To Explore the Value of New MR Technology in Non-invasive Quantitative Assessment of Systemic Metabolism, Disease Status and Prognosis in Patients With Metabolic-Associated Fatty Liver Disease

Overview

The purpose of this study is to explore the value of new MR technology in assessing the systemic metabolism, disease status, and prognostic risk of metabolism-related fatty liver disease. By obtaining clinical, imaging, laboratory examination and pathological data of metabolism-related fatty liver disease, image processing software is used to analyze the images, explore the relationship between imaging parameters, body composition and metabolic diseases and metabolism-related fatty liver disease, and achieve non-invasive diagnosis, efficacy evaluation, and prognosis prediction of metabolism-related fatty liver disease. Thereby guiding clinical treatment and improving the prognosis and quality of life of patients with metabolism-related fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) is a chronic progressive liver disease caused by overnutrition and insulin resistance (IR) in genetically susceptible individuals. The disease spectrum includes non-alcoholic fatty liver (NAFL), non-alcoholic steatohepatitis (NASH) and its associated fibrosis and liver cirrhosis \[1-2\]. With the prevalence of obesity and type 2 diabetes mellitus (T2DM), the global prevalence and incidence of NAFLD continue to increase, especially in my country \[3-5\]. NAFLD is the most common chronic liver disease in the world and the main cause of elevated serum transaminases in healthy people undergoing physical check-ups. It has now replaced viral hepatitis as the largest chronic liver disease in my country \[4-5,10\]. In addition, NAFLD, metabolic syndrome (MetS) and T2DM are mutually causal, and together promote the development of malignant tumors such as arteriosclerosis cardiovascular disease (CVD), chronic kidney disease (CKD), liver decompensation, and hepatocellular carcinoma (HCC)\[1- 2, 6 -7\]. To this end, NAFLD has become an increasingly serious public health problem in my country \[4,8\]. In 2020, the International Fatty Liver Expert Group recommended that NAFLD be renamed metabolic dysfunction-associated fatty liver disease (MAFLD). The Hepatology Branch of the Chinese Medical Association actively stated its position \[8\], emphasizing that the diagnosis and treatment of NAFLD needs to follow the actual situation in my country. After extensive discussion, it was recommended that the English terms MAFLD and MASLD be translated into "metabolically related fatty liver disease. Diagnosis of MAFLD requires the exclusion of excessive drinking (weekly ethanol intake ≥210g in men and ≥140g in women) and other causes that can lead to fatty liver, and the patient has at least 1 MetS component \[1-2\]. Patients with suspected MAFLD need to routinely test blood biochemical analysis indicators and evaluate liver steatosis and fibrosis. At the same time, MetS components should be systematically screened and CVD risk should be assessed. Common malignancies and esophageal varices should be screened according to relevant guidelines. Liver biopsy histology is still the gold standard for evaluating liver steatosis and fibrosis \[1-2\]. MetS, T2DM and NAFLD interact with each other to promote the pathogenesis of metabolization-related diseases in multiple systems and organs across the body. The prognosis of patients with NAFLD is mainly related to CVD and non-hepatic malignancies. Liver related events (liver decompensation, HCC, liver transplantation, or liver-related death) are significantly increased when combined with progressive fibrosis \[2,6-7\]. MetS is independently associated with increased all-cause mortality and liver and CVD related mortality in patients with NAFLD. T2DM has a greater impact on the prognosis of patients with NAFLD than obesity. Obesity is also a factor that needs to be prevented and managed urgently. Adipose tissue in different parts of the human body is different in anatomy, cells, molecules, etc., so it is of great significance to more accurately measure and divide adipose tissue and muscles in the human body and explore their correlation with renal dysfunction. At present, the research technology using CT or MR images to automatically segment various body components of patients is constantly improving. Therefore, it is also of great significance to accurately assess the metabolic status of patients with metabolism-related fatty liver disease and explore the mechanisms related to metabolism and liver function, which will help doctors make clinical diagnosis and subsequent assisted designation of treatment plans. Magnetic resonance imaging (MRI) is widely used in medical imaging. Because of its non-invasive nature, high soft tissue resolution and multi-parameter analysis capabilities, it has become a key tool for the assessment and diagnosis of a variety of diseases. MRI can provide high-resolution images of tissue structures and can assess the functional status and metabolic activity of tissue through different imaging sequences, such as T1 and T2 weighted imaging, diffusion weighted imaging (DWI), and magnetization transfer imaging (MT) imaging. These characteristics and the constantly updated new imaging sequences allow MRI to demonstrate great potential in assessing liver disease, especially in non-invasively assessing tissue structure and functional status. MRI can not only display the anatomical structure of an organ in detail, but also monitor the fat fraction and functional status of an organ through multi-parameter imaging technology. For example, magnetic resonance imaging-derived protondensity fat fraction (MRI-PDFF) objectively evaluates the entire liver fat content and has been used in clinical trials to assess changes in liver fat content. MRI-PDFF≥5% and 10% indicate significant and moderate-severe liver steatosis, respectively. With the advancement of precision medicine and the rapid development of artificial intelligence in recent years, the combination of imagingomics and machine learning technologies has further enhanced the potential of MRI applications. Imagingomics is capable of automating and improving accurate diagnosis through high-throughput image feature extraction combined with machine learning models. These technologies show great potential especially in the staging and grading of metabolism-related fatty liver disease and prognostic assessment, where the accuracy and reliability of the assessment can be significantly improved through the construction of accurate models. Looking forward, the clinical application of CT and MRI technologies in the noninvasive evaluation of patients with metabolic-related fatty liver disease is promising. Their potential to improve patients' quality of life and liver health is enormous. However, current challenges remain, including the diffusion and standardization of the techniques, the accumulation and analysis of data, and the need for multicenter clinical studies. Nonetheless, through continued technological development and research, the use of MRI in the evaluation of patients with metabolism-related fatty liver disease will become more widespread and intensive.