SP #1: Detection of Liver Fibrosis using IVIM Diffusion and DCE-MRI in HCV

Detection of Liver Fibrosis using IVIM Diffusion and DCE-MRI in HCV

Significance:

Patients with Hepatitis C Virus (HCV) are at a high risk of developing liver fibrosis that can result in cirrhosis [1]. Cirrhosis of the liver can lead to liver failure and portal hypertension, which often results in liver transplant. Early stages of fibrosis, however, can be slowed or even reversed with the use of antiviral therapy. Thus, accurate diagnosis of different stages of liver fibrosis is imperative for proper treatment. Unfortunately, the degree of fibrosis is commonly determined from liver biopsy, which is not only invasive but also expensive and hampered by sampling error.

Aims:

In this study we will develop a noninvasive, highly accurate method to detect whole liver fibrosis based on a combination of a) diffusion-weighted MR imaging (DWI) with extraction of intravoxel incoherent motion (IVIM) parameters [2-4], and b) dynamic contrast-enhanced (DCE) MRI [4,5].

Approach:

To determine the diagnostic performance of diffusion and perfusion metrics derived from IVIM DWI for staging liver fibrosis in HCV, we administered a pilot study with 20 subjects (7 controls and 13 patients with HCV). The subjects underwent 4 different IVIM DWI sequences: respiratory-triggered (RT) bipolar (BP) sequence, RT monopolar (MP) sequence, free-breathing (FB) BP sequence and FB MP. The image quality for all sequences was assessed and biexponential analysis with the Bayesian method was administered to yield true diffusion coefficient (D), pseudodiffusion (D*) coefficient and perfusion fraction (PF) in liver parenchyma. We determined that the RT BP DWI sequence had the best results in terms of image quality, reproducibility and ability to discriminate between healthy and fibrotic liver [6]. 

The next stage of the study is to assess the ability of IVIM DWI to detect liver fibrosis in a larger sample size, to determine the comparative diagnostic performance of perfusion metrics derived from DCE-MRI, and to evaluate performance gains from combining IVIM and DCE-MRI.  A cohort of 135 HCV patients will be recruited for a 5-year study. The patients will undergo liver MRI (DW- and DCE-MRI) at three distinct time points (within 6 months of liver biopsy, before living related liver transplant and within 90 days before cadaveric liver transplantation). Histopathology from the liver biopsy will be used to determine the efficacy of the combined IVIM DWI and DCE-MRI predictive model.

BTRC Resources Utilized:

TR&D #1: This project is expected to benefit greatly from the support of the BTRC core team and technology.  The rapid radial acquisition and reconstruction approaches developed in TR&D #1 are expected to improve substantially the quality of liver DCE-MRI data collected in this proposal by allowing faster acquisitions, with improved quantification of the vascular input function and perfusion metrics. In addition, as we plan to expand this project to hepatocellular carcinoma (HCC) through a recently-funded U01 grant, it will be desirable to increase both the spatial and temporal resolution for quantification of HCC angiogenesis.

It is important to note the common Siemens MRI platforms between MSSM and NYU, as well as the past and present scientific collaborations between collaborative project PI and former NYU Radiology faculty member Dr. Taouli and his current NYUSOM colleagues on topics such as perfusion modeling / processing and radial VIBE.

Note that since the time of the original BTRC submission, the radial VIBE sequence and the GRASP reconstruction have both been deployed at MSSM, which is one of the sites participating in the ongoing multicenter GRASP study discussed in TR&D #1.  Figure 1 shows one early example of improvements in image quality achieved with free-breathing radial VIBE as compared with breath-held Cartesian VIBE.    Use of GRASP has also resulted in increased temporal resolution which is now being evaluated in perfusion analyses.

This early experience represents both an example of a successful service relationship and and an instance of effective dissemination of BTRC technologies. 

Principal Investigator: 
Key Personnel: 

Sponsors

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Philanthropic Support

We gratefully acknowledge generous support for radiology research at NYU Langone Medical Center from:
 
• The Big George Foundation
• Raymond and Beverly Sackler
• Bernard and Irene Schwartz

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