Literature DB >> 32309329

Preoperative three-dimensional versus two-dimensional evaluation in assessment of patients undergoing major liver resection for hepatocellular carcinoma: a propensity score matching study.

Pengpeng Li1, Mengchao Wang1, Yuan Yang1, Hui Liu1, Zeya Pan1, Beige Jiang1, Wan Yee Lau2, Gang Huang1, Weiping Zhou1.   

Abstract

BACKGROUND: Compared with 2D evaluation, 3D evaluation possesses the virtues of displaying spatial anatomy of intrahepatic blood vessels and its relations to tumors, and enabling calculation of liver volumes, thus facilitating preoperative surgery planning.
METHODS: The objective of this study is to study whether preoperative 3D (three-dimensional) evaluation produced better long-term overall survival (OS) outcomes compared to the traditional 2D (two-dimensional) evaluation in patients who underwent major hepatectomy for hepatocellular carcinoma (HCC). This retrospective study matched patients who underwent preoperative 2D evaluation with those who underwent preoperative 3D evaluation in a 1:1 ratio using propensity score matching. The primary endpoints were long-term survival outcomes in the two groups after major hepatectomy for HCC.
RESULTS: Of the 248 patients in each of the 2 matched groups, the baseline characteristics were comparable. The median follow-up for all patients was 36 months (range, 0-40 months). The 3-year OS of patients in the PSM cohort was 38.5%. Compared with the 2D Group, patients in the 3D Group had a better OS rate (HR 0.722, 95% CI: 0.556-0.938, P=0.015) and disease-free survival (DFS) rate (HR 0.741, 95% CI: 0.590-0.929, P=0.009). The 3-year OS and DFS rate for the 3D Group versus the 2D group were 58.9% and 44.0% versus 47.4% and 33.1%, respectively.
CONCLUSIONS: 3D preoperative evaluation resulted in significantly better intermediate-term (3-year) overall survival rate than the traditional 2D evaluation. 2020 Annals of Translational Medicine. All rights reserved.

Entities:  

Keywords:  Three-dimensional evaluation; hepatocellular carcinoma (HCC); major liver resection; overall survival

Year:  2020        PMID: 32309329      PMCID: PMC7154448          DOI: 10.21037/atm.2020.01.106

Source DB:  PubMed          Journal:  Ann Transl Med        ISSN: 2305-5839


Introductions

Hepatocellular carcinoma (HCC) is the dominating type of liver cancer in many countries, accounting for approximately 80% of all primary liver cancers (1). Hepatectomy is the most commonly used and effective treatment aiming at cure (2). Accurate preoperative evaluation is of great importance before liver resection to improve safety and effectiveness. For patients with large tumors or with tumors adjacent to major intrahepatic vessels, major liver resections, defined as resecting more than three Couinaud liver segments, have to be performed to eradicate tumors. Two-dimensional (2D) evaluation, which is carried out by the 2D images produced by either CT or MRI, has long been used in our institution. The limitations of these 2D images are inadequate exhibition of stereoscopic relationships between major intrahepatic blood vessels and tumors, and inability to precisely calculate the different liver volumes in the planning for operations (3,4). Three-dimensional (3D) evaluation allows these assessments to be done accurately, making this technology rapidly accepted by hepatobiliary surgeons in many institutions (5-8). Most researches on 3D evaluation focused on its ability to stereoscopically exhibit anatomy, accurately estimate liver volumes, and precisely determine surgical resection margins, thus tremendously help in preoperative surgical planning (9-12). Few studies described the long-term survival outcomes resulted from the benefits obtained in 3D evaluation. The objective of this study was to determine whether preoperative 3D evaluation produced better long-term overall survival outcomes compared to the traditional preoperative 2D evaluation.

Methods

Study design

A retrospective study was conducted on patients who underwent major liver resections for hepatocellular carcinoma (HCC) and were preoperatively assessed by either 2D or 3D evaluation at the Eastern Hepatobiliary Surgery Hospital from January 2012 to December 2018. Patients who underwent preoperative 2D evaluation was matched with patients who underwent preoperative 3D evaluation in a 1:1 ratio using propensity score matching.

