Heart failure is a clinical syndrome marked by breathlessness, even at low levels of exertion, general fatigue, and fluid retention that is estimated to affect 5.1 million people in the United States. Heart failure with preserved ejection fraction (HFpEF) ? wherein the heart adequately pumps blood to the body, but patients still have terrible symptoms ? is estimated to account for 50% of all heart failure cases. HFpEF is a vexing clinical problem for which diagnostic and prognostic evaluation remains elusive. Experts agree that impaired filling critically underlies HFpEF, which can be attributed to an increase in diastolic myocardial stiffness. Currently, however, no clinical technique exists for measuring left ventricular diastolic myocardial stiffness. In fact, the very definition of ?myocardial stiffness? remains poorly established. Consequently, the ability to study the mechanisms that underlie HFpEF is virtually non-existent and limited therapeutic options will persist without significant advances. The objective of this project is to use an Equilibrium-Material-Stability (EMS) framework that couples patient-specific clinical MRI and LV pressure data in a computational model of the heart to diagnose changes in diastolic myocardial stiffness. The central hypothesis is that the new EMS framework for understanding the mechanisms of diastolic dysfunction in HFpEF will be more sensitive and outperform currently available approaches. The following specific aims outline our approach:
AIM #1 ? Refine advanced free-breathing MRI methods needed to measure diastolic myocardial stiffness. To accurately estimate regional diastolic myocardial stiffness coefficients our EMS framework incorporates high resolution anatomy, strain data, LV pressure, and our recent work establishing that myofiber orientation maps can be measured in vivo using cardiac diffusion tensor MRI (cDTI).
AIM #2 ? Validate our in vivo diastolic myocardial stiffness evaluation framework in humans. Our work will establish an acceptable clinical method for measuring global and regional diastolic myocardial stiffness that overcomes limitations associated with using pressure-volume loops.
AIM #3 ? Measure changes in diastolic myocardial stiffness in a longitudinal study of patients with HFpEF. This will establish the diagnostic sensitivity of the EMS framework with comparison to cardiac MRI biomarkers of increased stiffness, thereby providing mechanistic insight to one critical underlying cause of HFpEF.

Public Health Relevance

Heart failure is a clinical syndrome marked by breathlessness, even at low levels of exertion, general fatigue, and fluid retention that is estimated to affect 5.1 million people in the United States. Heart failure with preserved ejection fraction (HFpEF) ? wherein the heart adequately pumps blood to the body, but patients still have terrible symptoms ? accounts for about 50% of all heart failure cases and remains poorly understood. Our work seeks to provide better treatment options for the millions of Americans with HFpEF by developing and validating a new medical imaging framework for diagnosing, understanding, and evaluating the role that increases in heart stiffness play in cardiac dysfunction for patients with HFpEF.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL131823-03
Application #
9774287
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Danthi, Narasimhan
Project Start
2018-09-01
Project End
2021-06-30
Budget Start
2019-07-01
Budget End
2020-06-30
Support Year
3
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Palo Alto Veterans Institute for Research
Department
Type
DUNS #
624218814
City
Palo Alto
State
CA
Country
United States
Zip Code
94304
Verzhbinsky, Ilya A; Magrath, Patrick; Aliotta, Eric et al. (2018) TIME RESOLVED DISPLACEMENT-BASED REGISTRATION OF IN VIVO CDTI CARDIOMYOCYTE ORIENTATIONS. Proc IEEE Int Symp Biomed Imaging 2018:474-478
Aliotta, Eric; Moulin, Kévin; Magrath, Patrick et al. (2018) Quantifying precision in cardiac diffusion tensor imaging with second-order motion-compensated convex optimized diffusion encoding. Magn Reson Med 80:1074-1087