Prediction of major complications after hepatectomy using liver stiffness values determined by magnetic resonance elastography

Current status of preoperative risk assessment for posthepatectomy liver failure in patients with hepatocellular carcinoma

Liver resection is an effective therapeutic option for patients with hepatocellular carcinoma. However, posthepatectomy liver failure (PHLF) remains a major cause of hepatectomy-related mortality, and the accurate prediction of PHLF based on preoperative assessment of liver functional reserve is a critical issue. The definition of PHLF proposed by the International Study Group for Liver Surgery has gained acceptance as a standard grading criterion. Liver function can be estimated using a variety of parameters, including routine blood biochemical examinations, clinical scoring systems, dynamic liver function tests, liver stiffness and fibrosis markers, and imaging studies. The Child-Pugh score and model for end-stage liver disease scores are conventionally used for estimating liver decompensation, although the alternatively developed albumin-bilirubin score shows superior performance for predicting hepatic dysfunction. Indocyanine green clearance, a dynamic liver function test mostly used in Japan and other Asian countries, serves as a quantitative estimation of liver function reserve and helps determine indications for surgical procedures according to the estimated risk of PHLF. In an attempt to improve predictive accuracy, specific evaluation of liver fibrosis and portal hypertension has gained popularity, including liver stiffness measurements using ultrasonography or magnetic resonance elastography, as well as noninvasive fibrosis markers. Imaging modalities, including Tc-99m-labeled galactosyl serum albumin scintigraphy and gadolinium-enhanced magnetic resonance imaging, are used for preoperative evaluation in combination with liver volume. This review aims to provide an overview of the usefulness of current options for the preoperative assessment of liver function in predicting PHLF.

E-AHPBA-ESSO-ESSR Innsbruck consensus guidelines for preoperative liver function assessment before hepatectomy

BACKGROUND

Posthepatectomy liver failure (PHLF) contributes significantly to morbidity and mortality after liver surgery. Standardized assessment of preoperative liver function is crucial to identify patients at risk. These European consensus guidelines provide guidance for preoperative patient assessment.

METHODS

A modified Delphi approach was used to achieve consensus. The expert panel consisted of hepatobiliary surgeons, radiologists, nuclear medicine specialists, and hepatologists. The guideline process was supervised by a methodologist and reviewed by a patient representative. A systematic literature search was performed in PubMed/MEDLINE, the Cochrane library, and the WHO International Clinical Trials Registry. Evidence assessment and statement development followed Scottish Intercollegiate Guidelines Network methodology.

RESULTS

Based on 271 publications covering 4 key areas, 21 statements (at least 85 per cent agreement) were produced (median level of evidence 2- to 2+). Only a few systematic reviews (2++) and one RCT (1+) were identified. Preoperative liver function assessment should be considered before complex resections, and in patients with suspected or known underlying liver disease, or chemotherapy-associated or drug-induced liver injury. Clinical assessment and blood-based scores reflecting liver function or portal hypertension (for example albumin/bilirubin, platelet count) aid in identifying risk of PHLF. Volumetry of the future liver remnant represents the foundation for assessment, and can be combined with indocyanine green clearance or LiMAx® according to local expertise and availability. Functional MRI and liver scintigraphy are alternatives, combining FLR volume and function in one examination.

CONCLUSION

These guidelines reflect established methods to assess preoperative liver function and PHLF risk, and have uncovered evidence gaps of interest for future research.

Clinical application of Magnetic resonance elastography in hepatocellular carcinoma: from diagnosis to prognosis

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and a major public health problem worldwide. Liver fibrosis is closely correlated with liver functional reserve and the risk of HCC development. Meanwhile, malignant tumors generally have high cellularity compared to benign tumors, which results in increased stiffness. Magnetic resonance elastography (MRE) has emerged as a new non-invasive technique for assessing tissue stiffness with excellent diagnostic accuracy, not only for assessing liver fibrosis but also for measuring tumor stiffness. Recent studies provide new evidence that MRE may play an important role in the management of patients with HCC and show several novel clinical applications, such as predicting the development of HCC, differentiating between benign/malignant liver lesions (FLL) and HCC pathological grades, assessing treatment response, and predicting recurrence after treatment, although some findings are controversial. Therefore, we conducted this review to summarize these novel applications of MRE in HCC patients and also discuss their limitations and future advancement.