Patients

The inclusion criteria were: (I) patients with histopathologically confirmed HCC; (II) patients who underwent either preoperative 2D or 3D evaluation; (III) Child-Pugh score A and baseline serum alanine aminotransferase (ALT) level <2 times the upper limit of normal; and (IV) patients underwent major liver resection defined as resection of more than three Couinaud liver segments. The exclusion criteria were: (I) patients who had liver tumor other than HCC; (II) patients who had a history of other anti-cancer therapy; (III) patients who had undergone liver resection previously; and (IV) patients had severe dysfunction of heart, lung, kidney or other organs.

Preoperative evaluations

2D evaluation was performed with the traditional 2D images of CT or MRI. The extent of liver resection and the plane of liver transection were determined by experienced surgeons for radical resection of tumor with a surgical resection margin of at least 1 cm. As far as possible, an anatomical resection based on liver segment/sectors/hemilivers was done. A non-anatomical wedge resection was only carried out for tumors near important intrahepatic blood vessel which could not be cut off. The patients were not included in this study as these liver resections were not major resections. Vascular resection followed by reconstruction was carried out if clinically indicated. The 3D-evaluation took advantage of the 3D visualization model, which has the abilities to 3-dimensionally exhibit intrahepatic anatomy, precisely work out the liver volumes of the future resected specimen and the remnant liver, separate the liver into 8 Couinaud segments, and exactly determine the liver segments where the tumor is located. As a consequence, this model can be used to plan liver resection. Major vascular structures along the planned transection plane can be shown clearly in this model (the Three-dimensional Visualization Software, Shenzhen XuDong Digital Medical Imaging Technology Co., Ltd or the IQQA-Liver EDDA Technology Inc, Princeton, NJ). In the simulation liver resection model, a transection plane was determined by including the tumor with an adequate resection margin in the planned resected specimen. The vascular inflow and outflow to the planned remnant liver were preserved intact. The estimated remnant liver volume by the 3D visualization model should meet the criteria for liver resection, which was pre-defined as a FLR/SLV ratio >40% (FLR/BW >0.8%) in patients with a background of fibrosis or cirrhosis (13,14), and a ratio >30% (FLR/BW >0.5%) in patients with a normal liver (15,16). If the tumor was close to the middle hepatic vein, extended left/right hepatectomy to include the middle hepatic vein would be performed in patients whose FLR met the predefined requirements.

Operation procedures

All surgeries were open hepatectomy following the previously reported techniques (17). Intraoperative ultrasound was routinely used to determine the number and location of tumor, and to determine the relationship between tumors and major vessels. The surgery plan would be changed if additional tumors, or severe liver cirrhosis were found during the operations. Liver parenchymal transection was performed using an ultrasonic scalpel (Harmonic Scalpel, HS; Ethicon Endosurgery, USA) or Ligasure (LigaSure, Covidien, USA).

Data collection and follow-up

Routine preoperatively collected baseline data included intravenous contrast-enhanced CT scan of liver, 3D visualization reconstruction (if carried out) using the Three-dimensional Visualization Software (Shenzhen XuDong Digital Medical Imaging Technology Co., Ltd or the IQQA-Liver EDDA Technology Inc, Princeton, NJ), liver function tests, renal function tests, coagulation profile, complete blood count, chest X-ray, electrocardiogram, lung function tests, gastroscopy, ultrasonic examination of liver and spleen, hepatitis B virus/hepatitis C virus serology tests and tumor markers (AFP, CEA, CA19-9). Echocardiography was carried out in patients older than 60 years. Intraoperative data collected in this study included operative procedures, duration of operation, time of hepatic inflow occlusion, intraoperative blood loss and volume of blood transfusion. Postoperative data included liver function tests, renal function tests, coagulation profile and complete blood count on postoperative day 1, 3, 5 and 7, and ultrasonic examination of liver, portal vein, hepatic vein, X-ray chest on postoperative day 4, postoperative complications (postoperative mortality and morbidity rates) and surgical resection margins. Patients were regularly followed-up in the HCC Clinic. Patients who failed to attend the scheduled follow-up appointments were contacted by a research nurse. Morbidity was classified according to the Clavien-Dindo classification (18). Minor complications were defined as complication less than grade IIIa. Severe complications were defined as grade IIIb or greater. Post-hepatectomy liver failure (PHLF) was defined and graded using the “ISGLS” criteria (19). Renal failure was defined as an increase of creatinine within 48 hours after surgery to more than 1.4 times of the preoperative level (20). The degrees of liver fibrosis was evaluated using the METAVIR scoring (21). Surgical resection margin was defined as the shortest macroscopic distance from the edge of tumor to the resection plane. R0 resection was defined as no gross tumor left after resection with non-existence of tumor cells at the plane of transection on microscopic examination. Patients were followed-up once every month after surgery and re-examined with enhanced CT or MRI, liver function tests, AFP, HBV-DNA and chest radiography once every three months. The primary endpoint was long-term survival outcomes in the 2D and 3D evaluation groups. The secondary endpoints were: (I) Intraoperative data, and (II) postoperative mortality and morbidity rates.

