From LI-RADS Classification to HCC Pathology: A Retrospective Single-Institution Analysis of Clinico-Pathological Features Affecting Oncological Outcomes after Curative Surgery

Background: The latest Liver Imaging Reporting and Data System (LI-RADS) classification by the American College of Radiology has been recently endorsed in the American Association for the Study of Liver Disease (AASLD) guidelines for Hepatocellular carcinoma (HCC) management. Although the LI-RADS protocol has been developed as a diagnostic algorithm, there is some evidence concerning a possible correlation between different LI-RADS classes and specific pathological features of HCC. We aimed to investigate such radiological/pathological correlation and the possible prognostic implication of LI-RADS on a retrospective cohort of HCC patients undergoing surgical resection. Methods: We performed a retrospective analysis of the pathological characteristics of resected HCC, exploring their distribution among different LI-RADS classes and analyzing the risk factors for recurrence-free, overall and cancer-specific survival Results: LI-RADS-5 (LR-5) nodules showed a higher prevalence of microvascular invasion (MVI), satellitosis and capsule infiltration, as well as higher median values of alpha-fetoprotein (αFP) compared to LI-RADS-3/4 (LR-3/4) nodules. MVI, αFP, satellitosis and margin-positive (R1) resection resulted as independent risk factors for recurrence-free survival, while LI-RADS class did not exert any significant impact. Focusing on overall survival, we identified patient age, Eastern Cooperative Oncology Group performance status (ECOG-PS), Model for End Stage Liver Disease (MELD) score, αFP, MVI, satellitosis and R1 resection as independent risk factors for survival, without any impact of LI-RADS classification. Last, MELD score, log10αFP, satellitosis and R1 resection resulted as independent risk factors for cancer-specific survival, while LI-RADS class did not exert any significant impact. Conclusions: Our results suggest an association of LR-5 class with unfavorable pathological characteristics of resected HCC; tumor histology and underlying patient characteristics such as age, ECOG-PS and liver disease severity exert a significant impact on postoperative oncological outcomes.

Machine Learning Applied to Omics Datasets Predicts Mortality in Patients with Alcoholic Hepatitis

Alcoholic hepatitis is a major health care burden in the United States due to significant morbidity and mortality. Early identification of patients with alcoholic hepatitis at greatest risk of death is extremely important for proper treatments and interventions to be instituted. In this study, we used gradient boosting, random forest, support vector machine and logistic regression analysis of laboratory parameters, fecal bacterial microbiota, fecal mycobiota, fecal virome, serum metabolome and serum lipidome to predict mortality in patients with alcoholic hepatitis. Gradient boosting achieved the highest AUC of 0.87 for both 30-day mortality prediction using the bacteria and metabolic pathways dataset and 90-day mortality prediction using the fungi dataset, which showed better performance than the currently used model for end-stage liver disease (MELD) score.

Impact of Aspartate Aminotransferase–to–platelet Ratio Index Based Score to Assess Posthepatectomy Liver Failure in Patients With Hepatocellular Carcninoma

Background: Posthepatectomy liver failure (PHLF) is a life-threatening complication following hepatic resection. The aspartate aminotransferase-to-platelet ratio index (APRI) is a noninvasive model for assessing the liver functional reserve in patients with hepatocellular carcinoma (HCC). This study aimed to establish a scoring model to stratify patients with HCC at risk for PHLF.Methods: This single-center retrospective study included 451 patients who underwent hepatic resection for HCC between 2004 and 2017. Preoperative factors, including noninvasive liver fibrosis markers and intraoperative factors, were evaluated. The predictive impact for PHLF was evaluated using receiver operating characteristic (ROC) curves of these factors.Results: Of 451 patients, 30 (6.7%) developed severe PHLF (grade B/C). Multivariate logistic analysis indicated that APRI, model for end-stage liver disease (MELD) score, operating time, and intraoperative blood loss were significantly associated with severe PHLF. A scoring model (over 0–4 points) was calculated using these optimal cutoff values. The area under the ROC curve of the established score for severe PHLF was 0.88, which greatly improved the predictive accuracy compared with these factors alone (p < 0.05 for all). Conclusions: The scoring model-based APRI, MELD score, operating time, and intraoperative blood loss can predict severe PHLF in patients with HCC.

