Prediction Of Posthepatectomy Liver Failure Research Articles

Risk predictors of post-hepatectomy liver failure: unraveling complexities and navigating challenges in clinical application

Risk predictors of post-hepatectomy liver failure: unraveling complexities and navigating challenges in clinical application

Utility of gadoxetate disodium-enhanced magnetic resonance imaging in evaluating liver failure risk after major hepatic resection.

Post-hepatectomy liver failure (PHLF) is still a predominant cause of hepatectomy-related mortality. However, it is difficult to evaluate the remnant liver functional reserve accurately before surgery to prevent PHLF. In this study, we aimed to explore the role of gadoxetate disodium-enhanced magnetic resonance imaging (MRI) in evaluating remnant liver functional reserve. For this cross-sectional study, the sample retrospectively included 56 patients undergoing liver resections of at least three segments between June 2019 and September 2022 at The General Hospital of the Western Theater Command. Pre-surgery assessments involved liver computer tomography (CT), an indocyanine green (ICG) clearance test, the Child-Pugh scoring system, and liver function serum biochemical indicators. Each patient underwent a gadoxetate disodium-enhanced MRI before the hepatectomy, and we measured the remnant hepatocellular uptake index (rHUI) as well as the standard remnant hepatocellular uptake index (SrHUI). We examined the diagnostic utility of rHUI, SrHUI, indocyanine green retention rate of 15 minutes (ICG R15), and Albumin for PHLF. Receiver operating characteristics (ROC) analyses were used to measure the preoperative liver function parameters (namely, rHUI, SrHUI, ICG R15, and Albumin) for predicting PHLF. The areas under the curve (AUCs) were calculated and compared between different preoperative liver function parameters using the Wilson/Brown method. The Pearson or Spearman correlation coefficient was used for correlation analysis between ICG R15, Albumin, and rHUI and between ICG R15, Albumin, and SrHUI, respectively. Twelve patients (21.43%) had complications of PHLF. We found significant differences in rHUI, SrHUI, ICG R15, and Albumin between the non-PHLF and PHLF groups. The pooled r between ICG R15 and rHUI was -0.591 [95% confidence interval (CI): -0.740 to -0.389, P<0.001], and between ICG R15 and SrHUI was -0.534 (95% CI: -0.703 to -0.308, P<0.001). The area under the curve (AUC) values of rHUI, SrHUI, ICG R15, and Ablumin were 0.871 (sensitivity 81.82%; specificity 91.67%), 0.878 (sensitivity 79.55%; specificity 83.33%), 0.835 (sensitivity 99.73%; specificity 66.67%), and 0.782 (sensitivity 88.64%; specificity 58.33%), respectively. We found that the rHUI and SrHUI calculated using the gadoxetate disodium-enhanced MRI reflected a combination of remnant hepatocyte function and liver volume, and these were useful as a quantitative assessment indicator of remnant liver functional reserve and can be a better predictor of PHLF after major hepatic resection.

A combined pre- and intra-operative nomogram in evaluation of degrees of liver cirrhosis predicts post-hepatectomy liver failure: a multicenter prospective study.

Adequate evaluation of degrees of liver cirrhosis is essential in surgical treatment of hepatocellular carcinoma (HCC) patients. The impact of the degrees of cirrhosis on prediction of post-hepatectomy liver failure (PHLF) remains poorly defined. This study aimed to construct and validate a combined pre- and intra-operative nomogram based on the degrees of cirrhosis in predicting PHLF in HCC patients using prospective multi-center's data. Consecutive HCC patients who underwent hepatectomy between May 18, 2019 and Dec 19, 2020 were enrolled at five tertiary hospitals. Preoperative cirrhotic severity scoring (CSS) and intra-operative direct liver stiffness measurement (DSM) were performed to correlate with the Laennec histopathological grading system. The performances of the pre-operative nomogram and combined pre- and intra-operative nomogram in predicting PHLF were compared with conventional predictive models of PHLF. For 327 patients in this study, histopathological studies showed the rates of HCC patients with no, mild, moderate, and severe cirrhosis were 41.9%, 29.1%, 22.9%, and 6.1%, respectively. Either CSS or DSM was closely correlated with histopathological stages of cirrhosis. Thirty-three (10.1%) patients developed PHLF. The 30- and 90-day mortality rates were 0.9%. Multivariate regression analysis showed four pre-operative variables [HBV-DNA level, ICG-R15, prothrombin time (PT), and CSS], and one intra-operative variable (DSM) to be independent risk factors of PHLF. The pre-operative nomogram was constructed based on these four pre-operative variables together with total bilirubin. The combined pre- and intra-operative nomogram was constructed by adding the intra-operative DSM. The pre-operative nomogram was better than the conventional models in predicting PHLF. The prediction was further improved with the combined pre- and intra-operative nomogram. The combined pre- and intra-operative nomogram further improved prediction of PHLF when compared with the pre-operative nomogram. Clinicaltrials.gov Identifier: NCT04076631.

