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
NCT ID: NCT07149571
Last Updated: 2025-09-02
Study Results
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Basic Information
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RECRUITING
500 participants
OBSERVATIONAL
2025-04-01
2032-12-31
Brief Summary
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Detailed Description
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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.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Metabolic-Associated Fatty Liver Disease patients
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
2. Age/gender: unlimited;
3. Patients who voluntarily participate in clinical trials and sign written subject informed consent
Exclusion Criteria
2. Voluntarily participation in the study and provision of written informed consent.
ALL
Yes
Sponsors
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Tongji Hospital
OTHER
Responsible Party
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Zhen Li
Professor
Locations
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Tongji hospital
Wuhan, Hubei, China
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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TJ-IRB202411109
Identifier Type: -
Identifier Source: org_study_id
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