Value of Preoperative Indocyanine Green Clearance Test for Predicting Post-Hepatectomy Liver Failure in Noncirrhotic Patients

Interpretable machine learning model for predicting post-hepatectomy liver failure in hepatocellular carcinoma

Post-hepatectomy liver failure (PHLF) is a severe complication following liver surgery. We aimed to develop a novel, interpretable machine learning (ML) model to predict PHLF. We enrolled 312 hepatocellular carcinoma (HCC) patients who underwent hepatectomy, and 30% of the samples were utilized for internal validation. Variable selection was performed using the least absolute shrinkage and selection operator regression in conjunction with random forest and recursive feature elimination (RF-RFE) algorithms. Subsequently, 12 distinct ML algorithms were employed to identify the optimal prediction model. The area under the receiver operating characteristic curve, calibration curves, and decision curve analysis (DCA) were utilized to assess the model's predictive accuracy. Additionally, an independent prospective validation was conducted with 62 patients. The SHapley Additive exPlanations (SHAP) analysis further explained the extreme gradient boosting (XGBoost) model. The XGBoost model exhibited the highest accuracy with AUCs of 0.983 and 0.981 in the training and validation cohorts among 12 ML models. Calibration curves and DCA confirmed the model's accuracy and clinical applicability. Compared with traditional models, the XGBoost model had a higher AUC. The prospective cohort (AUC = 0.942) further confirmed the generalization ability of the XGBoost model. SHAP identified the top three critical variables: total bilirubin (TBIL), MELD score, and ICG-R15. Moreover, the SHAP summary plot was used to illustrate the positive or negative effects of the features as influenced by XGBoost. The XGBoost model provides a good preoperative prediction of PHLF in patients with resectable HCC.

Predictive Value of Preoperative ICG-R15 Testing in Post-hepatectomy Liver Failure Following Major Liver Resection: Indian Experience

Surgical resection stands as the preeminent therapeutic approach for both primary hepatocellular carcinoma and metastatic liver malignancies. Its efficacy is contingent upon the attainment of a comprehensive excision while ensuring a sufficient future liver remnant (FLR). However, post-hepatectomy liver failure (PHLF) remains a significant challenge, particularly in patients with preexisting liver disease. The present study aims to investigate the predictive value of the preoperative indocyanine green retention test at 15 min (ICG-R15) in identifying patients at risk of PHLF following major liver resection. This retrospective review focused on patients who underwent the ICG-R15 test before major liver resection between August 2021 and January 2023. All patients underwent standard preoperative evaluation and staging. Patients with primary or metastatic liver cancer planned for major resection and undergoing ICG-R15 were included in the study. Patients with elevated serum bilirubin (> 3 mg/dl) and those not undergoing liver resection or minor liver resection (< 3 segments) were excluded from the study. PHLF was defined by the International Study Group of Liver Surgery (ISGLS) criteria. Follow-up was performed to identify 90-day morbidity. Using univariate and multivariate logistic regression analyses, we confirmed independent risk parameters that predicted postoperative major complications and severe PHLF. The study included 72 patients who underwent preoperative ICG-R15 testing prior to major liver resection. PHLF occurred in 28 patients (38.9%), with 24 patients (33.3%) classified as severity score B and 3 patients (4.16%) had severity score C. Univariate analysis revealed future liver remnant (FLR), ICG-R15, and blood transfusion as predictors of PHLF. Multivariate analysis confirmed FLR (p = 0.019) and ICG-R15 (p = 0.032) as significant predictors. Receiver operating characteristic curve analysis yielded an area under the curve of 0.642 for ICG-R15 in predicting PHLF. An optimal cut-point of 7.5 was determined. Our study highlights the importance of preoperative risk assessment of liver function evaluation using the ICG-R15 test, to predict the risk of PHLF following liver resection. Implementing appropriate interventions, especially in patients with borderline FLR, can improve surgical outcomes and enhance patient safety. Further research and prospective studies are essential to refine risk prediction models and improve rates of PHLF after liver resections.