Prediction of post-hepatectomy liver failure by preoperative gadoxetate disodium-enhanced magnetic resonance imaging

BackgroundApproximately 15% of patients experience post-hepatectomy liver failure after major hepatectomy. Poor hepatocyte uptake of gadoxetate disodium, a magnetic resonance imaging contrast agent, may be a predictor of post-hepatectomy liver failure. MethodsA retrospective cohort study of patients undergoing major hepatectomy (≥3 segments) with a preoperative gadoxetate disodium-enhanced magnetic resonance imaging was conducted. The liver signal intensity (standardized to the spleen) and the functional liver remnant was calculated to determine if this can predict post-hepatectomy liver failure after major hepatectomy. ResultsIn 134 patients, low signal intensity of the remnant liver standardized by signal intensity of the spleen in post-contrast images was associated with post-hepatectomy liver failure in multiple logistic regression analysis (Odds Ratio 0.112; 95% CI 0.023–0.551). In a subgroup of 33 patients with lower quartile of functional liver remnant, area under the curve analysis demonstrated a diagnostic accuracy of functional liver remnant to predict post-hepatectomy liver failure of 0.857 with a cut-off value for functional liver remnant of 1.4985 with 80.0% sensitivity and 89.3% specificity. ConclusionFunctional liver remnant determined by gadoxetate disodium-enhanced magnetic resonance imaging is a predictor of post-hepatectomy liver failure which may help identify patients for resection, reducing morbidity and mortality.

A Novel Method Using Gadolinium-Ethoxybenzyl Diethylenetriamine Pentaacetate Acid-Enhanced Magnetic Resonance Imaging for Predicting Post-Hepatectomy Liver Failure in Hepatocellular Carcinoma Patients with a Major Portal Vein Tumor Thrombus

Introduction: The usefulness of gadolinium-ethoxybenzyl diethylenetriamine pentaacetate acid-enhanced magnetic resonance imaging (EOB-MRI) in assessing the functional future remnant liver volume (fFRLV) to predict post-hepatectomy liver failure (PHLF) has been previously reported. Herein, we evaluated the efficacy of this technique in patients with hepatocellular carcinoma (HCC) with a major portal vein tumor thrombus (PVTT). Methods: This study included 21 patients with PVTT in the ipsilateral first-order branch (Vp3) and 30 patients with PVTT in the main trunk/contralateral branch (Vp4). To evaluate fFRLV, the signal intensity (SI) of the remnant liver was determined on T1-weighted images, using both conventional and newly developed methods. The fFRLV was calculated using the SI of the remnant liver and muscle, remnant liver volume, and body surface area. Preoperative factors predicting PHLF (≥grade B) in HCC patients with Vp3/4 PVTT were evaluated. Results: In the Vp3 group, we found fFRLV area under the receiver-operating characteristic curves (AUCs) above 0.70 (AUC = 0.875, 0.750) using EOB-MRI results calculated using either the plot or whole method. None of the parameters in the Vp4 group had an AUC greater than 0.70. Conclusion: The fFRLV calculated by EOB-MRI using the whole method can be as useful as the conventional method in predicting PHLF (≥grade B) for HCC patients with Vp3 PVTT.

Evaluation and Prediction of Post-Hepatectomy Liver Failure Using Imaging Techniques: Value of Gadoxetic Acid-Enhanced Magnetic Resonance Imaging.

