Liver failure after hepatectomy: A risk assessment using the pre-hepatectomy shear wave elastography technique

Accepted Manuscript Title: Liver Failure after Hepatectomy: A Risk Assessment Using the Pre-hepatectomy Shear Wave Elastography Technique Author: Hong Han Hao Hu Wen Ping Wang Hong Ding Feng Mao PII: DOI: Reference:

S0720-048X(16)30354-0 http://dx.doi.org/doi:10.1016/j.ejrad.2016.11.006 EURR 7625

To appear in:

European Journal of Radiology

Received date: Revised date: Accepted date:

27-7-2016 1-11-2016 2-11-2016

Please cite this article as: Han Hong, Hu Hao, Wang Wen Ping, Ding Hong, Mao Feng.Liver Failure after Hepatectomy: A Risk Assessment Using the Prehepatectomy Shear Wave Elastography Technique.European Journal of Radiology http://dx.doi.org/10.1016/j.ejrad.2016.11.006 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Liver Failure after Hepatectomy: A Risk Assessment Using the Pre-hepatectomy Shear Wave Elastography Technique

Hong Han1, Hao Hu2, Wen Ping Wang1*, Hong Ding1, Feng Mao1

1Department of Ultrasound, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai 200032, China, 2Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai 200032, China,

*Corresponding Author: Wen Ping Wang, Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China Phone: +8613681975670 E-mail: [email protected]; [email protected];

Abstract Objective: To determine the efficacy of liver stiffness (LS) measurements utilizing the Shear Wave Elastography (SWE) technique for predicting post-hepatectomy liver failure (PHLF) among patients with hepatocellular carcinoma (HCC). Methods: Data from eighty consecutive patients who were undergoing hepatectomy for HCC were prospectively identified and evaluated with preoperative SWE. The SWE was measured with advanced ultrasound equipment (Philips EPIQ7; Philips Healthcare, Seattle, WA, USA). PHLF classification was defined according to the International Study Group of Liver Surgery Recommendations (ISGLS). Results: SWE was successfully performed in 77 patients. According to the ISGLS criteria, PHLF occurred in 35.1% of patients (27 patients), including 2/25 patients with Grade A/B, respectively. Elevated SWE values (P=0.002) and histological cirrhosis (P=0.003) were independent predictors of PHLF according to the multivariate analysis. Patients with SWE values higher than or equal to 6.9 kPa were identified at higher risk of PHLF (area under the curve: 0.843, sensitivity: 77.8% and specificity: 78.0%). Postoperative dynamic course of the median the Model For End-stage Liver Disease (MELD) score showed irregular changes among patients with an SWE >6.9 kPa. Patients with an SWE <6.9 kPa, postoperative dynamic course of the median MELD score gradually decreased. Conclusion: LS measured with SWE is a valid and reliable method for the prediction of PHLF grade A/B among patients with HCC. SWE could become a routine examination for the preoperative evaluation of PHLF.

Keywords: Liver Failure; hepatocellular carcinoma; Shear Wave Elastography

Introduction Post-hepatectomy liver failure (PHLF) occurs most often in patients suffering from hepatocirrhosis with relatively poor liver regeneration ability and impaired functional reservation of the remnant liver tissue after partial liver resection. PHLF is not only the leading cause of mortality but also the leading cause of life-threatening complications linked to surgical treatment (1-3). Additionally, the cost associated with liver failure is more than three times the cost associated with liver resection (4). Due to improvements in preoperative evaluation and surgery management tools, the incidence of serious PHLF related to death has declined. However, mild/moderate liver failure and liver dysfunction after liver surgery are very common. The traditional criterion (50-50 criteria) has gradually limited the requirement for clinical risk stratification for patients with PHLF. As such, the International Study Group of Liver Surgery (ISGLS) proposed a definition and grading of the severity of posthepatectomy liver failure (A/B/C grades). Unfortunately, very few studies have focused on the patient population with mild/moderate PHLF (grades A/B). To accurately predict PHLF, preoperative hepatic functional reserve evaluations have been widely reported and used for patient selection. Simple-to-use liver enzyme tests and clinical grading systems have been acknowledged with some limitations regarding the provision of accurate assessments of postoperative liver functional recovery. The indocyanine green clearance test are widely used to evaluate pre-operative liver reserve function in Asian countries. Unfortunately, this evaluation is expensive and time consuming (5). Further, it has not provided satisfactory