In vivo evaluation of liver function by multimodal imaging in an alcohol-induced liver injury model

Background

Visually evaluating liver function is a hot topic in hepatology research. There are few reliable and practical visualization methods for evaluating the liver function in vivo in experimental studies. In this study, we established a multimodal imaging approach for in vivo liver function evaluation and compared healthy mice with chronic alcoholic liver injury (cALI) model mice to explore its potential applicability in experimental research.

Methods

In vivo fluorescence imaging (IVFI) technology was utilized to visually represent the clearance of indocyanine green from the liver of both healthy mice and mice with cALI. The reserve liver function was evaluated via IVFI using the Cy5.5-galactosylated polylysine probe, which targets the asialoglycoprotein receptor of hepatocytes. Hepatic microcirculation was assessed through laser speckle perfusion imaging of hepatic blood perfusion. The liver microstructure was then investigated by in vivo confocal laser endomicroscopy imaging. Finally, hepatic asialoglycoprotein receptor expression, histology, and the levels of serum alanine aminotransferase and aspartate aminotransferase were measured.

Results

In vivo multimodal imaging results intuitively and dynamically showed that indocyanine green clearance [mean ± standard deviation (SD): 30.83±14.71, 95% confidence interval (CI): 20.3 to 41.35], the fluorescence signal intensity (mean ± SD: 1,217.92±117.63; 95% CI: 1,148.38 to 1,290.84) and fluorescence aggregation area (mean ± SD: 5,855.80±1,271.81; 95% CI: 5,051.57 to 6,653.88) of Cy5.5-galactosylated polylysine targeting the asialoglycoprotein receptor, and hepatic blood perfusion (mean ± SD: 1,494.86±299.33; 95% CI: 1,316.98 to 1,690.16) in model mice were significantly lower than those in healthy mice (all P<0.001). Compared to healthy mice, the model mice exhibited a significant decline in liver asialoglycoprotein receptor expression (mean ± SD: 219.03±16.34; 95% CI: 208.97 to 230.69; P<0.001), increased serum alanine aminotransferase (mean ± SD: 149.70±47.89 U/L; 95% CI: 81.75 to 128.89; P=0.01) and aspartate aminotransferase levels (mean ± SD: 106.30±36.13 U/L; 95% CI: 122.01 to 180.17; P=0.021), hepatocyte swelling and deformation, disappearance of the hepatic cord structure, partial necrosis, and disintegration of hepatocytes. The imaging features of fluorescence signals in liver regions, hepatic blood perfusion and microstructure were biologically related to hepatic asialoglycoprotein receptor expression, serum indices of liver function, and histopathology in model mice.

Conclusions

Utilizing in vivo multimodal imaging technology to assess liver function is a viable approach for experimental research, providing dynamic and intuitive visual evaluations in a rapid manner.

Preoperative indocyanine green (ICG) clearance test: Can we really trust it to predict post hepatectomy liver failure? A systematic review of the literature and meta-analysis of diagnostic test accuracy

INTRODUCTION

Post hepatectomy liver failure (PHFL) still represents a potentially fatal complication after major liver resection. Indocyanine green (ICG) clearance test represents one of the most widely adopted examinations in the preoperative workup. Despite a copious body of evidence which has been published on this topic, the role of ICG in predicting PHLF is still a matter of debate.

METHODS

A systematic review of the literature was conducted according to PRISMA-DTA guidelines. The primary outcome was the assessment of diagnostic performance of ICG in predicting PHLF. The secondary outcome was the mean ICG_R15 and ICG_PDR in patients experiencing PHLF.

RESULTS

Seventeen studies, for a total of 4852 patients, were deemed eligible. Sensitivity ranged from 25% to 83%; Specificity ranged from 66.1% to 93.8%. ICG clearance test pooled AUC was 0.673 (95% CI: 0.632-0.713). The weighted mean ICG_R15 was 11 (95%CI: 8.3-13.7). The weighted mean ICG_PDR was 16.5 (95%CI: 13.3-19.8). High risk of bias was detected in all examined domains.