Despite improvements in operative techniques and perioperative care, post-hepatectomy liver failure (PHLF) remains the most serious cause of morbidity and mortality after surgery, and several risk factors have been identified to predict PHLF. Although volumetric assessment using imaging contributes to surgical simulation by estimating the function of future liver remnants in predicting PHLF, liver function is assumed to be homogeneous throughout the liver. The combination of volumetric and functional analyses may be more useful for an accurate evaluation of liver function and prediction of PHLF than only volumetric analysis. Gadoxetic acid is a hepatocyte-specific magnetic resonance (MR) contrast agent that is taken up by hepatocytes via the OATP1 transporter after intravenous administration. Gadoxetic acid-enhanced MR imaging (MRI) offers information regarding both global and regional functions, leading to a more precise evaluation even in cases with heterogeneous liver function. Various indices, including signal intensity-based methods and MR relaxometry, have been proposed for the estimation of liver function and prediction of PHLF using gadoxetic acid-enhanced MRI. Recent developments in MR techniques, including high-resolution hepatobiliary phase images using deep learning image reconstruction and whole-liver T1 map acquisition, have enabled a more detailed and accurate estimation of liver function in gadoxetic acid-enhanced MRI.

Pre-operative evaluation of spontaneous portosystemic shunts as a predictor of post-hepatectomy liver failure in patients undergoing liver resection for hepatocellular carcinoma

Pre-operative evaluation of spontaneous portosystemic shunts as a predictor of post-hepatectomy liver failure in patients undergoing liver resection for hepatocellular carcinoma

Liver remnant volume to body weight ratio of 0.65% as a lower limit in right hepatic trisectionectomy with bile duct resection

BackgroundPrevious studies have suggested the utility of an indocyanine green plasma clearance rate of the future liver remnant (FLR) (ICGK-F) ≥0.05 in hepatobiliary resection to reduce the surgical risk. The present study aimed to verify whether future liver remnant size rather than ICGK-F matters in extended hepatobiliary resection. MethodsBetween 2004 and 2021, patients who underwent right hepatic trisectionectomy with bile duct resection were included. The effect of the FLR volume-to-body weight ratio (FLR/BW) and ICGK-F on posthepatectomy liver failure was evaluated along with other parameters. ResultsAmong 91 study patients, the median ICGK-F, FLR, and FLR/BW were 0.057 (range, 0.027–0.099), 392 mL (145–705), and 0.78% (0.40–1.37), respectively. Posthepatectomy liver failure occurred in 23 patients. The incidence was 10 (40%) in 25 patients with an ICGK-F <0.05 and 12 (18%) in 65 patients with an ICGK-F ≥0.05 (P = .053); 13 (52%) in 25 patients with a FLR/BW <0.65% and 10 (15%) in 66 patients with a FLR/BW ≥0.65% (P = .001). Multivariate analysis showed that a FLR/BW <0.65% (odds ratio, 11.7; P = .005), age ≥65 years (odds ratio, 31.7; P < .001), and blood loss ≥25 mL/kg (odds ratio, 22.1; P = .004) were independent predictors of posthepatectomy liver failure, but ICGK-F <0.05 was not (P = .499). According to the meeting number of 3 factors, posthepatectomy liver failure incidence was 0 of 22 (0%) in patients with 0 factors, 6 of 43 (14%) in patients with 1, and 17 of 26 (65%) in patients with 2 or 3 (P < .001). ConclusionA FLR/BW ≥0.65% may serve as a volumetric basis to reduce posthepatectomy liver failure after extended hepatobiliary resection.

Balance of Gata3 and Ramp2 in hepatocytes regulates hepatic vascular reconstitution in postoperative liver regeneration