Sarcopenia Predicts Major Complications after Resection for Primary Hepatocellular Carcinoma in Compensated Cirrhosis

Simple Summary

Sarcopenia, which is defined as a loss of skeletal muscle mass, function and strength, is the result of major metabolic changes often observed in advanced liver disease. Its evaluation mirrors the nutritional and functional status of the patients, and thus has been recently implicated as an outcome predictor of patients with liver diseases and hepatocellular carcinoma. This study provides evidence that sarcopenia, as assessed by the skeletal muscle index, is associated with age and body mass index in liver surgery candidates. More importantly, it is associated with higher rates of major complications (Clavien-Dindo grade III or IV) in patients with compensated advanced chronic liver disease and/or portal hypertension undergoing liver resection for primary hepatocellular carcinoma.

Abstract

The burden of post-operative complications of patients undergoing liver resection for hepatocellular carcinoma (HCC) is a cause of morbidity and mortality. Recently, sarcopenia has been reported to influence the outcome of patients with cirrhosis. We aimed to assess factors associated with sarcopenia and its prognostic role in liver surgery candidates. We included all patients with compensated advanced chronic liver disease (cACLD) undergoing liver resection for primary HCC consecutively referred to the University of Bologna from 2014 to 2019 with an available preoperative abdominal CT-scan performed within the previous three months. A total of 159 patients were included. The median age was 68 years, and 80.5% of the patients were male. Sarcopenia was present in 82 patients (51.6%). Age and body mass index (BMI) were associated with the presence of sarcopenia at multivariate analysis. Thirteen (8.2%) patients developed major complications and 14 (8.9%) presented PHLF grade B-C. The model for end-stage liver disease score was associated with the development of major complications, whereas cACLD presence, thrombocytopenia, portal hypertension (PH), Child-Pugh score and Albumin-Bilirubin score were found to be predictors of clinically significative PHLF. The rate of major complications was 11.8% in sarcopenic patients with cACLD compared with no complications (0%) in patients without sarcopenia and cACLD (p = 0.032). The rate of major complications was significantly higher in patients with (16.3%) vs. patients without (0%) sarcopenia (p = 0.012) in patients with PH. In conclusion, sarcopenia, which is associated with age and BMI, may improve the risk stratification of post-hepatectomy major complications in patients with cACLD and PH.

A proposed model on MR elastography for predicting postoperative major complications in patients with hepatocellular carcinoma

Objective

To develop a model for predicting post-operative major complications in patients with hepatocellular carcinoma (HCC).

Methods

In all, 186 consecutive patients with pre-operative MR elastography were included. Complications were categorised using Clavien‒Dindo classification, with major complications defined as ≥Grade 3. Liver-stiffness measurement (LSM) values were measured on elastogram. The indocyanine green clearance rate of liver remnant (ICG-Krem) was based on the results of CT volumetry, intraoperative data, and ICG-K value. For an easy application to the prediction model, the continuous variables were converted to categories. Moreover, logistic regression analysis and fivefold cross-validation were performed. The prediction model's discriminative performance was evaluated using the area under the receiver operating characteristic curve (AUC), and the calibration of the model was assessed by the Hosmer‒Lemeshow test.

Results

43 of 186 patients (23.1%) had major complications. The multivariate analysis demonstrated that LSM, albumin-bilirubin (ALBI) score, intraoperative blood loss, and ICG-Krem were significantly associated with major complications. The median AUC of the five validation subsets was 0.878. The Hosmer-Lemeshow test confirmed no evidence of inadequate fit (p = 0.13, 0.19, 0.59, 0.59, and 0.73) on the fivefold cross-validation. The prediction model for major complications was as follows: -2.876 + 2.912 [LSM (>5.3 kPa)]+1.538 [ALBI score (>-2.28)]+0.531 [Intraoperative blood loss (>860 ml)]+0.257 [ICG-Krem (<0.10)].

Conclusion

The proposed prediction model can be used to predict post-operative major complications in patients with HCC.

Advances in knowledge

The proposed prediction model can be used in routine clinical practice to identify post-operative major complications in patients with HCC and to strategise appropriate treatments of HCC.

Risk Prediction Model Based on Magnetic Resonance Elastography-Assessed Liver Stiffness for Predicting Posthepatectomy Liver Failure in Patients with Hepatocellular Carcinoma

Background/Aims

Posthepatectomy liver failure (PHLF) is a major complication that increases mortality in patients with hepatocellular carcinoma after surgical resection. The aim of this retrospective study was to evaluate the utility of magnetic resonance elastography-assessed liver stiffness (MRE-LS) for the prediction of PHLF and to develop an MRE-LS-based risk prediction model.

