ABSTRACT
RESEARCH PROJECT - Chronic myocardial infarction and heart failure with preserved ejection fraction affect
millions of patients in the US. These cardiac pathologies impair the mechanical performance of the heart and
may lead to breathlessness, exercise intolerance, and severe fatigue. Both are associated with an increase in
passive myocardial stiffness, but despite the widespread clinical presentation and dire prognosis associated
with these cardiac diseases, our ability to accurately characterizes changes in stiffness remains profoundly
limited. Our understanding is limited, in part, because the available measures of “cardiac stiffness” are both
poorly defined and based on assumptions that depend, in part, on ventricular geometry instead of changes to
tissue microstructure. In addition,the current material models describing myocardial stiffness are based on ex
vivo data, and therefore do reflect the in vivo environment and conditions.
Thegoal of this researchis to develop robust definitions of myocardial stiffness and measures of cardiac
kinematics (strain) that are needed to transform patient-specific MRI data into quantitative diagnostic measures
of diastolic stiffness in patients with cardiovascular diseases. In order to achieve this objective, we will first
identify strain measures that characterize the kinematics of passive filling(Specific Aim-1). Then, we will
use these in vivo kinematic measures, combined with intraventricular pressure data, to robustly define a
measure of diastolic myocardial stiffness in vivo(Specific Aim-2). Lastly, to validate our new myocardial
stiffness formulation and test its diagnostic capabilities, we will identify distinct differences in local
myocardial stiffness between infarcted, border zone, and remote myocardium (Specific Aim-3).
This work will lead to a new approach that can leverage patient specific MRI and pressure data to extract
quantitative kinematic and passive stiffness diagnostic biomarkers. These biomarkers will enable a rigorous
diagnosis of pathologies such as heart failure with preserved ejection fraction (HFpEF) and quantitatively
characterize the impact of myocardial remodeling (e.g., due to an infarct) on diastolic myocardial stiffness.
CANDIDATE CAREER GOALS AND DEVELOPMENT PLAN -An advanced understanding of the medical and
clinical aspects of cardiac mechanics and kinematics is essential to validate and evaluatenumerical models
against available data, interpret the model results, and propose new research directions. In this award I plan to
acquire the necessary medical and clinical knowledge to complement my numerical analysis capabilities and
allow me to pursue my research in translational cardiac biomechanics. This multidisciplinary skill set will enable
me to start an independent professorial appointment in academia, which is my main career goal.
During the duration of this award, I plan to: 1) significantly increase my knowledge of cardiac anatomy,
physiology, and pathophysiology by attending a cardiovascular physiology course, participating in Dr. Ennis's
(mentor) and Dr. Garfinkel's (co-mentor) weekly group meetings, and attending Cardiology and Radiology
Grand Rounds; 2)Improve my understanding of the physics of cardiac MRI and data processing by attending
Dr. Ennis's graduate level MRI physics course, observe clinical cardiac MRI exams, processing cine DENSE
and cardiac DT-MRI data, and acquiring MRI data for animal experiments in Year 2 and 3; 3)Learn how to
present my research results to a medical audience - largely different from the engineering community in which I
currently work - by presenting my research results at weeklyclinical conferences, group meetings with MRI
experts, and in medically oriented professional conferences (e.g., AHA); and 4) Establish independence and
leadership skills by directing research projects with undergraduate students and discussing with Dr. Ennis how
to prioritize the many research projects, applications, presentations, and other duties.
ENVIRONMENT -Dr. Ennis's (mentor), Dr. Garfinkel's (co-mentor), and Dr. Demer's (co-mentor) research
experience and the overall research environment at UCLA are exceptionally well suited to support the
presented research plan. Dr. Ennis has extensive experience in all the core areas involved in the presented
research. He has worked for many years in cardiac and cardiovascular magnetic resonance imaging, finite
element modeling and material property estimation of the cardiovascular system, and cardiac function and
microstructure. Dr. Garfinkel has extensive experience in mathematical modeling of biological systems, with
particular emphasis on modeling cardiac electrophysiology. Moreover, Dr. Garfinkel is an expert in statistical
analysis applied to biological problems. Dr. Perotti (PI) will greatly benefit from working with Dr. Garfinkel to
improve his approach to cardiac modeling and incorporate rigorous statistical analyses in his research.Dr.
Demer's is an expert in theoretical and experimental aspects of the mechanical response of cardiovascular
tissues to a range of loading conditions.Dr. Perotti will be able to discuss with Dr. Demerthe physiological
features that must be captured in his computational model and the medical implications of changes in
myocardial kinematics and stiffness. Collaborating with her will ensure the project stays clinically focused.
UCLA itself is ideal for carrying out the research plan described in this proposal. Few centers can offer the
proximity of physical, educational,and intellectual resources that can be found at UCLA, including proven
collaborations between the medical school, bioengineering, and mechanical engineering and the world-class
MRI experimental facilities and computational resources.