Post-hepatectomy liver failure (PHLF) leads to poor prognosis in patients undergoing hepatectomy, with hepatic vascular reconstitution playing a critical role. However, the regulators of hepatic vascular reconstitution remain unclear. In this study, we aimed to investigate the regulatory mechanisms of hepatic vascular reconstitution and identify biomarkers predicting PHLF in patients undergoing hepatectomy. Candidate genes that were associated with hepatic vascular reconstitution were screened using adeno-associated virus vectors in Alb-Cre-CRISPR/Cas9 mice subjected to partial hepatectomy. The biological activities of candidate genes were estimated using endothelial precursor transfusion and associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) models. The level of candidates was detected in biopsies from patients undergoing ALPPS. Risk factors for PHLF were also screened using retrospective data. Downregulation of Gata3 and upregulation of Ramp2 in hepatocytes promoted the proliferation of liver sinusoidal endothelial cells and hepatic revascularization. Pigment epithelium-derived factor (PEDF) and vascular endothelial growth factor A (VEGFA) played opposite roles in regulating the migration of endothelial precursors from bone marrow and the formation of new sinusoids after hepatectomy. Gata3 restricted endothelial cell function in patient-derived hepatic organoids, which was abrogated by a Gata3 inhibitor. Moreover, overexpression of Gata3 led to higher mortality in ALPPS mice, which was improved by a PEDF-neutralizing antibody. The expression of Gata3/RAMP and PEDF/VEGFA tended to have a negative correlation in patients undergoing ALPPS. A nomogram incorporating multiple factors, such as serum PEDF/VEGF index, was constructed and could efficiently predict the risk of PHLF. The balance of Gata3 and Ramp2 in hepatocytes regulates the proliferation of liver sinusoidal endothelial cells and hepatic revascularization via changes in the expression of PEDF and VEGFA, revealing potential targets for the prevention and treatment of PHLF. In this study, we show that the balance of Gata3 and Ramp2 in hepatocytes regulates hepatic vascular reconstitution by promoting a shift from pigment epithelium-derived factor (PEDF) to vascular endothelial growth factor A (VEGFA) expression during hepatectomy- or ALLPS (associating liver partition and portal vein ligation for staged hepatectomy)-induced liver regeneration. We also identified serum PEDF/VEGFA index as a potential predictor of post-hepatectomy liver failure in patients who underwent hepatectomy. This study improves our understanding of how hepatocytes contribute to liver regeneration and provides new targets for the prevention and treatment of post-hepatectomy liver failure.

Albumin-indocyanine green evaluation of future liver remnant predicts liver failure after anatomical hepatectomy for hepatocellular carcinoma: A dual-center retrospective study.

The albumin-indocyanine green evaluation (ALICE) score is a useful predictor of post-hepatectomy liver failure (PHLF); however, its usefulness in combination with future liver remnant (FLR), measured by 3-D volumetry, has not been investigated. This study aimed to investigate the relationship between the ALICE of the FLR (ALICE-FLR) score and severe PHLF. The clinical data of 215 patients who underwent anatomical hepatectomy for hepatocellular carcinoma without portal vein embolization at two institutes between January 2010 and December 2021 were analyzed retrospectively. PHLF occurrence and severity were determined according to the International Study Group of Liver Surgery's definition. Grades B and C PHLF were defined as severe PHLF. The ALICE-FLR, ALICE scores, and indocyanine green clearance of FLR (ICGK-FLR) were evaluated for severe PHLF prediction. Severe PHLF was observed in 40 patients (18.6%). The areas under the curve (AUCs) for the ALICE-FLR, ALICE scores, ICGK-FLR, and FLR were 0.76, 0.64, 0.73, and 0.69, respectively. The AUC of the ALICE-FLR score was significantly higher than that of the ALICE score. The ALICE-FLR score was identified as an independent predictor of severe PHLF (the odds ratio for every 0.01 increment in the ALICE-FLR score was 1.24; 95% confidence interval, 1.070-1.453; p = 0.004). Among patients with severe PHLF, the ALICE-FLR score was significantly higher in the grade C than in the grade B PHLF group. The combination of liver function models, including indocyanine green, albumin, and FLR is considered compatible for predicting severe PHLF.

Tc-99m mebrofenin hepatobiliary scintigraphy to assess future liver remnant function before major liver surgery.

