Faculty Opinions recommendation of Hepatocellular Carcinoma and Non-Alcoholic Fatty Liver Disease: A Step Forward for Better Evaluation Using Ultrasound Elastography.

The increasing prevalence of non-alcoholic fatty liver disease (NAFLD) in the general population prompts for a quick response from physicians. As NAFLD can progress to liver fibrosis, cirrhosis, and even hepatocellular carcinoma (HCC), new non-invasive, rapid, cost-effective diagnostic methods are needed. In this review, we explore the diagnostic performance of ultrasound elastography for non-invasive assessment of NAFLD and NAFLD-related HCC. Elastography provides a new dimension to the conventional ultrasound examination, by adding the liver stiffness quantification in the diagnostic algorithm. Whilst the most efficient elastographic techniques in staging liver fibrosis in NAFLD are vibration controlled transient elastography (VCTE) and 2D-Shear wave elastography (2D-SWE), VCTE presents the upside of assessing steatosis through the controlled attenuation parameter (CAP). Hereby, we have also critically reviewed the most important elastographic techniques for the quantitative characterization of focal liver lesions (FLLs), focusing on HCC: Point shear wave elastography (pSWE) and 2D-SWE. As our paper shows, elastography should not be considered as a substitute for FLL biopsy because of the stiffness values overlap. Furthermore, by using non-invasive, disease-specific surveillance tools, such as US elastography, a subset of the non-cirrhotic NAFLD patients at risk for developing HCC can be detected early, leading to a better outcome. A recent ultrasomics study exemplified the wide potential of 2D-SWE to differentiate benign FLLs from malignant ones, guiding the clinician towards the next steps of diagnosis and contributing to better long-term disease surveillance.

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Performance of Ultrasound Techniques and the Potential of Artificial Intelligence in the Evaluation of Hepatocellular Carcinoma and Non-Alcoholic Fatty Liver Disease

Cancers ◽

10.3390/cancers13040790 ◽

2021 ◽

Vol 13 (4) ◽

pp. 790

Author(s):

Monica Lupsor-Platon ◽

Teodora Serban ◽

Alexandra Iulia Silion ◽

George Razvan Tirpe ◽

Alexandru Tirpe ◽

...

Keyword(s):

Artificial Intelligence ◽

Hepatocellular Carcinoma ◽

Liver Disease ◽

Fatty Liver ◽

Fatty Liver Disease ◽

Liver Lesion ◽

Focal Liver Lesion ◽

Ultrasound Contrast Agents ◽

Alcoholic Fatty Liver ◽

Alcoholic Fatty Liver Disease

Global statistics show an increasing percentage of patients that develop non-alcoholic fatty liver disease (NAFLD) and NAFLD-related hepatocellular carcinoma (HCC), even in the absence of cirrhosis. In the present review, we analyzed the diagnostic performance of ultrasonography (US) in the non-invasive evaluation of NAFLD and NAFLD-related HCC, as well as possibilities of optimizing US diagnosis with the help of artificial intelligence (AI) assistance. To date, US is the first-line examination recommended in the screening of patients with clinical suspicion of NAFLD, as it is readily available and leads to a better disease-specific surveillance. However, the conventional US presents limitations that significantly hamper its applicability in quantifying NAFLD and accurately characterizing a given focal liver lesion (FLL). Ultrasound contrast agents (UCAs) are an essential add-on to the conventional B-mode US and to the Doppler US that further empower this method, allowing the evaluation of the enhancement properties and the vascular architecture of FLLs, in comparison to the background parenchyma. The current paper also explores the new universe of AI and the various implications of deep learning algorithms in the evaluation of NAFLD and NAFLD-related HCC through US methods, concluding that it could potentially be a game changer for patient care.

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Two Metabolomics Phenotypes of Human Hepatocellular Carcinoma in Non-Alcoholic Fatty Liver Disease According to Fibrosis Severity

Metabolites ◽

10.3390/metabo11010054 ◽

2021 ◽

Vol 11 (1) ◽

pp. 54

Author(s):

Benjamin Buchard ◽

Camille Teilhet ◽

Natali Abeywickrama Samarakoon ◽

Sylvie Massoulier ◽

Juliette Joubert-Zakeyh ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Liver Disease ◽

Fatty Liver ◽

Fatty Liver Disease ◽

Monounsaturated Fatty Acids ◽

Metabolic Reprogramming ◽

Resonance Spectroscopy ◽

Alcoholic Fatty Liver ◽

The Impact ◽

Alcoholic Fatty Liver Disease

Non-Alcoholic Fatty Liver Disease (NAFLD) is considered as the forthcoming predominant cause for hepatocellular carcinoma (HCC). NAFLD-HCC may rise in non-cirrhotic livers in 40 to 50% of patients. The aim of this study was to identify different metabolic pathways of HCC according to fibrosis level (F0F1 vs. F3F4). A non-targeted metabolomics strategy was applied. We analyzed 52 pairs of human HCC and adjacent non-tumoral tissues which included 26 HCC developed in severe fibrosis or cirrhosis (F3F4) and 26 in no or mild fibrosis (F0F1). Tissue extracts were analyzed using 1H-Nuclear Magnetic Resonance spectroscopy. An optimization evolutionary method based on genetic algorithm was used to identify discriminant metabolites. We identified 34 metabolites differentiating the two groups of NAFLD-HCC according to fibrosis level, allowing us to propose two metabolomics phenotypes of NAFLD-HCC. We showed that HCC-F0F1 mainly overexpressed choline derivatives and glutamine, whereas HCC-F3F4 were characterized by a decreased content of monounsaturated fatty acids (FA), an increase of saturated FA and an accumulation of branched amino acids. Comparing HCC-F0F1 and HCC-F3F4, differential expression levels of glucose, choline derivatives and phosphoethanolamine, monounsaturated FA, triacylglycerides were identified as specific signatures. Our metabolomics analysis of HCC tissues revealed for the first time two phenotypes of HCC developed in NAFLD according to fibrosis level. This study highlighted the impact of the underlying liver disease on metabolic reprogramming of the tumor.

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