Methods

A total of 160 hepatocellular carcinoma patients who underwent surgical resection with available preoperative MRE-LS data were enrolled. Clinical and laboratory parameters were collected from medical records. Logistic regression analyses were conducted to identify the risk factors for PHLF and develop a risk prediction model.

Results

PHLF was present in 24 patients (15%). In the multivariate logistic analysis, high MRE-LS (kPa; odds ratio [OR] 1.49, 95% confidence interval [CI] 1.12 to 1.98, p=0.006), low serum albumin (≤3.8 g/dL; OR 15.89, 95% CI 2.41 to 104.82, p=0.004), major hepatic resection (OR 4.16, 95% CI 1.40 to 12.38, p=0.014), higher albumin-bilirubin score (>-0.55; OR 3.72, 95% CI 1.15 to 12.04, p=0.028), and higher serum α-fetoprotein (>100 ng/mL; OR 3.53, 95% CI 1.20 to 10.40, p=0.022) were identified as independent risk factors for PHLF. A risk prediction model for PHLF was established using the multivariate logistic regression equation. The area under the receiver operating characteristic curve (AUC) of the risk prediction model was 0.877 for predicting PHLF and 0.923 for predicting grade B and C PHLF. In leave-one-out cross-validation, the risk model showed good performance, with AUCs of 0.807 for all-grade PHLF and 0. 871 for grade B and C PHLF.

Conclusions

Our novel MRE-LS-based risk model had excellent performance in predicting PHLF, especially grade B and C PHLF.

Hepatectomy-Induced Alterations in Hepatic Perfusion and Function - Toward Multi-Scale Computational Modeling for a Better Prediction of Post-hepatectomy Liver Function

Liver resection causes marked perfusion alterations in the liver remnant both on the organ scale (vascular anatomy) and on the microscale (sinusoidal blood flow on tissue level). These changes in perfusion affect hepatic functions via direct alterations in blood supply and drainage, followed by indirect changes of biomechanical tissue properties and cellular function. Changes in blood flow impose compression, tension and shear forces on the liver tissue. These forces are perceived by mechanosensors on parenchymal and non-parenchymal cells of the liver and regulate cell-cell and cell-matrix interactions as well as cellular signaling and metabolism. These interactions are key players in tissue growth and remodeling, a prerequisite to restore tissue function after PHx. Their dysregulation is associated with metabolic impairment of the liver eventually leading to liver failure, a serious post-hepatectomy complication with high morbidity and mortality. Though certain links are known, the overall functional change after liver surgery is not understood due to complex feedback loops, non-linearities, spatial heterogeneities and different time-scales of events. Computational modeling is a unique approach to gain a better understanding of complex biomedical systems. This approach allows (i) integration of heterogeneous data and knowledge on multiple scales into a consistent view of how perfusion is related to hepatic function; (ii) testing and generating hypotheses based on predictive models, which must be validated experimentally and clinically. In the long term, computational modeling will (iii) support surgical planning by predicting surgery-induced perfusion perturbations and their functional (metabolic) consequences; and thereby (iv) allow minimizing surgical risks for the individual patient. Here, we review the alterations of hepatic perfusion, biomechanical properties and function associated with hepatectomy. Specifically, we provide an overview over the clinical problem, preoperative diagnostics, functional imaging approaches, experimental approaches in animal models, mechanoperception in the liver and impact on cellular metabolism, omics approaches with a focus on transcriptomics, data integration and uncertainty analysis, and computational modeling on multiple scales. Finally, we provide a perspective on how multi-scale computational models, which couple perfusion changes to hepatic function, could become part of clinical workflows to predict and optimize patient outcome after complex liver surgery.

Accuracy comparison of MR elastography and biological markers in detecting liver fibrosis and predicting postoperative ascites

BACKGROUND

This retrospective study aimed to compare the discriminative performance between magnetic resonance elastography (MRE) and biological markers in detecting liver fibrosis and in predicting postoperative ascites (PA).

METHODS

We enrolled 77 patients consecutively who underwent hepatectomy between March 2017 and June 2019. Liver fibrosis was histopathologically graded using the METAVIR scoring system as reference. Discriminative performance of non-invasive assessments in detecting different stages of liver fibrosis and predicting PA was evaluated by receiver-operator curve analysis.

