Vol. 3 No. 4 - Dec 2017

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High-Frequency 4-Dimensional Ultrasound (4DUS): A Reliable Method for Assessing Murine Cardiac Function Frederick W. Damen 1 , Alycia G. Berman 1 , Arvin H. Soepriatna 1 , Jessica M. Ellis 2 , Stephen D. Buttars 3 , Kristiina L. Aasa 3 , and Craig J. Goergen 1 1 Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN; 2 Department of Nutrition Science, Purdue University, West Lafayette, IN; and 3 FUJIFILM VisualSonics, Toronto, ON, Canada Corresponding Author: Craig J. Goergen, PhD 206 S. Martin Jischke Dr., West Lafayette, IN 47907, USA; E-mail: Key Words: ultrasound, cine MRI, cardiac disease, mouse, hypertrophy Abbreviations: Short-axis motion-mode (SAX MM); magnetic resonance imaging (MRI); 4-dimensional ultrasound (4DUS); left ventricle (LV); end-diastole volume (EDV), peak-systole volume (PSV), stroke volume (SV), ejection fraction (EF), left ventricle mass (LVM) In vivo imaging has provided a unique framework for studying pathological progression in various mouse models of cardiac disease. Although conventional short-axis motion-mode (SAX MM) ultrasound and cine magnetic resonance imaging (MRI) are two of the most prevalent strategies used for quantifying cardiac function, there are few notable limitations including imprecision, inaccuracy, and geometric assumptions with ultrasound, or large and costly systems with substantial infrastructure requirements with MRI. Here we present an automated 4-dimensional ultrasound (4DUS) technique that provides comparable information to cine MRI through spatiotemporally synced imaging of cardiac motion. Cardiac function metrics derived from SAX MM, cine MRI, and 4DUS data show close agreement between cine MRI and 4DUS but overestimations by SAX MM. The inclusion of a mouse model of cardiac hypertrophy further highlights the precision of 4DUS compared with that of SAX MM, with narrower groupings of cardiac metrics based on health status. Our findings suggest that murine 4DUS can be used as a reliable, accurate, and cost-effective technique for longitudinal studies of cardiac function and disease progression. INTRODUCTION Murine cardiac disease models have become the foundation for systematically studying mechanisms and factors that influence negative outcomes such as heart failure (1-3). Although ex vivo techniques (eg, histology, proteomics) provide substantial information regarding gross and molecular composition, their information is limited to the state of tissue at sacrifice. In vivo imaging, on the other hand, can provide longitudinal informa- tion and result in a more comprehensive understanding of dis- ease progression, particularly when studying changes in cardiac function. Although many noninvasive imaging modalities exist, high-frequency ultrasound and cine magnetic resonance imag- ing (MRI) are most widely used to assess murine cardiac function (4-6). High-frequency ultrasound uses megahertz-frequency ul- trasonic waves to acquire images of the heart, with contrast corresponding to differences in acoustic impedance between tissue types. This modality is particularly useful for imaging mice, as even with their rapid heart rates (approaching 600 bpm), near-real-time temporal resolution can be achieved. Nev- ertheless, standard ultrasound imaging techniques for calculat- ing cardiac function (eg, short-axis motion-mode or M-Mode [SAX MM]) require the use of geometric models to estimate the ventricular volumes as spheres, ellipsoids, or other shapes (7, 8). Although these geometric assumptions are commonly used to study heart function in vivo (9, 10), the left ventricle (LV) in a mouse has a complicated 3-dimensional shape, which can in- crease in complexity with varying disease states. Cardiac cine MRI exploits the contrasting magnetic proper- ties of myocardial tissue and flowing blood to collect volumetric information across a heartbeat. These 4-dimesional (3-dimen- sional 1 time) data are spatiotemporally compiled from spa- tially adjacent slices of cine data across the heart. Compared with ultrasound, cine MRI takes longer to process images because the region of interest must be sampled several times before each slice of cine data can be properly reconstructed. However, cine MRI is often considered a gold standard method for acquiring LV information, as the chamber's entire boundary can be directly imaged (11-13). Unfortunately, ac- quiring cine MRI data is often costlier owing to system availability, maintenance, and required infrastructure for op- erating a superconducting magnet. Building upon the idea of spatiotemporally compiling loops of MRI data, we present here an automated 4D ultrasound (4DUS) ADVANCES IN BRIEF ABSTRACT © 2017 The Authors. Published by Grapho Publications, LLC This is an open access article under the CC BY-NC-ND license ( ISSN 2379-1381 180 TOMOGRAPHY.ORG | VOLUME 3 NUMBER 4 | DECEMBER 2017

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