellar reports speaker fees and support outside the submitted work from Integra, Medtronic, Olympus, Corza, Sirtex and Johnson & Johnson.
  6. Roberto Troisi reports speaker fees and support outside the submitted work from Integra, Stryker, Medtronic, Medistim, MSD.

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Supplementary Materials

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