Spatiotemporal Analysis of Cardiac Disease Using Murine Four-Dimensional Ultrasound

Frederick William Damen, Purdue University

Abstract

Cardiac disease remains the number one cause of all mortality in the United States, prompting a continued effort to understand the various factors that exacerbate heart disease. To this end, murine models of cardiac disease have served a crucial role by allowing researchers to systematically manipulate disease-linked factors and longitudinally track changes in cardiovascular function. Routine assessment of heart function in these mice is often conducted using high-frequency ultrasound; however, cardiac function metrics drawn from conventional ultrasound imaging heavily relies on measurements obtained from a representative slice of the heart and idealized geometries of the left ventricle. While high-field cine-MRI can circumvent these limitations with volumetric imaging, our group has recently developed and validated a high frequency four-dimensional ultrasound (4DUS) technique that provides higher spatiotemporal resolution, comparable accuracy in cardiac metrics, and relatively faster acquisitions compared to cine-MRI. We have also developed standardized analysis methods for left-ventricular 4DUS data, encapsulated in a custom interactive software toolbox. Our software helps users measure regionally-specific myocardial kinematics, interpolates a four-dimensional mesh of the endo- and epi-cardial boundaries, and then quantifies various myocardial strain metrics. We have applied these tools to study disease progression in two murine models of pathological cardiac hypertrophy (i.e. Cpt2M-/- and Nkx2-5183P/+). Backed by our demonstrated findings, we aim to provide researchers studying cardiac disease a more comprehensive approach to characterizing their chosen models, and increase the scientific reach of cardiovascular research at large.

Degree

Ph.D.

Subject Area

Histology|Physiology|Artificial intelligence|Medical imaging|Medicine|Public health

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