Abstract
Biomechanical forces intimately contribute to cardiac morphogenesis. However, volumetric imaging to investigate the cardiac mechanics with high temporal and spatial resolution remains an imaging challenge. We hereby integrated light-field microscopy (LFM) with light-sheet fluorescence microscopy (LSFM), coupled with a retrospective gating method, to simultaneously access myocardial contraction and intracardiac blood flow at 200 volumes per second. While LSFM allows for the reconstruction of the myocardial function, LFM enables instantaneous acquisition of the intracardiac blood cells traversing across the valves. We further adopted deformable image registration to quantify the ventricular wall displacement and particle tracking velocimetry to monitor intracardiac blood flow. The integration of LFM and LSFM enabled the time-dependent tracking of the individual blood cells and the differential rates of segmental wall displacement during a cardiac cycle. Taken together, we demonstrated a hybrid system, coupled with our image analysis pipeline, to simultaneously capture the myocardial wall motion with intracardiac blood flow during cardiac development.
Highlights
The zebrafish (Danio rerio) model is a well-established genetic system to study cardiovascular development and disease [1,2,3]
To elucidate the underlying biomechanical mechanisms, we have embraced the zebrafish system for the ease of genetic and pharmacological manipulations and its rapidity for organ development
In the presence of a rapid heartbeat, microscopy is confined by temporal resolution to image the cardiac contraction and blood flow
Summary
The zebrafish (Danio rerio) model is a well-established genetic system to study cardiovascular development and disease [1,2,3]. Previous investigations have reported a retrospective gating method [20,21] to re-align the asynchronous time-lapse images that were sequentially acquired at each slice of the heart This approach has been effective in reconstructing the myocardial deformation and electrical conduction [7,20,22]. This method is limited from capturing the intracardiac blood cells, because the periodicity assumption fails due to the random cell motion [20]. A majority of analyses for blood flow have adopted the 2-D image-based techniques or in silico models [23,24,25,26]
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