RESULTS

The concordance indices (C-indices) for MRE and biological markers for detecting significant fibrosis (≥F2) and cirrhosis (F4) were: MRE, 0.84 and 0.86; Wisteria floribunda agglutinin + Mac-2 binding protein (WM2BP), 0.63 and 0.71; Hyaluronic acid (HA), 0.72 and 0.75; 7 S-type 4 collagen (T4C), 0.61 and 0.66; APRI, 0.76 and 0.83; and Fib-4, 0.75 and 0.76. Univariable logistic analysis for predicting PA showed that C-indices were 0.751 (p = 0.007), 0.798 (p = 0.106), 0.771 (p = 0.050), 0.674 (p = 0.855), 0.655 (p = 0.263), and 0.560 (p = 0.640) for MRE, WM2BP, Fib-4, HA, APRI, and T4C, respectively.

CONCLUSION

MRE has a higher diagnostic performance than biological markers in detecting the stages of liver fibrosis and is a predictor for PA after hepatectomy.

Predictive value of combined computed tomography volumetry and magnetic resonance elastography for major complications after liver resection

PURPOSE

To retrospectively compare the predictive value of computed tomography volumetry (CTV), magnetic resonance elastography (MRE) of the liver, and their combination for major complications after liver resection.

METHODS

We enrolled 108 consecutive patients who underwent anatomical liver resection for liver tumors and preoperative contrast-enhanced CT and MRE. The future liver remnant (FLR) ratio was calculated by CTV, while the liver stiffness measurement (LSM) was obtained by MRE. FLR ratio alone, LSM alone, and combined FLR ratio and LSM were evaluated to predict major complications (Clavien-Dindo grade ≥ IIIa). Univariate and multivariate analyses of hepatic biochemical parameters and imaging data were performed to identify predictors of major complications. Receiver operating characteristic analyses of FLR ratio, LSM, and their combination were performed, and the sensitivity and specificity were calculated.

RESULTS

Twenty-two (20.4%) of the 108 patients experienced major complications. According to multiple regression analysis, the FLR ratio (odds ratio [OR] 0.96, 95% confidence interval [CI] 0.91-0.99, p = 0.040) and LSM (OR 1.72, 95% CI 1.01-2.94, p = 0.047) were independent predictors of major complications. The combined FLR ratio and LSM were predictive of major complications, with an area under the curve (AUC) of 0.818, sensitivity of 68.2%, and specificity of 84.9%. The AUC and specificity for combined FLR ratio and LSM were larger than those for FLR ratio (AUC: 0.711, specificity: 80.2%) and LSM (AUC: 0.793, specificity: 80.2%).

CONCLUSION

Combined CTV and MRE analysis can improve the AUC and specificity for predicting major complications after anatomical liver resection.

A nomogram based on liver stiffness predicts postoperative complications in patients with hepatocellular carcinoma

BACKGROUND & AIMS

Liver stiffness measurement (LSM), assessed by transient elastography (Fibroscan), has been demonstrated to predict post-hepatectomy liver failure in patients who undergo hepatic resection for hepatocellular carcinoma (HCC). However, other complications are also likely to be related to the underlying grade of liver fibrosis. Herein, we aimed to identify predictors of postoperative complications and to build and develop a novel nomogram able to identify patients at risk of developing severe complications.

METHODS

Data from patients who underwent hepatectomy for HCC between 2006 and 2016 at 2 referral centres were retrospectively reviewed. All surgical complications were recorded and scored using the comprehensive complication index (CCI), ranging from 0 (uneventful course) to 100 (death). A CCI ≥26.2 was used as a threshold to define severe complications.

RESULTS

During the study period, 471 patients underwent hepatic resection for HCC. Among them, 50 patients (10.6%) had a CCI ≥26.2. Age, model for end-stage liver disease (MELD) score and LSM values, together with serum albumin, were independent predictors of high CCI. The nomogram built on these variables was internally validated and showed good performance (optimism-corrected c-statistic = 0.751). A regression equation to predict the CCI was also established by multiple linear regression analysis: [LSM (kPa) × 0.254] + [age (years) × 0.118] + [MELD score (pt.) × 1.050] - [albumin (g/dl) × 2.395] - 3.639.

CONCLUSION

A novel nomogram, combining LSM values, age and liver function tests provided an excellent preoperative prediction of high CCI in patients with resectable HCC. This predictive model could be used as a reference for clinicians and surgeons to help them in clinical decision-making.

LAY SUMMARY

Liver stiffness measurement is increasingly being used to assess the degree of liver fibrosis in patients with cirrhosis and/or chronic hepatitis. Using Fibroscan, we developed a novel nomogram to predict severe complications following liver resection for hepatocellular carcinoma, according to the new comprehensive complication index. This tool could be used as a reference for clinicians and surgeons to help them in clinical decision-making.