Assessment of liver function is paramount before hepatectomy. This study aimed to assess future liver remnant function (FLR-F) using hepatobiliary scintigraphy (HBS) and to compare it to FLR volume (FLR-V) in the prediction of posthepatectomy liver failure (PHLF). The impact of volume and function gains were also assessed in patients undergoing portal vein embolization (PVE) or liver venous deprivation (LVD). All consecutive patients undergoing major hepatectomy between 02/2018 and 09/2021 with preoperative HBS were included. FLR-V was expressed as percentage of total liver volume and analyzed using preoperative computed tomography. FLR-V and FLR-F gains after embolization were expressed in percentage. Receiver operating characteristic analysis was performed to compare both methods in predicting PHLF. Thirty-six patients were included. PVE and LVD were performed in 4 (11%) and 28 patients (78%), respectively. Overall, PHLF occurred in eight patients (22%). FLR-F gain after embolization showed significant ability to predict PHLF (area under the curve [AUC] = 0.789), with cut-off value of 150% showing a sensitivity of 1.00, a specificity of 0.42, and a negative predictive value of 1.00. Preoperative HBS shows a high sensitivity to predict PHLF when HBS is performed twice to measure the function gain after venous embolization.

Comparing Outcomes of Minimally Invasive and Open Hepatectomy for Primary Liver Malignancies in Patients with Low-MELD Cirrhosis

IntroductionCirrhotic patients with primary liver cancer may undergo curative-intent resection when selected appropriately. Patients with T1 tumors and low-MELD are generally referred for resection. We aim to evaluate whether minimally invasive hepatectomy (MIH) is associated with improved outcomes versus open hepatectomy (OH). MethodsNSQIP hepatectomy database 2014–2021 was used to select patients with T1 Hepatocellular Carcinoma (HCC) or Intra-hepatic Cholangiocarcionoma (IHCC) and low-MELD cirrhosis (MELD ≤ 10) who underwent partial hepatectomy. Propensity score matching was applied between OH and MIH patients, and 30-day postoperative outcomes were compared. Multivariable regression was used to identify predictors of post-hepatectomy liver failure (PHLF) in the selected population. ResultsThere were 922 patients: 494 (53.6%) OH, 372 (40.3%) MIH, and 56 (6.1%) began MIH converted to OH (analyzed with the OH cohort). We matched 354 pairs of patients with an adequate balance between the groups. MIH was associated with lower rates of bile leak (HR 0.37 [0.19–0.72)], PHLF (HR 0.36 [0.15–0.86]), collections requiring drainage (HR 0.30 [0.15–0.63]), postoperative transfusion (HR 0.36 [0.21–0.61]), major (HR 0.45 [0.27–0.77]), and overall morbidity (HR 0.44 [0.31–0.63]), and a two-day shorter median hospitalization (3 vs. 5 days; HR 0.61 [0.45–0.82]). No difference was noted in operative time, wound, respiratory, and septic complications, or mortality. Regression analysis identified ascites, prior portal vein embolization (PVE), additional hepatectomies, Pringle’s maneuver, and OH (vs. MIH) as independent predictors of PHLF. ConclusionMIH for early-stage HCC/IHCC in low-MELD cirrhotic patients was associated with improved postoperative outcomes over OH. These findings suggest that MIH should be considered an acceptable approach in this population of patients.

Spleen volume is a predictor of posthepatectomy liver failure and short-term mortality for hepatocellular carcinoma.

The study aimed at retrospectively assessing the impact of spleen volume (SpV) on the development of posthepatectomy liver failure (PHLF) in patients who underwent hepatectomy for hepatocellular carcinoma (HCC). 152 patients with primary HCC who underwent hepatectomy (sectionectomy or more) were classified into PHLF and non-PHLF groups, and then the relationship between PHLF and SpV was assessed. SpV (cm3) was obtained from preoperative CT and standardized based on the patient's body surface area (BSA, m2). PHLF was observed in 39 (26%) of the 152 cases. SpV/BSA was significantly higher in the PHLF group, and the postoperative 1-year survival rate was significantly worse in the PHLF group than that in the non-PHLF group (p = 0.044). Multivariable analysis revealed SpV/BSA as a significant independent risk factor for PHLF. Using the cut-off value (160 cm3/m2), the 152 cases were divided into small SpV and large SpV groups. The incidence of PHLF was significantly higher in the large SpV group (p = 0.002), the liver failure-related mortality rate was also significantly higher in the large SpV group (p = 0.007), and the 1-year survival rate was significantly worse in the large SpV group (p = 0.035). These results suggest SpV as a predictor of PHLF and short-term mortality in patients who underwent hepatectomy for HCC. Moreover, SpV measurement is a simple and potentially useful method for predicting PHLF in patients with HCC.