Statistical analysis

To limit selection bias arising from lack of randomization, Propensity Score Matching (PSM) was performed to match patients who underwent preoperative 2D evaluation with patients who underwent preoperative 3D evaluation in a 1:1 ratio using the nearest neighbor matching method with a 0.2 caliper width based on the following variables: age, sex, BMI, ASA score, infection status of HBV, HBV-DNA levels, AFP level, platelet count, maximum tumor diameter, tumor number, total bilirubin (TBIL) level, albumin (ALB) level, Alanine transaminase (ALT) level, positivity for microvascular invasion (MVI) and cirrhosis status. Continuous data were expressed as median (range), and categorical data as a count or ratio. The Mann-Whitney U test was used as the non-parametric test for two independent samples. Categorical variables were tested by the Pearson's chi-square or Fisher exact tests. The Kaplan-Meier method was used to estimate overall survival (OS). OS was defined as the time from first treatment to death of all causes. The Log-rank test was used to compare survival outcomes between the two groups. The Cox regressions were carried out to examine the association between OS and demographic and other covariates. All computations relied on the standard software (SPSS Statistics v24; IBM, Chicago, IL). A 2-sided P<0.05 was considered as statistically significant.

Results

From January 2012 to December 2018, 748 patients with HCC underwent major liver resection in our department. Thirty-six patients were excluded because of missing data. Therefore, 712 patients (the 2D group: n=365; the 3D group: n=347) were eligible for PSM at a 1:1 ratio. After PSM, 248 patients were matched and included in each of the 2 groups.

Baseline characteristics

The baseline characteristics of the patients before and after PSM in the 2 groups are shown in . In the crude cohorts, the 2D group exhibited a larger maximum tumor diameter (9.5 vs. 8.4 cm, P=0.025) and a higher proportion of multiple tumors (37.8% vs. 29.4%, P=0.022) compared with the 3D group. In the PSM cohorts, there were no significant differences in the baseline characteristics between the two groups.
Table 1

Baseline characteristics of patients in the two groups before and after propensity score matching

CharacteristicsCrude cohortPSM cohort
2D (n=365)3D (n=347)P value2D (n=248)3D (n=248)P value
Age (years)50 [19–81]52 [17–83]0.66251 [19–77]52 [17–83]0.497
Sex, male, n (%)302 (82.74)274 (78.96)0.200205 (82.66)196 (79.03)0.304
BMI23.3 (19.6–31.0)23.5 (19.6–31.0)0.18023.15 (19.9–30.2)23.5 (19.6–31.0)0.125
ASA score ≥2, n (%)28 (7.67)24 (6.92)0.69923 (9.27)19 (7.66)0.519
Hbs Ag+, n (%)325 (89.04)309 (89.05)0.997230 (92.7)225 (90.73)0.415
HBV-DNA >1,000, n (%)154 (42.19)149 (42.94)0.840102 (41.13)111 (44.76)0.414
ALT (UI/L)26 [5–80]27 [5–79]0.96224 [5–78]27 [5–79]0.477
ALB38.9 (34.1–49.5)38.9 (33–50.8)0.25838.6 (34.1–48.8)38.4 (33.0–50.8)0.340
TBIL16.5 (4.5–33.8)16.0 (4.2–33.6)0.93415.7 (4.5–33.8)15.05 (5.8–29.9)0.472
Platelet count, (109/L)176 [51–497]168 [45–473]0.147176.5 [51–497]168 [61–461]0.216
Liver cirrhosis n (%)109 (29.86)90 (25.94)0.24366 (26.61)58 (23.39)0.407
AFP >20 ug/L, n (%)210 (57.53)187 (53.89)0.328141 (56.85)131 (52.82)0.367
Maximum tumor size (cm)9.5 (2.7–24.4)8.4 (2.4–25)0.0259.15 (3.1–24.4)9.30 (3.8–25)0.707
Tumor number (multiple) n (%)138 (37.81)102 (29.39)0.02279 (31.85)65 (26.21)0.166
MVI, n (%)171 (46.85)163 (46.97)0.973113 (45.56)121 (48.79)0.472
Follow up time36 (0–40)38 (0–40)
Tumor type, n (%)
   HCC365 (100.0)347 (100.0)248 (100.0)248 (100.0)
Child-Pugh stage, n (%)
   A365 (100.0)347 (100.0)248 (100.0)248 (100.0)
   B00
   C00
BCLC stage, n (%)
   A201 (55.07)207 (59.65)0.216152 (61.29)158 (63.71)0.578
   B114 (31.23)86 (24.78)0.05666 (26.61)56 (22.58)0.253
   C50 (13.70)54 (15.56)0.48230 (12.10)34 (13.71)0.500