prediction ability between clinical outcome and hepatic histological examination results (6). Other methods have been used to assess the risk of postoperative liver decompensation, including the invasive measurement of the hepatic venous pressure gradient (7-9), liver gadoxetic acid–enhanced magnetic resonance (MR) imaging (10), and measurements of various serum biomarkers for liver fibrosis (11). However, a consensus has not been met regarding the superiority of one of these methods (9,12). Ultrasonic elastography imaging is a noninvasive and reproducible method. Extensive investigations showed that this technology can accurately measure liver stiffness (LS) and distinguish the degree of liver fibrosis and cirrhosis to objectively reflect liver functional reserve (13,14). The Shear Wave Elastography (SWE) technique, which has obtained the approval of the U.S. Food and Drug Administration, is a new, noninvasive, two-dimensional shear wave-based elastography technology for the assessment of liver fibrosis. SWE can be utilized to measure LS in patients with chronic hepatitis. SWE values can accurately assess the degree of liver fibrosis and the grade of necroinflammatory activity in patients with chronic hepatitis (15,16). Currently, the literature regarding the role of LS measurements using the SWE technique to predict PHLF is limited. In this study, we assessed whether LS measured by SWE could accurately predict PHLF grades A/B in patients undergoing hepatectomy for HCC.

Methods This prospective, single-center study was performed from January 2014 until

December 2015. The study was approved by the Hospital Ethics Committee in accordance with the Declaration of Helsinki (Approval No: B2015-063). Written informed consent was obtained from every patient prior to SWE examination. The inclusion criteria were as follows: potentially resectable HCC prepared for hepatectomy; preoperative LS measurement by ultrasonic elasticity imaging scheduled within 1 week; and Child-Pugh A/B liver function. Patients with recurrent tumors before hepatectomy or who had undergone chemotherapy or transarterial chemoembolization treatment between the SWE examination and hepatectomy were excluded. In total, 80 patients were included in the study. Preoperative characteristics, comorbidities, laboratory data (including liver function tests, clinical grading systems, and typical serum biochemical markers for liver fibrosis), radiological data (including computed tomography/MR and Doppler ultrasound), and surgical data were collected for all patients undergoing hepatectomy. All resected specimens were examined histopathologically for the presence of liver fibrosis (stage 1–4). The percentage of steatosis in the surrounding tissues was also evaluated. Preoperative comorbidities were defined as the presence of more than one of the following: respiratory disease (chronic obstructive pulmonary disease), cardiovascular disease (valve disease, ischemic, arrhythmia, or cardiomyopathy), and endocrine disease (diabetes mellitus requiring therapy). Clinical signs of portal hypertension (PH) were defined as the coexistence of splenomegaly, low platelet counts and esophageal varices (17). Major hepatectomy was defined as resection of 4 or more

liver segments. Minor hepatectomy was defined as resection of 3 or less liver segments (18). Serum markers for liver fibrosis included serum hyaluronic acid, laminin and pre-albumin. The Model for End-Stage Liver Disease (MELD) score and the Child-Pugh score were calculated using each formula (19). MELD score is calculated using serum bilirubin, serum creatinine, and International Normalized Ratio (INR) and is given by the formula 9.57*ln (creatinine) + 3.78*ln (total bilirubin) + 11.2*ln (INR) + 6.43.

SWE Examination Protocol The SWE technique was performed using the latest generation Philips ultrasound Elasto system (Philips EPIQ7; Philips Healthcare, Seattle, WA, USA). The SWE examination was performed by two sonographers with 20 years of US examination experience. The examiners were blind to the status of each patient. SWE measurements were performed after at least 6 hours of fasting and after a complete abdominal ultrasound evaluation. The right lobe of the liver was chosen as the test site through the seventh to tenth intercostal space using a convex transducer (C5-1). The operator positioned the probe to locate a 0.5×1.5 cm measurement region of interest, avoiding visible vessels or ducts. The maximum measuring depth of the liver tissue reached 8 cm. The patient was then asked to cease breathing momentarily during the measurement process. LS was expressed in kPa (kilopascals) (Figure 1). Ten sequential measurements were performed in the same location for each patient. For each patient, LS values were accepted if the success rate was higher than 80%.