Poresekčná pečeňová nedostatočnosť – skórovacie systémy v klinickej praxi

Summary: Introduction: Posthepatectomy liver failure (PHLF) is still a dreaded disease entity despite medical advances. The primary aim of the work was to retrospectively apply selected scoring systems used to assess the risk of PHLF to a group of patients after major liver resections operated at the authors‘ workplace. We anticipate that the latest scoring systems will provide a more accurate picture of PHLF risk. Methods: Between 2007 and 2016, 82 patients meeting the inclusion criteria (elective removal of three or more liver segments for neoplasm) were identified. Five scoring systems were applied to them, namely: “50-50” criterion, ISGLS classification, Hyder score, ALBI and Liu score. Results: Using the “50-50” criterion, none of the patients reached the diagnosis of PHLF. Applying the ISGLS scoring system, 68 patients (86%) had grade “A” and 11 had grade “B” PHLF on the 5th postoperative day. Hyder‘s score above 11 was achieved by two patients who died on the 14th and 34th postoperative day. In the ALBI score, only one patient achieved a value of more than –1.39 (–0.4), while he died on the second postoperative day. Within the Liu score, 55 patients had a predicted very serious risk of developing PHLF, while 46 patients died with an average survival of 27 months after resection. Of the five applied scoring systems, only in the case of ALBI and Liu scores was a statistically significant difference between subgroups of patients with different degrees of presence or prediction of PHLF. A marginally significant difference in the proportion of genders was also noted within the entire set, with men having a higher chance of death (OR 2.63; 95% CI 0.83–8.32). Discussion: The ALBI scoring system correlates with the literature. It has shown very good prediction in several meta-analyses of cohorts of patients after major liver resection. A significantly positive clinical factor of the use of this system is that it is based on preoperative values of laboratory blood tests and can be proposed as a stable prediction model for short-term results after liver resection. Conclusion: The presented scoring systems still represent a rather heterogeneous view of PHLF. Our work points to the ALBI score as the best scoring system. Consistent stratification of patients and treatment in high-volume centers are key pillars of prevention of PHLF. Key words: hepatectomy – liver failure – liver neoplasm – posthepatectomy liver failure – major liver resection – scoring systems

A deep learning model for prediction of post hepatectomy liver failure after hemihepatectomy using preoperative contrast-enhanced computed tomography: a retrospective study.

Post-hepatectomy liver failure (PHLF) remains clinical challenges after major hepatectomy. The aim of this study was to establish and validate a deep learning model to predict PHLF after hemihepatectomy using preoperative contrast-enhancedcomputed tomography with three phases (Non-contrast, arterial phase and venous phase). 265 patients undergoing hemihepatectomy in Sir Run Run Shaw Hospital were enrolled in this study. The primary endpoint was PHLF, according to the International Study Group of Liver Surgery's definition. In this study, to evaluate the proposed method, 5-fold cross-validation technique was used. The dataset was split into 5 folds of equal size, and each fold was used as a test set once, while the other folds were temporarily combined to form a training set. Performance metrics on the test set were then calculated and stored. At the end of the 5-fold cross-validation run, the accuracy, precision, sensitivity and specificity for predicting PHLF with the deep learning model and the area under receiver operating characteristic curve (AUC) were calculated. Of the 265 patients, 170 patients with left liver resection and 95 patients with right liver resection. The diagnosis had 6 types: hepatocellular carcinoma, intrahepatic cholangiocarcinoma, liver metastases, benign tumor, hepatolithiasis, and other liver diseases. Laparoscopic liver resection was performed in 187 patients. The accuracy of prediction was 84.15%. The AUC was 0.7927. In 170 left hemihepatectomy cases, the accuracy was 89.41% (152/170), and the AUC was 82.72%. The accuracy was 77.47% (141/182) with liver mass, 78.33% (47/60) with liver cirrhosis and 80.46% (70/87) with viral hepatitis. The deep learning model showed excellent performance in prediction of PHLF and could be useful for identifying high-risk patients to modify the treatment planning.