BMI, body mass index; ASA score, The American Society of Anaesthesiologists physical status classification system; TBIL, total bilirubin; ALB, serum albumin; ALT, alanine transaminase; MVI, microvascular invasion; HCC, hepatocellular carcinoma; BCLC stage, Barcelona Clinic Liver Cancer (BCLC) classification.

BMI, body mass index; ASA score, The American Society of Anaesthesiologists physical status classification system; TBIL, total bilirubin; ALB, serum albumin; ALT, alanine transaminase; MVI, microvascular invasion; HCC, hepatocellular carcinoma; BCLC stage, Barcelona Clinic Liver Cancer (BCLC) classification.

Intraoperative findings

The intraoperative data of the two groups of patients after PSM are listed in . Significant differences in the number of patients who required intraoperative red blood cells transfusion (P=0.004), and in the volume of intraoperative blood loss (P=0.018) were found between the two groups. Anatomical liver resection was carried out in 206 of 248 patients (83.1%) in the 3D Group compared with only 75 of 248 patients (30.2%) in the 2D Group (P<0.001). The median resection margin of the 3D Group was significantly better than the 2D Group, (median 0.7, range, 0–1.8 cm versus median 0.3, range, 0–1 cm, respectively, P<0.001).
Table 2

Intraoperative clinical data of patients in the two groups after propensity score matching

CharacteristicsResultsP values
2D Group (n=248)3D Group (n=248)
Operating time (min)270 [180–420]260 [150–360]0.461
Pringle’s maneuver, n (%)237 (95.6)229 (92.3)0.123
   Pringle’s maneuver duration, (min)32 (0–70)32 (0–60)0.393
Number of blood transfusion, n (%)92 (37.1)62 (25.0)0.004
   Volume of red blood cells transfusion (units)0 (0–29)0 (0–16)0.007
Intraoperative bleeding volume (mL)500 [200–8,600]400 [200–2,800]0.018
Type of hepatectomy, n (%)
   Anatomical resection75 (30.2)206 (83.1)<0.001
   Non-anatomical resection173 (69.8)42 (16.9)
Resection margins (cm)0.3 (0–1.0)0.7 (0–1.8)<0.001

Postoperative results

The postoperative complications after PSM are shown in . Significant differences between the two groups existed in the incidences of postoperative Grade III complications: 30 of 248 patients, or 12.1% in the 3D group, and 50 of 248 patients, or 20.1% in the 2D group (P=0.015). The details of the Grade III complications are shown in . All the postoperative complications responded well to conservative treatment, percutaneous drainage or reoperation. Liver failure (≥ Grade C) happened more frequently but insignificantly in the 2D Group (2.4%) when compared with the 3D Group (0.4%) (P=0.122). Three patients in the 2D Group but no patient in the 3D group died of PHLF within 90 days of surgery. The causes of 90-day mortality are shown in .
Table 3

Postoperative clinical data of patients in the two groups after propensity score matching

CharacteristicsResultsP values
2D Group (n=248)3D Group (n=248)
Morbidity, n (%)131 (52.8)120 (48.4)0.323
Postoperative complications, n (%)
   Grade I35 (14.1)28 (11.3)0.345
   Grade II98 (39.5)88 (35.5)0.354
   Grade III50 (20.1)30 (12.1)0.015
      Bile leakage2710
      Abdominal hemorrhage51
      Pleural effusion3533
      Biliary obstruction40
      Intra-abdominal infection31
      Disruption of wound11
      Atelectasis32
   Grade IV7 (2.8)5 (2.0)0.559
   Grade V3 (1.2)00.248
Liver failure (≥ Grade C), n (%)6 (2.4)1 (0.4)0.122
Death in 90 days, n (%)3 (1.2)00.248
   Liver failure2
   Portal vein thrombosis1

Postoperative complications were classified by Clavin-Dindo classification. Liver failure was defined using the “ISGLS” criteria.