Liver Surgery Liver surgeons with more than 15 years of experience either performed or assisted all liver resections. Surgery was performed through a right bilateral subcostal incision. If necessary, the incision was extended to the left subcostal region. The surgeons carefully searched the abdominal cavity to determine the extent of local disease, extrahepatic metastases, and peritoneal seeding. The corresponding hepatic pedicle, hepatic vein, and short hepatic veins were ligated and divided. Pringle’s maneuver was applied to occlude the blood inflow to the liver. The cycles were 15 minutes of clamp time followed by 5 minutes of unclamped time. Liver resection was performed by a clamp-crushing method. Drainage was routinely placed in the subphrenic cavity before closure.

Study Endpoints The primary endpoint of the study was to evaluate the relationship between preoperative LS measured by SWE and the development of PHLF. PHLF was defined by the grading system following the ISGLS recommendations, which had a good relationship with postsurgical long-term outcomes according to recent studies (20,21). The severity of liver failure was graded on the basis of its effect on clinical treatment. Grade A requires a substantial regular postoperative course. The clinical treatment of patients with grade B deviates from the regular course, but invasive therapy is not required. The need for invasive treatment defines

grade C. A detailed report of postoperative complications was recorded during the postoperative course and has been presented here.

Statistical Analyses Continuous variables were expressed as medians and ranges, and the values for different subgroups were compared using the unpaired Mann-Whitney test (for comparisons between groups). Categorical variables were expressed as prevalence, and the subgroups were compared using the Fisher’s exact test. Factors significantly associated with PHLF according to the univariate analysis were further evaluated with a multivariate backward logistic regression analysis to determine whether the factors were independent predictors of PHLF. The diagnostic accuracy of the identified risk factors was assessed using receiver operating characteristic (ROC) curve analyses. The area under the curve (AUC), sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios for the SWE cut-off points were calculated and reported. Relationships between the MELD score, SWE and LS values were evaluated using both linear and non-linear regression models. A significance level of 0.05 was applied for all analyses. The statistical analyses were performed using SPSS Version 13.0 software (SPSS, Chicago, IL, USA) and MedCalc for Windows, version 12.5 (MedCalc Software, Ostend, Belgium).

Results

Patient Characteristics Patient baseline characteristics are reported in Table 1. The entire study population had a median age of 59 years (range: 24-91). A large proportion of the study population had a history of chronic hepatitis (89.6%). Twenty-four (31.2%) patients presented with preoperative comorbidities. The median MELD score was 5.8 (range: 4.8-6.5). Seventy-two patients (90.0%) were classified with Child-Pugh class A. Ten patients (12.5%) presented with some degree of PH. The LS measurements were successful in 77 patients. The median SWE value was 6.3 kPa (range: 2.4–22.0). Finally, upon histopathologic examination, 48 patients (60.0%) had F4 fibrosis and 12 (15.6%) had F3 fibrosis. Major post-operative complications included grade A/B liver failure (35.1%), fever with positive blood cultures requiring modification of antibiotics (5.2%) and others (3.9%). PHLF occurred in 35.1% of patients (n=27), including 32.5% of patients (n=25) with Grade A and 2.6% of patients (n=2) with Grade B.

Identification of Risk Factors for the Prediction of Postoperative Liver Failure Table 2 reports the results from the univariate and multivariate logistic regression analyses for identifying the preoperative, intraoperative, and histological factors (continuous and categorical variables) that potentially affect PHLF. A higher serum INR level (P=0.022); higher total serum bilirubin level (P=0.046); higher levels of serum aspartate aminotransferase (P=0.002) and alanine aminotransferase (P=0.018);

higher serum levels of hyaluronic acid (P=0.026), laminin (P=0.006) and pre-albumin (P=0.001); higher SWE values (P=0.001); and the presence of PH (P=0.01) and F4 fibrosis (according to postoperative histopathology analysis) (P=0.001) were significantly associated with PHLF. In the multivariate logistic regression analysis, higher preoperative SWE values (P=0.002) and the presence of cirrhosis (according to postoperative histopathology analysis) (P=0.003) were independent predictors of PHLF.

Receiver Operating Curve Analysis According to the ROC analysis, an SWE value equal to or higher than 6.9 kPa was the best cut-off value for predicting PHLF [AUC=0.843, 95% confidence interval (CI): 0.755–0.931; sensitivity=77.8%; specificity=78.0%; positive predictive value=0.710; negative predictive value=0.891; positive likelihood ratio=4.568; negative likelihood ratio=0.266] (Figure 2). When considering cirrhotic patients only, the ROC curve analysis revealed that the best SWE cut-off value for the prediction of postoperative liver failure was 8.7 kPa (sensitivity: 76.0%, specificity: 87.0% and AUC: 0.847).