Demographic Profile and Clinical Spectrum of Alcoholic Liver Disease among Males in Pakistan

Introduction: Alcohol is the most common substance abused in western world. Males tend to have more severe liver disease because of heavy and regular drinking. Methods: Adult patients, 16 years of age and older, diagnosed with ALD within 1 year, were included in the study. Liver disease from other causes was excluded. Demographic profiles, clinical features, laboratory and endoscopic findings of the patients, Child-Turcotte-Pugh (CTP), Model End Stage Liver Disease (MELD) were recorded. Results: A total of 104 patients with ALD who met the inclusion criteria were enrolled in the study. The mean age of the patients enrolled in the study was 49.2 years (SD = 13.1). Most of the patients were in the 30-65 age group. The four most common clinical symptoms in patients were abdominal distension (n = 89, 85.6%), bilateral lower limb edema (n = 78, 75%), jaundice (n = 39, 37.5%) and anorexia (n = 41, 39.4%). Of 104 patients, 96 (92.3%) had cirrhosis, 9 (8.7%) had fatty liver and alcoholic hepatitis. Of 94 patients with ALD, 49(52.1%) had CTP grade C and 83 (88.3%) had MELD score ≥ 16. Conclusions: ALD was mainly observed in young patients. The most common clinical symptoms were abdominal distension, bilateral oedema of the lower limbs, jaundice and anorexia. Among patients with cirrhosis of the liver, the majority of patients were CTP class C and obtained a MELD score ≥16. Keywords: Alcoholic liver disease, clinical profile, demographic profile

Race/Ethnicity Is Not Independently Associated with Risk of Adverse Waitlist Removal among Patients with HCC Exception Points

(1) Background: Since 2015, exception points have been awarded to appropriate candidates after six months of waitlist time to allow more equitable access to liver transplants regardless of hepatocellular carcinoma status. However, it remains unknown whether racial disparities in outcomes among waitlisted patients remain after the introduction of a 6-month waiting period for exception points. (2) Methods: Using the United Network for Organ Sharing database, we identified 2311 patients diagnosed with hepatocellular carcinoma listed for liver transplant who received exception points from 2015 to 2019. The outcome of interest was waitlist survival defined as the composite outcome of death or removal for clinical deterioration. Competing risk analysis was used to identify factors associated with death or removal for clinical deterioration. The final model adjusted for age, sex, race/ethnicity, blood type, diabetes, obesity, laboratory MELD score, tumor size, AFP, locoregional therapies, UNOS region, and college education. (3) Results: No difference was found in the risk of adverse waitlist removal among ethnic/racial groups.

Liver Transplantation – A Case Report

Liver transplantation is a treatment option for patients with End-stage Liver disease for whom all possible modes of surgical and medical treatment have been exhausted. The indications for Liver transplantation can be either acute or chronic liver disease. The absolute contra indications are active alcohol or substance abuse, severe cardiopulmonary or other co morbid conditions that would preclude meaningful recovery after transplant. Patients are listed on the waiting list according to their blood type and Model of End- Stage Liver Disease (MELD) score. The surgical procedure entails the excision of both donor and recipient livers and transplantation of the donor liver into the recipient (Orthotopic Liver Transplantation). This article gives an overview about liver transplantation and its management. A case report is presented and the nursing care has been discussed in detail.

CT radiomics nomogram for the preoperative prediction of severe post-hepatectomy liver failure in patients with huge (≥ 10 cm) hepatocellular carcinoma

Background This study aimed to establish a radiomics-based nomogram for predicting severe (grade B or C) post-hepatectomy liver failure (PHLF) in patients with huge (≥ 10 cm) hepatocellular carcinoma (HCC). Methods One hundred eighty-six patients with huge HCC (training dataset, n = 131 and test dataset, n = 55) that underwent curative hepatic resection were included in this study. The least absolute shrinkage and selection operator (LASSO) approach was applied to develop a radiomics signature for grade B or C PHLF prediction using the training dataset. A multivariable logistic regression model was used by incorporating radiomics signature and other clinical predictors to establish a radiomics nomogram. Decision tree analysis was performed to stratify the risk for severe PHLF. Results The radiomics signature consisting of nine features predicted severe PHLF with AUCs of 0.766 and 0.745 for the training and test datasets. The radiomics nomogram was generated by integrating the radiomics signature, the extent of resection and the model for end-stage liver disease (MELD) score. The nomogram exhibited satisfactory discrimination ability, with AUCs of 0.842 and 0.863 for the training and test datasets, respectively. Based on decision tree analysis, patients were divided into three risk classes: low-risk patients with radiomics score < -0.247 and MELD score < 10 or radiomics score ≥ − 0.247 but underwent partial resections; intermediate-risk patients with radiomics score < − 0.247 but MELD score ≥10; high-risk patients with radiomics score ≥ − 0.247 and underwent extended resections. Conclusions The radiomics nomogram could predict severe PHLF in huge HCC patients. A decision tree may be useful in surgical decision-making for huge HCC hepatectomy.