Postoperative complications were classified by Clavin-Dindo classification. Liver failure was defined using the “ISGLS” criteria. The median follow-up for all patients was 36 months (range, 0–40 months). And the median follow-up for patients in PSM cohort was 38 months (range, 0–40). The 3-year OS of patients in the crude cohorts was 53·8%. Patients in the 3D Group exhibited better overall survival (OS) rate than patients in the 2D Group (HR =0.666, 95% CI: 0.533–0.831, P<0.001). The 3-year OS rate of the 3D and 2D groups were 61.0% and 46.9%, respectively (). Cox regression analyses showed that evaluation using 3D (HR =0.727, 95% CI: 0.578–0.914, P=0.006), small tumor (HR =1.111, 95% CI: 1.081–1.141, P<0.001), solitary tumor (HR =1.473, 95% CI: 1.171–1.853, P=0.001), MVI negativity (HR =1.795, 95% CI: 1.416–2.277, P<0.001), AFP negativity (HR =1.385, 95% CI: 1.092–1.757, P=0.007) and absence of severe liver fibrosis (HR =1.399, 95% CI: 1.105–1.772, P=0.005) were significant good risk factors of OS (). Compared with patients in the 2D Group, patients in the 3D Group also had significantly better disease-free survival (DFS) rate (HR =0.716, 95% CI: 0.591–0.866, P=0.001) (). The 3-year DFS rate in the 3D and 2D groups of patients were 45.1% versus 32.9%. The 3-year OS of the patients in the PSM cohorts was 38·5%. Patients in the 3D Group presented with better overall survival (OS) rate than patients in the 2D Group (HR =0.722, 95% CI: 0.556–0.938, P=0.015). The 3-year OS for all the patients in the two groups was 53.2%. The 3-year OS rate of the 3D and 2D groups were 58.9% and 47.4% (). Cox regression analyses showed that evaluation using 3D (HR =0.652, 95% CI: 0.497–0.855, P=0.002), small tumor (HR =1.084, 95% CI: 1.047–1.123, P<0.001), solitary tumor (HR =2.108, 95% CI: 1.602–2.773, P<0.001), MVI negativity (HR =2.226, 95% CI: 1.641–3.020, P<0.001), AFP negativity (HR =1.466, 95% CI: 1.102–1.951, P=0.009) and absence of severe liver fibrosis (HR =1.396, 95% CI: 1.041–1.872, P=0.026) were significant good risk factors of OS (). Compared with patients in the 2D Group, patients in the 3D Group also had significantly better disease-free survival (DFS) rate (HR =0.741, 95% CI: 0.590–0.929, P=0.009) (). The 3-year DFS rate of patients was 44.0% in the 3D Group versus 33.1% in the 2D Group.
Figure 1

Comparison of the overall survivals (OS) between all the patients in two groups of crude cohorts. Patients in the 3D Group presented with better OS rate than patients in the 2D Group (P<0.001) (A). Comparison of the disease-free survivals (DFS) between all the patients in two groups of crude cohorts. Patients in the 3D Group also had significantly better DFS rate (P=0.001) (B).