Patients Characteristics Stratified by High or Low SWE Values As expected (Table 3), patients with an SWE value ≥6.9 kPa had higher preoperative serum international normalized ratios (INRs) (p=0.023); higher preoperative levels of serum bilirubin (p=0.03), hyaluronic acid (p=0.002), and

laminin (p=0.041); and slightly higher preoperative serum pre-albumin levels (p=0.015). The patients with high SWE values also had higher MELD scores (p=0.018), more clinical signs of PH (p=0.001), less frequent occurrences of histological single HCC nodules, and were more frequently diagnosed with fibrosis stage F4 (p=0.001) than patients with SWE values <6.9 kPa.

There were no postoperative in-hospital mortalities. Thirty-four patients had an eventful postoperative course (44.2%). Among these patients, 27 had an SWE >6.9 kPa (35.1% of the 77 patients). PHLF occurred in 35.1% of patients (n=27), among these，grade A complications occurred in 25 patients: five with an SWE <6.9 kPa (6.5%) and twenty with an SWE >6.9 kPa (26.0%; p<0.001). Two grade B complications occurred in two patients with an SWE >6.9 kPa. Table 4 presents the postoperative complication details.

The Postoperative Dynamic Course of the MELD Score Stratified by High or Low SWE Values Figure 3 depicts the postsurgical dynamic course of the MELD score. As predicted, during the early postsurgical course, the MELD values significantly increased among patients regardless of SWE values. The MELD score gradually declined to pre-surgical levels two weeks after surgical resection. Among patients with an SWE <6.9 kPa, the median MELD score gradually decreased. Among patients with an SWE >6.9 kPa, the median MELD scores had irregular changes.

Discussion Due to improvements in preoperative evaluations, perioperative management and surgical techniques, the incidence of PHLF (50–50 criteria) (22) and severe PHLF-related mortality has decreased during the past few decades. However, mild-moderate liver failure and liver dysfunction (grade A/B; ISGLS Grading System) is very common following liver surgery. Mild-moderate PHLF is strongly associated with liver surgery safety, short-term prognoses and higher economic costs and also indirectly constrains long-term prognoses. Thus, the prediction of PHLF is of great clinical significance to accurately assess liver functional reserve. Shear wave elastography imaging is a non-invasive and repeatable technology that can accurately differentiate significant fibrosis (F≥2) among patients with liver disease (23,24). In theory, severe liver cirrhosis indicates fewer functional liver cells (25). Accordingly, hepatic reserve function is worse when there are fewer functional liver cells. Hepatic reserve function is defined as a total of all normal liver cells function. The risk for PHLF can be indirectly reflected by assessing hepatic reserve function. Therefore, it provided fundamental theories for predicting PHLF using shear wave elastography imaging. Our present prospective study was designed to evaluate the predictive ability of LS measured by SWE among patients with grade A/B PHLF HCC. SWE has good stability and reproducibility as the latest generation of elastography technology (15,16). The predictive performance of SWE was compared with other preoperative

and perioperative risk factors. This new technique provides an important tool with which clinicians and patients can minimize the incidence rate of PHLF. In our study, the highest predictive value was the SWE measurement. Additionally, preoperative liver function indexes, such as serum INR, bilirubin, and AST, also demonstrated significant predictive abilities. Serum markers for liver fibrosis, such as hyaluronic acid, laminin, and pre-albumin, were associated with PHLF in the univariate but not the multivariate analysis (perhaps these markers separately predict PHLF). Recently, a new study indicated that a model consisting of four liver fibrosis markers provided better predictions (11). The preoperative clinical signs of PH were also relatively good predictors of PHLF. Liver cirrhosis is the primary reason for the formation of PH and is thus linearly correlated. Our SWE cut-off value of 6.9 kPa (77.8% sensitivity; 78.0% specificity; 0.843 AUC) accurately predicted PHLF in our study. Few studies have investigated the performance of SWE technology for identifying PHLF grades A/B. In Cescon et al., the best ElastPQ cut-off value via Fibroscan for the prediction of PHLF was 15.7 kPa with an AUC of 0.865 (14). The higher cut-off value could be explained by the fact that their study mainly included patients with PHLF grade C. Thus, the LS values were relatively higher. According to the obtained SWE cut-off value, patients with an elevated SWE had a higher degree of histological F4 fibrosis, which is directly correlated with the existence of poorer liver function, such as higher serum INR levels, bilirubin levels and MELD scores. Similarly, the degree of liver fibrosis was positively associated

