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Extraction of murine cardiac functional parameters on a beat-by-beat basis is limited with the existing imaging modalities due to insufficient three-dimensional temporal resolution. Faster volumetric imaging methods enabling in vivo characterization of functional parameters are poised to advance cardiovascular research and provide a better understanding of the mechanisms underlying cardiac diseases. We present a new approach based on analyzing contrast-enhanced optoacoustic (OA) images acquired at high volumetric frame rate without using cardiac gating or other approaches for motion correction. We apply an acute murine myocardial infarction model optimized for acquisition of artifact-free optoacoustic imaging data to study cardiovascular hemodynamics. Infarcted hearts (n = 21) could be clearly differentiated from healthy controls (n = 9) based on a significantly higher pulmonary transit time (PTT) (2.25 [2.00-2.41] s versus 1.34 [1.25-1.67] s, p = 0.0235), while no statistically significant difference was observed in the heart rate (318 [252-361] bpm versus 264 [252-320] bpm, p = 0.3129). Nevertheless, nonlinear heartbeat dynamics was stronger in the healthy hearts, as evidenced by the third harmonic component in the heartbeat spectra. MRI data acquired from the same mice further revealed that the PTT increases with the size of infarction and similarly increases with reduced ejection fraction. Moreover, an inverse relationship between infarct PTT and time post-surgery was found, which suggests the occurrence of cardiac healing. In combination with the proven ability of optoacoustics to track targeted probes within the injured myocardium, our method can depict cardiac anatomy, function, and molecular signatures, with both high spatial and temporal resolution. Volumetric four-dimensional optoacoustic characterization of cardiac dynamics with supreme temporal resolution can capture cardiovascular dynamics on a beat-by-beat basis in mouse models of myocardial ischemia.

Characterization of Cardiac Dynamics in an Acute Myocardial Infarction Model by Four-Dimensional Optoacoustic and Magnetic Resonance Imaging