CONCLUSIONS

Preoperative ICG clearance test alone may not represent a reliable method to predict post hepatectomy liver failure. Its diagnostic significance should be framed within multiparametric models involving clinical and imaging features.

Minimizing the risk of small-for-size syndrome after liver surgery

BACKGROUND

Primary and secondary liver tumors are not always amenable to resection due to location and size. Inadequate future liver remnant (FLR) may prevent patients from having a curative resection or may result in increased postoperative morbidity and mortality from complications related to small-for-size syndrome (SFSS).

DATA SOURCES

This comprehensive review analyzed the principles, mechanism and risk factors associated with SFSS and presented current available options in the evaluation of FLR when planning liver surgery. In addition, it provided a detailed description of specific modalities that can be used before, during or after surgery, in order to optimize the conditions for a safe resection and minimize the risk of SFSS.

RESULTS

Several methods which aim to reduce tumor burden, preserve healthy liver parenchyma, induce hypertrophy of FLR or prevent postoperative complications help minimize the risk of SFSS.

CONCLUSIONS

With those techniques the indications of radical treatment for patients with liver tumors have significantly expanded. The successful outcome depends on appropriate patient selection, the individualization and modification of interventions and the right timing of surgery.

Variations between the anatomical and functional distribution, based on 99m technetium -mebrofinate SPECT-CT scan, in patients at risk of post hepatectomy liver failure

BACKGROUND

The aim of the current study is to investigate the variations of anatomical (LVRem%) and functional remnant volumes (fLVRem%) and the dynamic uptake of Technetium-Mebrofinate (FRLF) measured from 99m Technetium-Mebrofinate SPECT-CT scan (TMSCT) in patients at high risk of post-hepatectomy liver failure (PHLF).

METHODS

Variations in the measures of LVRem% and fLVRem% were assessed. The predictive accuracies of LVRem%, fLVRem% and FRLF with respect to PHLF were reported.

RESULTS

From the N = 92 scans performed, LVRem% and fLVRem% returned identical results in 15% of cases, and ±10 percentage points in 79% of cases. Some patients had larger discrepancies, with difference of >10 percentage points in 21% of cases. The difference was significant in those with primary liver cancers (-4.4 ± 9.2, p = 0.002). For the N = 29 patients that underwent surgery as planned on TMSCT, FRLF was a strong predictor of PHLF, with an AUROC of 0.83 (p = 0.005).

CONCLUSION

TMSCT is emerging as a useful modality in pre-operative assessment of patients undergoing major liver resection. For those with primary liver cancer, there is a significant variation in the anatomical and functional distributions that needs considered in surgical planning. Reduced FRLF, measured as the dynamic uptake in the future liver remnant, is a strong predictor of PHLF.

A Nomogram Based on Preoperative Inflammatory Indices and ICG-R15 for Prediction of Liver Failure After Hepatectomy in HCC Patients

Objective

To establish a nomogram based on inflammatory indices and ICG-R15 for predicting post-hepatectomy liver failure (PHLF) among patients with resectable hepatocellular carcinoma (HCC).

Methods

A retrospective cohort of 407 patients with HCC hospitalized at Xiangya Hospital of Central South University between January 2015 and December 2020, and 81 patients with HCC hospitalized at the Second Xiangya Hospital of Central South University between January 2019 and January 2020 were included in the study. Totally 488 HCC patients were divided into the training cohort (n=378) and the validation cohort (n=110) by random sampling. Univariate and multivariate analysis was performed to identify the independent risk factors. Through combining these independent risk factors, a nomogram was established for the prediction of PHLF. The accuracy of the nomogram was evaluated and compared with traditional models, like CP score (Child-Pugh), MELD score (Model of End-Stage Liver Disease), and ALBI score (albumin-bilirubin) by using receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).