with the occurrence of clinical signs of PH. In addition, liver fibrosis disturbs the balance between the synthesis and degradation of the extracellular matrix in liver tissue. Excessive proliferation and abnormal deposition of the extracellular matrix will increase serum levels of extracellular matrix components or degraded products (26). Thus, patients with elevated SWE levels had higher levels of biomarkers for liver fibrosis. Interestingly, patients with elevated SWE values more frequently presented with multiple tumor nodules. Compared to patients with single HCC nodules, patients with multiple nodules require resection of more normal liver tissue surrounding the tumor, which greatly reduces the remaining liver function. We also noted that severe liver cirrhosis was associated with a greater likelihood of the occurrence of multiple tumor nodules. Further work will be necessary to confirm this observation. The present prospective study has several strengths. Pre-operative SWE values measured by noninvasive ultrasonic elastography could objectively reflect the liver reserve capacity and was a good predictor of grade A/B PHLF. It shows better independently risk prediction ability, when compared with all kinds of preoperative risk factor of PHLF. Secondly, the main endpoint of the study was specific to the patient population with mild-moderate liver failure (grades A/B) on the basis of the ISGLS recommendations, which expands the population in which SWE is predictive, but also be more adaptable to the current and future clinical conditions. Third, our study compared SWE with conventional quantitative liver function tests, clinical grading systems and the presence of portal hypertension. We also introduced novel

serum biochemical markers for liver fibrosis. Fourth, SWE can provide good stability and reproducibility in measuring LS. This study also had several limitations. We did not use the hepatic venous pressure gradient to assess PHLF. The hepatic venous pressure gradient can be used before surgery to stratify the risk of PHLF (8). However, the accuracy of the hepatic venous pressure gradient may not be better than a simple noninvasive index (9). Another limitation was the relatively small sample size. Due to the high prevalence of hepatitis B virus infections in our country, most patients enrolled in the study had HBV-related HCC. In conclusion, preoperative LS measured by SWE is a good independent predictor for the risk of PHLF grades A/B. SWE could be a routine examination tool for the preoperative evaluation of liver reserve function.

REFERENCES 1. Breitenstein S, DeOliveira ML, Raptis DA, et al. Novel and simple preoperative score predicting complications after liver resection in noncirrhotic patients. Ann Surg 2010;252(5):726–734. 2. Schindl MJ, Millar AM, Redhead DN, et al. The adaptive response of the reticuloendothelial system to major liver resection in humans. Ann Surg 2006;243(4):507–514. 3. Paugam-Burtz C, Janny S, Delefosse D, et al. Prospective validation of the “fifty-fifty” criteria as an early and accurate predictor of death after liver resection in intensive care unit patients. Ann Surg 2009;249(1):124–128. 4. Lock JF, Reinhold T, Malinowski M, et al. The costs of postoperative liver failure and the economic impact of liver function capacity after extended liver resection: a single-center experience. Langenbecks Arch Surg 2009;394(6):1047–1056. 5. Lam CM, Fan ST, Lo CM, et al. Major hepatectomy for hepatocellular carcinoma in patients with an unsatisfactory indocyanine green clearance test. Br J Surg

