1. Integrating light-sheet imaging with virtual reality to recapitulate developmental cardiac mechanics
- Author
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Yichen Ding, Chih-Chiang Chang, René R. Sevag Packard, Tatiana Segura, Elias Sideris, Tzung K. Hsiai, Thao P. Nguyen, Juhyun Lee, Peng Fei, Arash Abiri, Yilei Li, Shuoran Li, Kyung In Baek, Jeffrey J. Hsu, Alex A. T. Bui, and Parinaz Abiri
- Subjects
0301 basic medicine ,Potassium Channels ,Computer science ,Interface (computing) ,Cardiology ,Image registration ,Virtual reality ,Mechanics ,01 natural sciences ,010309 optics ,Mice ,03 medical and health sciences ,Computer graphics (images) ,0103 physical sciences ,Medical imaging ,Animals ,Segmentation ,Computer vision ,Hyaluronic Acid ,Interactive visualization ,Zebrafish ,Cardiac cycle ,business.industry ,Virtual Reality ,Heart ,General Medicine ,Fibroblasts ,Mice, Inbred C57BL ,Cardiac Imaging Techniques ,030104 developmental biology ,Technical Advance ,Microscopy, Fluorescence ,Models, Animal ,Diagnostic imaging ,Artificial intelligence ,business ,Cardiac mechanics ,Algorithms ,Developmental Biology - Abstract
Currently, there is a limited ability to interactively study developmental cardiac mechanics and physiology. We therefore combined light-sheet fluorescence microscopy (LSFM) with virtual reality (VR) to provide a hybrid platform for 3D architecture and time-dependent cardiac contractile function characterization. By taking advantage of the rapid acquisition, high axial resolution, low phototoxicity, and high fidelity in 3D and 4D (3D spatial + 1D time or spectra), this VR-LSFM hybrid methodology enables interactive visualization and quantification otherwise not available by conventional methods, such as routine optical microscopes. We hereby demonstrate multiscale applicability of VR-LSFM to (a) interrogate skin fibroblasts interacting with a hyaluronic acid–based hydrogel, (b) navigate through the endocardial trabecular network during zebrafish development, and (c) localize gene therapy-mediated potassium channel expression in adult murine hearts. We further combined our batch intensity normalized segmentation algorithm with deformable image registration to interface a VR environment with imaging computation for the analysis of cardiac contraction. Thus, the VR-LSFM hybrid platform demonstrates an efficient and robust framework for creating a user-directed microenvironment in which we uncovered developmental cardiac mechanics and physiology with high spatiotemporal resolution.A user-directed perspective for studying cardiac mechanics, physiology, and developmental biology at single-cell resolution.
- Published
- 2020