Results

Cirrhosis (OR=2.203, 95%CI:1.070-3.824, P=0.030), prothrombin time (PT) (OR=1.886, 95%CI: 1.107-3.211, P=0.020), tumor size (OR=1.107, 95%CI: 1.022-1.200, P=0.013), ICG-R15% (OR=1.141, 95%CI: 1.070-1.216, P<0.001), blood loss (OR=2.415, 95%CI: 1.306-4.468, P=0.005) and AST-to-platelet ratio index (APRI) (OR=4.652, 95%CI: 1.432-15.112, P=0.011) were independent risk factors of PHLF. Nomogram was built with well-fitted calibration curves on the of these 6 factors. Comparing with CP score (C-index=0.582, 95%CI, 0.523-0.640), ALBI score (C-index=0.670, 95%CI, 0.615-0.725) and MELD score (C-ibasedndex=0.661, 95%CI, 0.606-0.716), the nomogram showed a better predictive value, with a C-index of 0.845 (95%CI, 0.806-0.884). The results were consistent in the validation cohort. DCA confirmed the conclusion as well.

Conclusion

A novel nomogram was established to predict PHLF in HCC patients. The nomogram showed a strong predictive efficiency and would be a convenient tool for us to facilitate clinical decisions.

A novel online calculator based on noninvasive markers (ALBI and APRI) for predicting post-hepatectomy liver failure in patients with hepatocellular carcinoma

BACKGROUND AND AIM

Post-hepatectomy liver failure (PHLF) remains the primary cause of in-hospital mortality after hepatectomy. Identifying predictors of PHLF is important to improve surgical safety. We sought to identify the predictive accuracy of two noninvasive markers, albumin-bilirubin (ALBI) and aspartate aminotransferase to platelet count ratio index (APRI), to predict PHLF among patients with hepatocellular carcinoma (HCC), and to build up an online prediction calculator.

METHODS

Patients who underwent resection for HCC between 2013 and 2016 at 6 Chinese hospitals were retrospectively analyzed. The independent predictors of PHLF were identified using univariate and multivariate analyses; derivative data were used to construct preoperative and postoperative nomogram models. Receiver operating characteristic (ROC) curves for the two predictive models, and ALBI, APRI, Child-Pugh, model for end-stage liver disease (MELD) scores were compared relative to predictive accuracy for PHLF.

RESULTS

Among the 767 patients in the analytic cohort, 102 (13.3%) experienced PHLF. Multivariable logistic regression analysis identified high ALBI grade (>-2.6) and high APRI grade (>1.5) as independent risk factors associated with PHLF in both the preoperative and postoperative models. Two nomogram predictive models and corresponding web-based calculators were subsequently constructed. The areas under the ROC curves for the postoperative and preoperative models, APRI, ALBI, MELD and Child-Pugh scores in predicting PHLF were 0.844, 0.789, 0.626, 0.609, 0.569, and 0.560, respectively.

CONCLUSIONS

ALBI and APRI demonstrated more accurate ability to predict PHLF than Child-Pugh and MELD. Two online calculators that combined ALBI and APRI were proposed as useful preoperative and postoperative tools for individually predicting the occurrence of PHLF among patients with HCC.

Comparison between preoperative two-dimensional shear wave elastography and indocyanine green clearance test for prediction of post-hepatectomy liver failure

BACKGROUND

Post-hepatectomy liver failure (PHLF) is one of the most serious complications and major causes of liver resection mortality. The purpose of this study is to investigate and compare the performance of preoperative two-dimensional shear wave elastography (2D-SWE) and the indocyanine green (ICG) clearance test for the prediction of PHLF.

METHODS

A total of 172 consecutive patients who were undergoing major liver resection were prospectively identified. Patients were evaluated by preoperative 2D-SWE and ICG clearance test. According to the International Study Group of Liver Surgery (ISGLS) recommendations, No PHLF, PHLF A, PHLF B, and PHLF C group classifications were defined. The differences in liver stiffness value (LSV) and ICG retention rate at 15 minutes (ICGR15) among the different PHLF classifications were investigated. The performance of LSV and ICGR15 for diagnosing different classifications of PHLF was compared.