1999;86(8):1012–1017. 6. Wong JS, Wong GL, Chan AW, et al. Liver stiffness measurement by transient elastography as a predictor on posthepatectomy outcomes. Ann Surg 2013;257(5):922–928. 7. European Association for the Study of the Liver; European Organisation for Research and Treatment of Cancer. EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol 2012;56:908–943. 8. Berzigotti A, Reig M, Abraldes JG, et al. Portal hypertension and the outcome of surgery for hepatocellular carcinoma in compensated cirrhosis: a systematic review and meta-analysis. Hepatology 2015;61:526–536. 9. Berzigotti A,Reig M,Abraldes JG, et al. Portal hypertension on the outcome of surgery for hepatocellular carcinoma in compensated cirrhosis: a systematic review and meta-analysis. Hepatology 2015;61(2):526-36. 10. Wibmer A, Prusa AM, Nolz R, et al. Liver failure after major liver resection: risk assessment byusing preoperative Gad -oxetic acid-enhanced 3-T MR imaging. Radiology 2013;269(3):777-86. 11. Shen Y, Shi G, Huang C, et al. Prediction of Post-Operative Liver Dysfunction by Serum Markers of Liver Fibrosis in Hepatocellular Carcinoma. PLoS One 2015;10(10):e0140932. 12. Yachida S, Wakabayashi H, Okano K, et al. Prediction of posthepatectomy hepatic functional reserve by serum hyaluronate. The British journal of surgery 2009;96(5):501–8. 13. M. Ziol, A. Handra-Luca, A. Kettaneh, et al. Beaugrand. Noninvasive assessment of liverfibrosis by measurement of stiffness in patients with chronic hepatitis C. Hepatology 41 (1) (2005) 48-54. 14. Cescon M, Colecchia A, Cucchetti A, et al. Value of Transient Elastography Measured With Fibroscan in Predicting the Outcome of Hepatic Resection for Hepatocellular Carcinoma. Ann Surg 2012;256(5):706-712. 15. Ma JJ, Ding H, Mao F, et al. Assessment of liver fibrosis with elastography point quantification technique in ch ronic hepatitis B viruspatients: a comparison with liver pathological results. J Gastroenterol Hepatol 2014;29(4):814-819. 16. Sporea I, Bota S, Grădinaru-Taşcău O, et al. Comparative study between two point Shear Wave Elastographic techniques: Acoustic Radiation Force Impulse (ARFI) elastography and SWE. Med Ultrason 2014;16(4):309-314. 17. Ishizawa T, Hasegawa K, Aoki T. Neither multiple tumors nor portal hypertension are surgical contraindications for hepatocellular carcinoma. Gastroenterology 2008;134:1908–1916. 18. S.K. Reddy, A.S. Barbas, R.S. Turley, et al. A standard definition of major hepatectomy: resection of four or more liver segments. HPB (Oxford) 2011;13(7):494-502. 19. Malinchoc M, Kamath PS, Gordon FD, et al. A model to predict poor survival in patients undergoing transjugular intrahepatic portosystemic shunts. Hepatology 2000;31:864-71.

20. Rahbari NN, Garden OJ, Padbury R, et al. Posthepatectomy liver failure: a definition and grading by the International Study Group of Liver Surgery (ISGLS). Surgery 2011;149(5):713-724. 21. Fukushima K, Fukumoto T, Kuramitsu K, et al. Assessment of ISGLS definition of posthepatectomy liver failure and its effect on outcome in patients with hepatocellular carcinoma. J Gastrointest Surg 2014;18:729–736. 22. Balzan S, Belghiti J, Farges O, et al. The ‘‘50-50 criteria” on postoperative day 5: an accurate predictor of liver failure and death after hepatectomy. Ann Surg 2005;242:824–828. 23. Zheng J, Guo H, Zeng J, et al. Two-dimensional shear-Wave elastography and conventional Us: The Optimal Evaluation of Liver Fibrosis and Cirrhosis. Radiology 2015;275(1):290-300. 24. Samir AE, Dhyani M, Vij A, et al. Shear-wave elastography for the estimation of liver fibrosis in chronic liver disease: determining accuracy and ideal site for measurement. Radiology 2015;274(3):888-96. 25. Yang YL, Di L, Duan YY, et al. A prospective experimental study of liver fibrosis with ultrasound and its correlation with hepatic reserve function and hemodynamics. BMC Gastroenterol 2012;23;12:168. 26. Castera L, Hartmann DJ, Chapel F, et al. Serum laminin and type IV collagen are accurate markers of histologically severe alcoholic hepatitis in patients with cirrhosis. Journal of hepatology 2000;32(3):412–8.

Figure 1. Measurements of shear wave elastography (SWE).

Figure 2. Receiver operating characteristic curve for postoperative PHLF according to SWE values.

Figure 3. The Postoperative Dynamic Course of the MELD Score Stratified by High or Low SWE Values. POD=postoperative day.