Table 4

Uni- and multi-variate analyses for the overall survival results in the crude cohort

FactorsCrude cohort
Univariate analysisMultivariate analysis
HR (95% CI)PHR (95% CI)P
Preoperative evaluation method (3D)0.666 (0.533–0.831)<0.0010.727 (0.578–0.914)0.006
Age0.985 (0.975–0.995)0.004
Sex1.286 (0.960–1.723)0.092
ASA score ≥20.959 (0.627–1.465)0.846
Tumor diameter1.127 (1.102–1.152)<0.0011.111 (1.081–1.141)<0.001
Multiple tumors1.928 (1.548–2.402)<0.0011.473 (1.171–1.853)0.001
AFP level (>20 ug/L)1.770 (1.407–2.228)<0.0011.385 (1.092–1.757)0.007
HBV-DNA (>1,000 copies/mL)1.278 (1.027–1.590)0.028
Platelet count1.001 (0.999–1.002)0.340
MVI (+)2.516 (2.008–3.153)<0.0011.795 (1.416–2.277)<0.001
Operation time1.002 (0.999–1.004)0.145
Intraoperative bleeding volume1.000 (1.000–1.000)0.034
Red blood cells transfusion volume1.049 (1.010–1.089)0.013
Liver cirrhosis (+)1.467 (1.163–1.850)0.0011.399 (1.105–1.772)0.005
HBsAg (+)1.578 (1.049–2.373)0.029
ALB0.994 (0.964–1.026)0.720
TBIL0.992 (0.977–1.008)0.324
ALT1.000 (0.994–1.006)0.921

Those variables found significant at P<0.2 in univariable analyses were entered into multivariable Cox-regression analyses.

Figure 2

Comparison of the overall survivals (OS) between all the patients in two groups of PSM cohorts. Patients in the 3D Group presented with better OS rate than patients in the 2D Group (P=0.015) (A). Comparison of the disease-free survivals (DFS) between all the patients in two groups of PSM cohorts. Patients in the 3D Group also had significantly better DFS rate (P=0.009) (B).

Table 5

Uni- and multi-variate analyses for the overall survival results in the PSM cohort

FactorsPSM cohort
Univariate analysisMultivariate analysis
HR (95% CI)PHR (95% CI)P
Preoperative evaluation method (3D)0.722 (0.556–0.938)0.0150.652 (0.497–0.855)0.002
Age0.992 (0.980–1.003)0.165
Sex1.285 (0.910–1.813)0.154
ASA score ≥20.940 (0.587–1.503)0.795
Tumor diameter1.123 (1.093–1.154)<0.0011.084 (1.047–1.123)<0.001
Multiple tumors3.108 (2.392–4.038)<0.0012.108 (1.602–2.773)<0.001
AFP level (>20 ug/L)1.848 (1.408–2.425)<0.0011.466 (1.102–1.951)0.009
HBV-DNA (>1,000 copies/mL)1.266 (0.976–1.641)0.075
Platelet count1.001 (0.999–1.003)0.202
MVI (+)3.341 (2.536–4.401)<0.0012.226 (1.641–3.020)<0.001
Operation time1.002 (0.998–1.005)0.368
Intraoperative bleeding volume1.000 (1.000–1.000)0.008
Red blood cells transfusion volume1.076 (1.030–1.124)0.001
Liver cirrhosis (+)1.544 (1.163–2.050)0.0031.396 (1.041–1.872)0.026
HBsAg (+)3.192 (1.576–6.463)0.001
ALB0.978 (0.937–1.019)0.288
TBIL1.000 (0.980–1.021)0.964
ALT1.003 (0.995–1.010)0.474

Those variables found significant at P<0.2 in univariable analyses were entered into multivariable Cox-regression analyses.

Comparison of the overall survivals (OS) between all the patients in two groups of crude cohorts. Patients in the 3D Group presented with better OS rate than patients in the 2D Group (P<0.001) (A). Comparison of the disease-free survivals (DFS) between all the patients in two groups of crude cohorts. Patients in the 3D Group also had significantly better DFS rate (P=0.001) (B). Those variables found significant at P<0.2 in univariable analyses were entered into multivariable Cox-regression analyses. Comparison of the overall survivals (OS) between all the patients in two groups of PSM cohorts. Patients in the 3D Group presented with better OS rate than patients in the 2D Group (P=0.015) (A). Comparison of the disease-free survivals (DFS) between all the patients in two groups of PSM cohorts. Patients in the 3D Group also had significantly better DFS rate (P=0.009) (B). Those variables found significant at P<0.2 in univariable analyses were entered into multivariable Cox-regression analyses.