RESULTS

PHLF occurred in 43 (25.0%) patients, and 24 (14.0%) patients were grade A, 14 (8.1%) were grade B, and 5 (2.9%) were grade C. Both LSV and ICGR15 of the PHLF C group were significantly higher than those of the No PHLF group (P=0.025, P=0.001, respectively). According to univariate and multivariate logistic regression analysis, LSV and ICGR15 were significantly related to PHLF (P=0.051, P=0.084, respectively). For diagnosis of ≥ PHLF A, ≥ PHLF B, and ≥ PHLF C, the areas under the receiver operating characteristic curve (AUCs) for 2D-SWE were 0.624 [95% confidence interval (CI): 0.536-0.712, P=0.015], 0.699 (95% CI: 0.576-0.821, P=0.005), and 0.831 (95% CI: 0.737-0.925, P=0.01), respectively. The AUCs of the ICG clearance test were 0.631 (95% CI: 0.542-0.721, P=0.01), 0.570 (95% CI: 0.436-0.704, P=0.32), and 0.717 (95% CI: 0.515-0.920, P=0.098), respectively. The AUC of LSV for the diagnosis of ≥ PHLF A was comparable to that of ICGR15 (P=0.17). The AUCs of LSV were significantly higher than those of ICGR15 for the diagnosis of ≥ PHLF B (P=0.002) and C (P=0.038).

CONCLUSIONS

2D-SWE demonstrates the potential to aid in the prediction of the severity of PHLF. Our findings also suggest that the performance of 2D-SWE is better than the ICG clearance test.

Comparison of preoperative two-dimensional shear wave elastography, indocyanine green clearance test and biomarkers for post hepatectomy liver failure prediction in patients with hepatocellular carcinoma

BACKGROUND

The preoperative prediction of post hepatectomy liver failure (PHLF) is essential, but there is no gold standard for the prediction at present, and the efficacy of different methods for the prediction has not been compared systematically. In this study, we aimed to compare the efficacy of preoperative two-dimensional shear wave elastography (2D-SWE), indocyanine green (ICG) clearance test and biomarkers for PHLF prediction in patients with hepatocellular carcinoma (HCC).

METHODS

We retrospectively studied 215 patients with HCC, who had undergone major liver resection in our hospital. Preoperative data of each patient, including liver stiffness value (LSV) of underlying hepatic parenchyma measured by 2D-SWE, ICG retention rate at 15 min (ICG-R15) measured by ICG clearance test, albumin-bilirubin (ALBI) scores, aspartate aminotransferase-platelet ratio index (APRI), and Fibrosis-4 (FIB-4) were collected for analysis. Post hepatectomy outcomes of study patients were also recorded for assessment of PHLF. The study patients were divided into development cohort (133 patients without PHLF, and 17 patients with PHLF) and validation cohort (59 patients without PHLF, and 6 patients with PHLF) randomly.

RESULTS

In the development cohort, LSV, ICG-R15 and ALBI scores were significantly different between patients with and without PHLF, while no significant difference of APRI and FIB-4 scores was found. LSV had higher AUC (the area under the receiver operating characteristic curve) (AUC = 0.795) for PHLF prediction than ICG-R15 (AUC = 0.619) and ALBI scores (AUC = 0.686) (p < 0.05 for all comparisons). In the validation cohort, the cutoff value of LSV obtained from the development cohort, 10.35 kPa,  revealed higher specificity (76.3%) for PHLF prediction than ICG-R15 (specificity: 66.1%) and ALBI scores (specificity: 69.5%) (p < 0.0001).

CONCLUSIONS

Compared with ICG-R15, ALBI scores, APRI and FIB-4, LSV measured by 2D-SWE may demonstrate better efficacy for preoperative PHLF prediction in patients with HCC.