OS-051-YI - MicroRNA based prediction of posthepatectomy liver failure and mortality outperforms established markers of preoperative risk assessment

OS-051-YI - MicroRNA based prediction of posthepatectomy liver failure and mortality outperforms established markers of preoperative risk assessment

Prediction of Post-hepatectomy Liver Failure: New Nomogram Based on Alanine Aminotransferase, Prothrombin Time Activity and Future Remnant Liver Proportion (APART Score)

Prediction of Post-hepatectomy Liver Failure: New Nomogram Based on Alanine Aminotransferase, Prothrombin Time Activity and Future Remnant Liver Proportion (APART Score)

How to implement the hiba index: a low-cost method for assessing future liver remnant function

Background: HIBA index is a novel method based on Hepatobiliary Scintigraphy (HBS) and Spect CT that can accurately predict posthepatectomy liver failure (PHLF) when planning a major liver resection.

A Nomogram Based on Preoperative Lab Tests, BMI, ICG-R15, and EHBF for the Prediction of Post-Hepatectomy Liver Failure in Patients with Hepatocellular Carcinoma

Background: Liver cancer is one of the most common malignant tumors, and worldwide, its incidence ranks sixth, and its morality third. Post-hepatectomy liver failure (PHLF) is the leading cause of death in patients who have undergone liver resection. This retrospective study investigated the risk factors for PHLF by predicting and constructing an index to evaluate the risk. This was achieved by combining the lab tests with an indocyanine green (ICG) clearance test. Methods: The study analyzed 1081 hepatocellular carcinoma (HCC) patients who had received liver resection at Sun Yat-sen University Cancer Center between 2005 and 2020. The patients were divided into a PHLF group (n = 113) and a non-PHLF group (n = 968), according to the International Study Group of Liver Surgery (ISGLS) criteria. Receiver operating characteristics (ROC) curves were then used to estimate the optimal cut-off values. Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors. Finally, a nomogram was constructed where the calibration plot, the areas under the ROC curve (AUC), and the decision curve analysis (DCA) showed good predictive ability. Results: Correlation analysis revealed that body mass index (BMI) was positively correlated with ICG-R15 and with effective hepatic blood flow (EHBF). Univariate and multivariate logistics regression analysis revealed that BMI, ICG-R15, international normalized ratio (INR), tumor size, hepatic inflow occlusion (HIO) time, and operation method were independent predictive factors for PHLF. When these factors and EHBF were included in the nomogram, the nomogram showed a good predictive value, with a C-index of 0.773 (95% Confidence Interval [CI]: 0.729-0.818). The INR had the largest ROC areas (AUC INR = 0.661). Among the variables, ICG-R15 (AUC ICG-R15 = 0.604) and EHBF (AUC EHBF = 0.609) also showed good predictive power. Conclusions: The risk of PHLF in HCC patients can be precisely predicted by this model prior to the operation. By integrating EHBF into the model, HCC patients at higher risk for PHLF can be identified more effectively.

Utility of serum autotaxin levels for predicting post hepatectomy liver failure in hepatocellular carcinoma.

This study aimed to evaluate the usefulness of serum autotaxin, a novel liver fibrosis marker, for predicting post hepatectomy liver failure (PHLF) in patients undergoing hepatectomy for hepatocellular carcinoma (HCC). Autotaxin was measured in sera from 269 patients undergoing hepatectomy for HCC. Correlations between autotaxin level, liver fibrosis stage (METAVIR F0-F4), and PHLF, as assessed by the International Study Group of Liver Surgery criteria, were analyzed. Median autotaxin concentrations correlated significantly with fibrosis stage (F0, 0.93; F1, 0.96; F2, 1.18; F3, 1.40; and F4, 1.47 mg/l; P < .0001). Autotaxin levels were significantly higher in female patients and hepatitis C virus antibody-positive patients compared with male or antibody-negative patients (P < .0001). PHLF grade ≥ B occurred in 25 patients (9.3%). A PHLF prediction model was constructed from four variables (autotaxin, resection rate, sex, and hepatitis C virus antibody positivity) and gave an area under the receiver operating characteristic curve of 0.8 (95% confidence interval [CI]: 0.69-0.87), which was superior to models based on ALPlat and resection rate (0.75, 95% CI: 0.64-0.83) or indocyanine green retention test and resection rate (0.72, 95% CI: 0.61-0.81). Serum autotaxin has utility for predicting liver fibrosis and PHLF in patients with HCC.