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临床试验/NCT06463366
NCT06463366招募中不适用

Multi-parametric Magnetic Resonance Imaging for the Precise Diagnosis and Quantitative Study of Liver Steatosis, Inflammation, and Fibrosis in Chronic Liver Disease.

Shengjing Hospital1 个研究点 分布在 1 个国家目标入组 100 人开始时间: 2022年6月14日最近更新:
适应症

试验速览

阶段
不适用
状态
招募中
入组人数
100
试验地点
1
主要终点
the changes of liver stiffness assessed by 3D-MRE before and after treatment.

研究概览

简要总结

To construct a novel, non-invasive, accurate, and convenient method to achieve the degree of liver damage is an important general problem in the management of patients with chronic liver disease. The investigators would like to develop non invasive advanced Magnetic Resonance Imaging (MRI) techniques (MR elastography, MRI-PDFF) to assess the degree of liver damage in patients with chronic liver disease. These techniques could reach high diagnostic performance for detection of liver fibrosis, inflammation and liver fat content; and could decrease the number of liver biopsies, which have risks and sample only a small portion of the liver.

详细描述

Patients with chronic hepatitis have increased risks of liver damage, including fibrosis and cirrhosis, which may eventually lead to hepatocellular carcinoma and end-stage liver disease requiring liver transplantation. These diseases are/will be the source of enormous health care costs and morbidity/mortality in the China.

Most hepatologists still rely on liver biopsy findings in patients newly diagnosed with chronic hepatitis, which enables the assessment of liver damage (fibrosis and inflammation). Liver biopsy has limitations, including cost, invasiveness, poor patient acceptance, limited sampling, inter-observer variability and is difficult to repeat.

Non invasive tests to capture the extent of liver damage at a larger scale are urgently needed. These will gain more acceptance among patients and hepatologists.

In this proposal, the investigators would like to test and validate non invasive MRI methods based on advanced MR elastography and MRI-PDFF techniques for the detection of fibrosis, cirrhosis and liver fat content in patients with chronic hepatitis. In order to improve the diagnostic performance of MRI, the investigators would like to build and validate a predictive model based on advanced functional MRI metrics (storage modulus, loss modulus and damping ratio [DR]) by follow up every 6 month. If validated, this novel non invasive algorithm will not only decreases the number of liver biopsies, but also enable earlier diagnosis of liver fibrosis when antiviral treatment is more effective, and enable a comprehensive evaluation of the liver (to assess for cirrhosis, portal hypertension and hepatocellular cancer).

This study is aimed to evaluate whether the change of liver stiffness assessed by MRE can predict treatment effectiveness in chronic liver disease treatment by follow up every 6 month.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
18 Years 至 75 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • Chronic liver disease (including viral hepatitis, alcoholic hepatitis, non alcoholic steatohepatitis, primary biliary cirrhosis, primary sclerosing cholangitis, etc..)
  • Age range of 18 to 75 years old
  • Accept systematic antiviral therapy or hormone or ursodesoxycholic acid or supportive liver protection therapy

排除标准

  • Age less than 18 years
  • Unable or unwilling to give informed consent
  • Contra-indications to MRI
  • Electrical implants such as cardiac pacemakers or perfusion pumps
  • Ferromagnetic implants such as aneurysm clips, surgical clips, prostheses, artificial hearts, valves with steel parts, metal fragments, shrapnel, tattoos near the eye, or steel implants
  • Ferromagnetic objects such as jewelry or metal clips in clothing
  • Pregnant subjects
  • Pre-existing medical conditions including a likelihood of developing seizures or claustrophobic reactions

结局指标

主要结局

the changes of liver stiffness assessed by 3D-MRE before and after treatment.

时间窗: 12 months

Liver stiffness regression is defined as the change of 3D MRE shear stiffness larger than 19%

次要结局

未报告次要终点

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Yu Shi

professor

Shengjing Hospital

研究点 (1)

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