Discussion

In our center before August 2014, traditional 2D evaluation was used to evaluate patients before operations and to develop operation plans. In August 2014, the 3D visualization system was introduced into our center. Since then, the number of patients who underwent 3D evaluation and preoperative planning has gradually been increasing. Now, most complex liver operations are evaluated by 3D visualization before operations. Studies have shown that the 3D visualization technology can facilitate planning and implementation of liver resections, especially in anatomic hepatectomy (6). In our study, 83.1% of patients in the 3D evaluation group underwent anatomic hepatectomy, which is significantly higher than the 30.2% of patients in the 2D evaluation group. There are two possible explanations: (I) preoperative 3D evaluation can accurately measure the distance between tumors and major intrahepatic vessels, thus providing better planning to the extent of liver resection and the plane of liver transection; (II) by using 3D, the residual liver volumes can be measured accurately to quantitatively assess the risk of postoperative liver failure for the planned operations. In our study, there were less intraoperative bleeding, less blood transfusion and fewer patients requiring blood transfusion in the 3D evaluation group. The 3D visualization model clearly showed the 3D anatomical structures of the major intrahepatic vessels, anatomic variations, and the relationship between intrahepatic vessels with tumors before the operations. It then enabled surgeons to design a relatively avascular liver plane to transect, to have a good preoperative understanding of which intrahepatic vessels were to be transected, which vessels should be protected and which vessels could be sacrificed during the operations, thus avoiding accidental vascular injuries during operations. With advances in technology and techniques in liver surgery, and with accumulation of surgical experience, the reported post-hepatectomy morbidity (47.7%) and mortality (4.7%) rates are still high (22,23). Liver failure is the most dreaded post-hepatectomy complication and the leading cause of death (19,24-26). The main causes of post-hepatectomy liver failure in the 2D imaging era are the difficulties in preoperative identification of intrahepatic vascular anomalies, and the accurate assessment of the volume of future liver remnant. Injury of intrahepatic vascular anomalies during operation can lead to ischemic necrosis or congestion of liver parenchyma, causing postoperative liver failure. Many studies have shown a significant correlation between the volume of future liver remnant with postoperative complications (27-29). The 3D visualization technology can accurately assess the extent of hepatectomy before operation, preserve adequate residual liver volumes, avoid damage to important intrahepatic vessels, ensure complete blood inflow and outflow to liver remnants, thus significantly reducing the chance of hepatic parenchymal necrosis, ischemia or congestion after hepatectomy, and the incidences of liver failure and death due to inadequate residual liver volume. The preoperative 3D visualization assessment leads to more anatomic resection and helps surgeons to design more reasonable liver transection and relatively less vascular planes to go through. All these contribute to less intraoperative bleeding and postoperative bile leak. As a consequence, the incidences of major complications (> Grade III) and post-hepatectomy hepatic failure for patients in the 3D Group were significantly lower than the 2D Group. Three patients died within 90 days after surgery in the 2D Group, while there were no deaths in the 3D Group. With heterogeneous distribution of liver function in livers (30,31), using liver volumetry alone is not enough to assess liver functional reserve of patients. Functional assessment is effective in supplementing liver volume evaluation (32). The (99m)Tc-GSA scintigraphy SPECT-CT fusion system can estimate correct functional liver volume and it is useful in comparison with conventional CT volumetry (33). Anatomic hepatectomy with adequate resection margins are important factors relating to better long-term survival outcomes of patients (34-38). Our study supported that 3D evaluation was better than the traditional 2D evaluation in the 3-year overall survival rate of patients. This study has several limitations. First, although this study used PSM to minimize the unbalanced baseline characteristics of patients in the two study groups, inherent biases can still occur in this retrospective study. Second, while most of the 2D group of patients were treated from January 2012 to August 2014, most of the 3D group of patients were treated from August 2014 to December 2018. The increase in experience in liver resection can explain at least partly the better treatment outcomes in the 3D evaluation group. Third, some preoperative examinations could not even be performed in the two groups, e.g., ICG-R15 and Fibro-scan. This can result in our inability to use some accurate indicators to assess the state of liver function and fibrosis in selecting variables to generate the propensity score model. Fourth, in this study, only patients with hepatocellular carcinoma who underwent major liver resections were included. Therefore, the significance of preoperative 3D evaluation on patients with less extensive hepatectomy was not studied.
  38 in total

1.  An algorithm for the grading of activity in chronic hepatitis C. The METAVIR Cooperative Study Group.

Authors:  P Bedossa; T Poynard
Journal:  Hepatology       Date:  1996-08       Impact factor: 17.425

