Shengjing Hospital of China Medical University
Shenyang, Liaoning, 110004, China
Location status: Recruiting
NCT Number: NCT06463366
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.
Interested in participating?
Request Info18 year–75 year
All sexes
Observational
Shenyang, Liaoning, 110004, China
Location status: Recruiting
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.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
3D-MRE(storage modulus, ., loss modulus and damping ratio [DR] for liver inflammation and fibrosis) MRI-PDFF(liver fat content)
Time frame: 12 months
Liver stiffness regression is defined as the change of 3D MRE shear stiffness larger than 19%
Contact information is provided by the study sponsor or research team.
Ruobing Bai
CONTACT
Yu Shi
CONTACT
Shengjing Hospital
Other
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