Non-invasive Detection of Right Ventricular Interstitial Fibrosis using MRI in Patients with Pulmonary Hypertension due to Hear Failure with Preserved Ejection Fraction

Project: Research project

Project Details

Description

More than half of patients hospitalized for heart failure in the United States have heart failure with preserved ejection fraction (HFpEF) and 80% of them have pulmonary hypertension (PH-HFpEF). Unfortunately, there are no proven treatments for these patients. Fibrosis plays an important role in the genesis of right ventricular (RV) dysfunction, but techniques to provide evidence for this are indirect and/or invasive. Current MRI technology allows quantitative assessment of diffuse interstitial fibrosis by employing a method called T1 mapping. This novel, non-invasive technique is feasible, reproducible, and has been validated against histology for assessment of myocardial fibrosis in the left ventricle.
We hypothesize that 1) T1 mapping can accurately detect diffuse RV interstitial fibrosis; 2) PH-HFpEF patients have significantly increased fibrosis; 3) the amount of fibrosis correlates with the degree of RV dysfunction; and 4) the degree of fibrosis is significantly different between various etiologies of PH.
We will use a rapid paced canine model of heart failure to provide histologic validation of diffuse RV interstitial fibrosis as detected by T1 mapping analysis and perform this technique in patients with PH to evaluate the degree of RV interstitial fibrosis.
Ultimately, we hope to gain greater mechanistic insight into the structural changes associated with RV remodeling in PH-HFpEF, and establish a new, clinical tool for phenotyping, risk stratification, and therapeutic targeting of individuals with PH-HFpEF in which fibrosis is a major contributor to the disease.
StatusFinished
Effective start/end date9/1/148/31/19

Funding

  • International Society for Heart & Lung Transplantation (Agmt 8/21/14)

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.