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ID05475015

Using 3D Magnetic Resonance Elastography to Assess Cirrhosis, Advanced Chronic Liver Disease, and Portal Hypertension A Prospective Multicenter Study to Develop a Non-Invasive Risk Stratification Method

Led by Shengjing Hospital · Updated on 2026-02-09

150

Participants Needed

1

Research Sites

21 weeks

Total Duration

AI-Summary

What this Trial Is About

Researchers are evaluating a new, non-invasive method using three-dimensional magnetic resonance elastography 3D-MRE to predict hepatic venous pressure gradient HVPG in patients with cirrhosis, portal hypertension, or advanced chronic liver disease. This study aims to establish a risk stratification system to better manage portal hypertension, a critical factor affecting the prognosis of these liver conditions. The trial is observational and focuses on improving diagnosis without invasive procedures like liver biopsy or traditional HVPG measurement. The study involves two groups a training cohort to develop the new 3D-MRE model for virtual HVPG prediction, and a validation cohort to confirm the models accuracy in different patients under similar conditions. Imaging is done using a 3.0-T MRI system with a phased-array body coil, while HVPG measurements are performed by skilled interventional radiologists following standard procedures. Participants undergo both assessments within one month. During the 12-month study, participants will have their portal hypertension assessed through the features of 3D-MRE and HVPG readings. Researchers will analyze the accuracy of 3D-MRE to predict portal hypertension levels. Participants provide informed consent and meet age and health criteria. The study includes monitoring to ensure reliable imaging and measurement results, with exclusion of those with conditions or treatments that may affect accuracy. The total participation involves these diagnostic steps, with no treatment interventions administered.

CONDITIONS

Brief Title

3D-MRE for Assessing Cirrhosis, Advanced Chronic Liver Disease and Portal Hypertension

Research Team

Y

Yifei Huang, M.D.

Y

Yu Shi, Prof.

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