Predictive value of perfusion CT for blood loss in liver resection

Blood loss is associated with the degree of damage in liver stiffness. Severe liver steatosis is a matter of concern in liver surgery, but does not correlate with liver stiffness. This study aimed to assess the relationship between blood perfusion of the liver and blood loss in liver pathologies. Data from elective liver resection for liver cancer were analyzed. All patients underwent preoperative assessments including perfusion CT. Patients were divided into 4 groups in accordance with the pathological background of liver parenchyma. Relationships between portal flow as assessed by perfusion CT and perioperative variables were compared. Factors correlating with blood loss were analyzed. In 166 patients, portal flow from perfusion CT correlated positively with platelet count and negatively with indocyanine green retention rate at 15 min. Background liver pathology was normal liver (NL) in 43 cases, chronic hepatitis (CH) in 56, liver cirrhosis (LC) in 42, and liver steatosis (LS) in 25. Rates of hepatitis viral infection and pathological hepatocellular carcinoma were more frequent in LC and CH groups than in the other groups (p < 0.05). LC and LS showed significantly worse liver function than the NL and CH groups. Portal flow from perfusion CT correlated positively with damage to liver parenchyma and negatively with blood loss at liver transection. Low portal flow on perfusion CT predicts blood loss during liver transection.

Effects of preoperative dental examination and oral hygiene instruction on surgical site infection after hepatectomy: a retrospective study

PURPOSE

This study retrospectively investigated relationships among risk factors and post-hepatectomy surgical site infection (SSI) and other complications in patients who underwent hepatectomy for hepatocellular carcinoma (HCC).

METHODS

We included 334 patients who underwent hepatectomies for liver cancers between January 2011 and December 2015 in this study. We evaluated risk factors for SSI and other post-hepatectomy complication, including demographic factors, preoperative factors, and preoperative intervention including oral management, perioperative factors, and length of hospital stay, with univariate and multivariate analyses. The oral management intervention included self-care instructions, extraction of infected teeth, removal of dental plaques and calculus (scaling), professional mechanical teeth cleaning, removal of tongue coating, and cleaning of dentures. SSI was defined in accordance with the guideline issued by the Centers for Disease Control and Prevention; it included purulent discharge from any incision or organ space within 30 days postoperatively, with or without microbiological evidence. Complications of grade II or greater, according to the Clavien-Dindo classification, were regarded as postoperative complications.

RESULTS

We found bacterial infection of ascites (Odds ratio (OR) = 13.72), lack of preoperative oral management intervention (OR = 10.17), and severe liver fibrosis (OR = 2.76) to be associated with SSI and severe liver fibrosis (OR = 2.28), hypoalbuminemia (OR = 2.02), blood transfusion (OR = 1.86), and longer operation time (OR = 1.80) to be associated with postoperative complications.

CONCLUSIONS

Preoperative oral management may reduce the risk of SSI in patients with HCC who undergo hepatectomy.

Preoperative Mac-2 binding protein glycosylation isomer level predicts postoperative ascites in patients with hepatic resection for hepatocellular carcinoma

AIM

Postoperative ascites is one of the most common complications after hepatic resection and is related to liver fibrosis. Mac-2 binding protein glycosylation isomer (M2BPGi) is a reliable and non-invasive marker for assessing liver fibrosis. This study aimed to evaluate whether preoperative M2BPGi level can predict postoperative refractory ascites in patients with curative hepatic resection for hepatocellular carcinoma.

METHODS

The present study retrospectively evaluated 59 patients between January 2016 and June 2018. We assessed the relationship between preoperative M2BPGi levels, expressed as the cut-off index, and postoperative ascites.

RESULTS

The median M2BPGi level was 1.36 (range 0.34-11.56). Postoperative ascites occurred in seven patients (11.9%). Among them, refractory ascites, defined as diuretic-resistant ascites, occurred in four patients (6.8%). Uni- and multivariate analysis showed that preoperative M2BPGi level was the only independent risk factor of postoperative ascites (odds ratio 3.28, P = 0.033). The cut-off values of M2BPGi for postoperative ascites and refractory ascites were 2.41 and 3.10, respectively. Remarkably, there were no patients with postoperative ascites and refractory ascites when the preoperative M2BPGi levels were less than each cut-off value.

CONCLUSION

Our results suggest that M2BPGi level is a reliable and non-invasive surrogate marker for predicting postoperative ascites before curative resection for hepatocellular carcinoma.