RecruitingNCT04429100

Rapid Breath-hold Quantitative Macromolecular Proton Fraction Imaging for Liver Fibrosis

Assessment of Fibrosis by Non-invasive Quantitative Imaging of Collagen in the Liver Using Breath-hold MRI With Comparison With MR Elastography and Liver Biopsy


Sponsor

Chinese University of Hong Kong

Enrollment

200 participants

Start Date

Mar 1, 2020

Study Type

OBSERVATIONAL

Conditions

Summary

Chronic liver disease is a major health problem worldwide. Liver fibrosis is a key feature in most chronic liver diseases. When identified early, liver fibrosis may be reversible. Currently, liver biopsy is the gold standard for the diagnosis of liver fibrosis. Liver biopsy; however, is invasive. Non-invasive diagnostic tools are increasingly used in clinical practice. However, the existing noninvasive methods still have significant limitations to detect early-stage liver fibrosis. Liver fibrosis is characterized by excessive deposition of collagen-rich connective tissues in the liver. The macromolecular proton fraction (MPF) is an MRI parameter which characterizes the magnetization transfer (MT) effect in tissues. Quantitative MPF imaging is non-invasive and can be used to measure collagen deposition in the liver due to the strong MT effect of collagen. It has been reported MPF quantification can be used for diagnosis of early-stage liver fibrosis. However, the existing approaches require B1, B0, and T1 map in addition to the imaging data for MPF quantification, which makes it challenging to adopt them for routine clinical use. The investigators propose a fast and robust MPF quantification approach. In contrast to the existing methods which rely on saturation radiofrequency pulses for MPF quantification, our approach is based on spin-lock radiofrequency pulses which have minimum Rabi oscillations. The whole imaging data can be acquired within a breath-hold less than 8 seconds. Our approach only needs a B1 map in addition to the imaging data for MPF quantification. The preliminary clinical studies on 3.0T MRI show the measurement using our approach is specific to collagen content and can be used to detect early-stage liver fibrosis. To further confirm the clinical value of the proposed approach, the investigators will investigate the relationship of the collagen content measured using the proposed non-invasive imaging approach and those measured based on morphometry analysis of histology, and determine the diagnostic value of the proposed method for detection of early stage liver fibrosis in a large cohort. The investigators will also perform comparative studies of the proposed method and the state-of-the-art quantitative MPF imaging technique. This project will provide a diagnostic technology for early detection of liver fibrosis. The proposed MRI technology also has potential to be used for other clinical purposes.


Eligibility

Inclusion Criteria6

  • Patient group
  • patients with histology-proven liver fibrosis, including those with liver fibrosis stage F0, early-stage liver fibrosis (F1-2), and late stage.
  • liver fibrosis(F3-4).
  • patient aged 18 years old and above.
  • Healthy control group
  • controls aged 18 years old and above.

Exclusion Criteria1

  • Contraindications to MRI, such as cardiac pacemaker, claustrophobia, pregnancy, metallic implants not suitable for MRI scan.

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Interventions

DIAGNOSTIC_TESTMagnetic Resonance Imaging

One novel MRI sequence, i.e. the quantitative imaging of macromolecular proton fraction (MPF), will be introduced into this study. MPF is defined as the relative amount of protons associated with macromolecules involved in magnetization exchange with free water protons. This parameter is independent of the pool model used for quantification and the pulse sequences used for data acquisition. Recent studies have found a strong association between MPF and collagen content in the fibrotic liver, indicating MPF is a potential biomarker of early-stage liver fibrosis.


Locations(1)

The Chinese University of Hong Kong, Prince of Wale Hospital

Hong Kong, Shatin, Hong Kong

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