Hepatic function assessment to predict post-hepatectomy liver failure: what can we trust? A systematic review

Post hepatectomy liver failure (PHLF) could occur even though an adequate liver volume is preserved. Liver function is not strictly related to the volume and the necessity to pre-operatively predict the future liver remnant (FLR) function is emerging, together with the wide spreading of techniques, aiming to optimize the FLR. The aim of this study was to systematically review all the available tests, to pre-operatively assess the liver function and to estimate the risk of PHLF. A systematic literature research of Medline, Embase, Scopus was performed in accordance to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, to identify all the studies available for pre-operative liver function tests to assess the risk of PHLF and/or complications. From the 1122 references retrieved, 79 were included in the review. Dynamic functional tests, such as indocyanine green test (ICG), could evaluate only global liver function, with no definition of functional capacity of the remnant. Magnetic resonance imaging (MRI) with liver-specific contrast agents enables both liver function and volume evaluation; the absence of ionizing radiation showed a better patient's compliance. Nuclear imaging studies as hepatobiliary scintigraphy (HBS) present the unique ability to allow a precise evaluation of the segmental liver function of the remnant liver. Liver volume could overestimate liver function. Several liver function tests are available to evaluate the risk of PHLF in the pre-operative setting. However, no single test alone could accurately predict PHLF. Pre-operative combination between a dynamic quantitative test, such as ICG, with MRI or HBS, should enable a more complete functional evaluation. Functional tests to predict PHLF should be chosen according to patient's characteristics, disease, and center experience.

Value of contrast-enhanced ultrasound for preoperative assessment of liver reserve function in patients with liver tumors

This study aimed to investigate the value of contrast-enhanced ultrasound (CEUS) for preoperative assessment of liver reserve function in patients with liver tumors. The indocyanine green (ICG) clearance tests and CEUS examinations of 45 noncirrhotic patients with liver tumors were performed prior to liver resection. Parameters time to peak (TtoPk), arrival time (Atm) as well as perfusion parameters A, k and A x k were generated from time-intensity curve (TIC) of CEUS. The correlation analyses of the ICG clearance per unit time (ICGK) and the retention rate at 15 min (ICGR15) with TtoPk, Atm, A, k and A x k were performed, and the diagnostic ability as well as optimal cut-off values of TtoPk and Atm for differentiating patients with ICGR15>10% from ICGR15<10% were analyzed. There were significant correlations of ICGK with TtoPk and Atm, and the correlation coefficients were 0.363 (p = 0.014) and -0.482 (p = 0.001), respectively. Significant correlations of ICGR15 with TtoPk and Atm were revealed, and the correlation coefficients were -0.416 (p = 0.004) and 0.303 (p = 0.043), respectively. No correlation of ICGK or ICGR15 with A, k and A x k was found in this study. There were significant differences in TtoPk and Atm between patients with ICGR15>10% and ICGR15<10% (p = 0.028 and p = 0.026, respectively). TtoPk and Atm both had good diagnostic abilities in diagnosing patients with ICGR15>10% verusus ICGR15<10% (AUROC = 0.711 and 0.721, respectively). For ICGR15>10% vs ICGR15, the optimal cut-off values of TtoPk and Atm were 13.307 s and 11.007 s, respectively, while the sensitivity and specificity were 75.0% and 72.7%, 60.6% and 75.0%, respectively. This study revealed that CEUS has the potential to be a new method to evaluate the liver reserve function of patients. With the optimal cut-off values of TtoPk and Atm, qualitative assessment of patients with ICGR15>10% could be more easily achieved by CEUS with good diagnostic abilities.

The role of imaging in prediction of post-hepatectomy liver failure

Post-hepatectomy liver failure (PHLF) is not only a leading cause of mortality but also a leading cause of life-threatening complications in patients undergoing liver resection. The ability to accurately detect the emergence of PHLF represents a crucially important step. Currently, PHLF can be predicted by a comprehensive evaluation of biological, clinical, and anatomical parameters. With the development of new technologies, imaging methods including elastography, diffusion-weighted magnetic resonance imaging, and gadolinium ethoxybenzyl diethylenetriaminepentaacetic acid-enhanced MRI play a more significant role in the pre-operative prediction and assessment of PHLF. In this review, we summarize the mainstream studies, with the aim of evaluating the role of imaging and improving the clinical value of existing scoring systems for predicting PHLF.