Table1. Baseline characteristics of the overall study population. Variable All patients (n=77) Gender, Male 63 (81.8%) Age, years 59 (24-91) Comorbidity 24 (31.2%) Viral hepatitis, HBV infection 69 (89.6%) Platelet count, 10 9/L 173 (50-606) Serum hemoglobin, g/L 137 (83-193) Serum creatinine, umol/L 77 (45-181) Serum albumin, g/L 41 (26-53) Serum INR 1.0 (0.87-1.29) Serum bilirubin, umol/L 12 (5.2-43) Serum sodium, mmol/L 142 (133-147) Serum AST, U/L 31 (14-167) Serum ALT, U/L 30 (8-98) Serum GGT, U/L 59 (17-1019) Serum hyaluronic acid, ng/Ml 98.7 (<60-510) Serum laminin, ng/Ml 50 (<50-400) Serum prealbumin, ng/mL 0.21 (0.09-0.38) Serum HBV DNA level, >10 4 IU/mL 30 (37.5%) Child-Pugh stage A 72 (90%) MELD score 5.8 (4.8-6.5) Clinical signs of PH 9 (11.7%) SWE values (kPa) 6.3 (2.4-22.0) The largest nodule diameter, imaging, cm 5.3 (1.7-14.0) Single HCC nodule, imaging 58 (72.5%) Major hepatectomy, surgery 23 (28.7%) Time of occlusion, surgery, min 12 (0-35) Blood loss, surgery, ml 200 (0-1500) Transfusion, surgery 15 (18.8%) Histological F4 fibrosis, pathology 48 (60%) The largest nodule diameter, pathology, cm 5.9 (1.2-16.0) Single HCC nodule, pathology 52 (65%) Presence of liver steatosis, pathology 16 (20%)

Table2. Univariate and multivariate logistic regression analyses for the continuous/categorical preoperative, intraoperative and histological variables of postoperative liver failure according to the ISGLS criteria. Variable Continuous Age Serum albumin Serum INR Serum bilirubin Serum sodium Serum AST Serum ALT Serum GGT Serum hyaluronic acid Serum laminin Serum prealbumin MELD score SWE values The largest nodule diameter, imaging Time of occlusion, surgery Blood loss, surgery Categorical

Univariate Analysis

Multivariate Analysis

presence of PHLF (n=27) 58 (37-75)

non-presence of PHLF (n=50) 59 (24-91)

Exp (B)

OR (95% CI)

P

0.911

40 (26-53)

41 (26-51)

0.712

1.03 (0.87-1.17)

0.98 (0.87-1.29)

0.022

0.96

0.385-2.394

0.93

13.1 (5.3-43)

10.7 (5.2-34.5)

0.046

1.046

0.953-1.148

0.342

142 (136-147)

142 (133-147)

0.368

41 (21-115) 39 (18-108) 64 (19-698)

33 (14-167) 31 (9-97) 56 (17-1019)

0.002 0.105 0.281

1.005

0.983-1.027

0.663

128.2 (60-510)

83.1 (60.0-324.7)

0.026

1.001

0.993-1.009

0.795

50 (50-400)

50 (50.0-203.6)

0.006

1.006

0.994-1.017

0.342

0.2 (0.09-0.32)

0.24 (0.12-0.38)

0.041

0.009

0.169-2.617

0.456

5.8 (4.8-6.5) 8.1 (4.6-22.0)

5.8 (4.8-6.4) 5.2 (2.4-11.6)

0.083 0.001

1.642

1.208-2.231

0.002

5 (1.7-14.0)

5.5 (2.0-13.8)

0.745

9.0 (0.0-33.0)

13.0 (0.0-35.0)

0.105

200 (30-1500)

200 (0-1500)

0.948

Category

OR (95% CI)

P

Exp (B)

OR (95% CI)

P

Gender, Male

Male vs. female

Comorbidity

Present vs. absent

Viral

Viral vs. others

1.437 (0.405-5.108) 1.513 (0.559-4.094) 0.889

P

0.575 0.415 0.879

hepatitis, HBV infection Serum HBV DNA level, >10 4 IU/mL Child-Pugh stage A Clinical signs of PH Major hepatectomy, surgery Transfusion, surgery Presence of liver steatosis, pathology Histological cirrhosis

(0.195-4.043)

higher vs. lower

Present vs. absent Present vs. absent

0.690 (0.260-1.835) 3.0 (0.469-19.177) 17.150 (1.980-148.542)

0.458

0.246 0.01

Major vs. minor

0.674 (0.613-4.572)

0.315

Present vs. absent

1.837 (0.584-5.778)

0.298

Present vs. absent

0.806 (0.248-2.620)

0.72

Present vs. absent

14.674 (3.134-68.717)