2.  Prognostic impact of anatomic resection for hepatocellular carcinoma.

Authors:  Kiyoshi Hasegawa; Norihiro Kokudo; Hiroshi Imamura; Yutaka Matsuyama; Taku Aoki; Masami Minagawa; Keiji Sano; Yasuhiko Sugawara; Tadatoshi Takayama; Masatoshi Makuuchi
Journal:  Ann Surg       Date:  2005-08       Impact factor: 12.969

3.  Portal vein embolization before major hepatectomy and its effects on regeneration, resectability and outcome.

Authors:  D Ribero; E K Abdalla; D C Madoff; M Donadon; E M Loyer; J-N Vauthey
Journal:  Br J Surg       Date:  2007-11       Impact factor: 6.939

4.  Acute kidney injury.

Authors:  Norbert Lameire; Wim Van Biesen; Raymond Vanholder
Journal:  Lancet       Date:  2008-11-29       Impact factor: 79.321

5.  Impact of three-dimensional reconstruction technique in the operation planning of centrally located hepatocellular carcinoma.

Authors:  Chi-hua Fang; Hai-su Tao; Jian Yang; Zhao-shan Fang; Wei Cai; Jun Liu; Ying-fang Fan
Journal:  J Am Coll Surg       Date:  2014-10-15       Impact factor: 6.113

Review 6.  Global Epidemiology of Hepatocellular Carcinoma (HCC Epidemiology).

Authors:  Aysegul Ozakyol
Journal:  J Gastrointest Cancer       Date:  2017-09

7.  The inhomogeneous distribution of liver function: possible impact on the prediction of post-operative remnant liver function.

Authors:  Henrik Nilsson; Silja Karlgren; Lennart Blomqvist; Eduard Jonas
Journal:  HPB (Oxford)       Date:  2014-10-09       Impact factor: 3.647

Review 8.  Current Technical Issues for Surgery of Primary Liver Cancer.

Authors:  Yoshikuni Kawaguchi; Goro Honda; Itaru Endo; Daniel Cherqui; Norihiro Kokudo
Journal:  Liver Cancer       Date:  2016-11-29       Impact factor: 11.740

9.  The value of residual liver volume as a predictor of hepatic dysfunction and infection after major liver resection.

Authors:  M J Schindl; D N Redhead; K C H Fearon; O J Garden; S J Wigmore
Journal:  Gut       Date:  2005-02       Impact factor: 23.059

Review 10.  Liver failure after partial hepatic resection: definition, pathophysiology, risk factors and treatment.

Authors:  Maartje A J van den Broek; Steven W M Olde Damink; Cornelis H C Dejong; Hauke Lang; Massimo Malagó; Rajiv Jalan; Fuat H Saner
Journal:  Liver Int       Date:  2008-07       Impact factor: 5.828

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  4 in total

1.  One- versus two-stage partial hepatectomy for large resectable solitary hepatocellular carcinomas determined preoperatively to have a narrow resection margin: a propensity score matching analysis.

Authors:  Yao Li; Peng-Peng Li; Da-Peng Sun; Jun-Sheng Ni; Wan Yee Lau; Gang Huang; Wei-Ping Zhou; Hui Liu; Ze-Ya Pan; Yuan Yang; Ling-Hao Zhao
Journal:  Hepatobiliary Surg Nutr       Date:  2022-10       Impact factor: 8.265

2.  Laparoscopic right hemihepatectomy following a novel optimized portal vein embolization: a video case report.

Authors:  Lei Liu; Wenbin Ding; Xue Liu; Weiping Zhou; Shengxian Yuan
Journal:  BMC Gastroenterol       Date:  2022-06-03       Impact factor: 2.847

3.  Application value of mixed reality in hepatectomy for hepatocellular carcinoma.

Authors:  Liu-Yang Zhu; Jian-Cun Hou; Long Yang; Zi-Rong Liu; Wen Tong; Yi Bai; Ya-Min Zhang
Journal:  World J Gastrointest Surg       Date:  2022-01-27

Review 4.  Augmented Reality and Image-Guided Robotic Liver Surgery.

Authors:  Fabio Giannone; Emanuele Felli; Zineb Cherkaoui; Pietro Mascagni; Patrick Pessaux
Journal:  Cancers (Basel)       Date:  2021-12-14       Impact factor: 6.639

  4 in total

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