Abstract
Novel insights into cardiac contractile dysfunction at the cellular level could deepen understanding of arrhythmia and heart injury, which are leading causes of morbidity and mortality worldwide. We present a comprehensive experimental and computational framework combining light-field microscopy and single-cell tracking to investigate real-time volumetric data in live zebrafish hearts, which share structural and electrical similarities to the human heart. Our system acquires 200 vol/s with lateral resolution of up to 5.02 ± 0.54 μm and axial resolution of 9.02 ± 1.11 μm across the whole depth using an expectation-maximization-smoothed deconvolution algorithm. We apply a deep-learning approach to quantify cell displacement and velocity in blood flow and myocardial motion and to perform real-time volumetric tracking from end-systole to end-diastole within a virtual reality environment. This capability delivers high-speed and high-resolution imaging of cardiac contractility at single-cell resolution over multiple cycles, supporting in-depth investigation of intercellular interactions in health and disease.