0.001

8.556

0.961-76.135

0.054

11.045

2.308-52.857

0.003

Table3. Baseline characteristics stratified by the SWE value subgroups. SWE values SWE values < 6.9 Variable ≥6.9 kPa (n=32) kPa (n=45) Gender, Male 28 (87.5%) 35 (77.8%) Age, years 60 (41-75) 58 (24-91) Comorbidity 10 (31.3%) 14 (31.1%) Viral hepatitis, HBV infection 30 (93.8%) 39 (86.7%) Platelet count, 10 9/L 154 (50-606) 196 (60-436) Serum hemoglobin, g/L 140 (93-193) 133 (83-176) Serum creatinine, umol/L 75 (49-181) 78 (45-117) Serum albumin, g/L 41 (26-53) 41 (26-51) Serum INR 1.01 (0.87-1.29) 0.97 (0.87-1.18) Serum bilirubin, umol/L 13.8 (5.3-43.0) 11.4 (5.2-25.8) Serum sodium, mmol/L 142 (137-146) 142 (133-147) Serum AST, U/L 39 (16-115) 32 (14-167) Serum ALT, U/L 38 (9-108) 30 (11-104) Serum GGT, U/L 65 (24-698) 53 (17-1019) Serum hyaluronic acid, ng/Ml 149 (60-510) 80 (60-325) Serum laminin, ng/mL 50 (50-400) 50 (50-204) Serum prealbumin, ng/mL 0.2 (0.09-0.31) 0.24 (0.11-0.38) Serum HBV DNA level, >10 4 IU/mL 13 (40.6%) 17 (37.8%) Child-Pugh stage A 29 (90.6%) 43 (95.6%) MELD score 5.8 (5.8-6.5) 5.7 (4.8-6.4) Clinical signs of PH 8 (25.0%) 1 (2.2%) SWE values (kPa) 8.6 (7.0-22.0) 4.9 (2.4-6.8) The largest nodule diameter, imaging, cm 5.0 (1.7-14.0) 5.6 (2.0-13.8) Single HCC nodule, imaging 13 (40.6%) 29 (64.4%) Major hepatectomy, surgery 12 (37.5%) 11 (24.4%) Time of occlusion, surgery, min 11 (0-33) 12 (0-35) Blood loss, surgery, ml 200 (0-800) 200 (10-1500) Transfusion, surgery 8 (25.0%) 7 (15.6%) Histological F4 fibrosis, pathology 29 (90.6%) 19 (42.2%) The largest nodule diameter, pathology, cm 4.0 (1.2-16.0) 5.6 (1.0-13.5) Single HCC nodule, pathology 15 (46.9%) 35 (77.8%) Presence of liver steatosis, pathology 3 (9.4%) 13 (28.9%)

P 0.607 0.453 0.99 0.315 0.119 0.917 0.289 0.798 0.023 0.03 0.536 0.73 0.894 0.456 0.002 0.041 0.015 0.801 0.387 0.018 <0.001 <0.001 0.625 0.039 0.217 0.894 0.41 0.302 <0.001 0.858 0.023 0.038

Table4. Postoperative complication grades A/B stratified by the SWE value subgroups according to the ISGLS proposal. SWE All SWE values Variables patients values ≥6.9 P <6.9 kPa (n = 77) kPa (n=32) (n=45) 27 At least one grade A/B complication 22 (71.0%) 5 (10.9%) 0.001 (35.1%) Ascites and/or pleural effusion requiring 12 9 (29.0%) 3 (6.5%) 0.011 medical (15.6%) therapy and/or drainage Ascites requiring albumin, diuretics 6 (7.8%) 5 (16.1%) 1 (2.2%) 0.031 and/or Drainage Pleural effusion requiring albumin, 1 (1.3%) 1 (3.2%) 0 (0.0%) 0.233 diuretics and/or drainage INR value between 1.5 and 2.0 4 (5.2%) 3 (9.7%) 0 (0.0%) 0.036 Bilirubin above 3 mg requiring additional 2 (2.6%) 1 (3.2%) 1 (2.2%) 0.806 radiological and laboratory tests Inadequate urine output 2 (2.6%) 1 (3.2%) 0 (0.0%) 0.233 Fever with positive blood cultures 4 (5.2%) 3 (9.7%) 1 (2.2%) 0.163 requiring modification of antibiotics and central line Replacement Biliary leak requiring delay in drainage 0 (0.0%) 0 (0.0%) 0 (0.0%) removal Other 3 (3.9%) 2 (6.5%) 1 (2.2%) 0.368 Need for salvage transplantation 0 (0.0%) 0 (0.0%) 0 (0.0%) -