Integrating light-sheet imaging with virtual reality to recapitulate developmental cardiac mechanics.

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Ding, Y; Abiri, A; Abiri, P; Li, S; Chang, C-C; Baek, KI; Hsu, JJ; Sideris, E; Li, Y; Lee, J; Segura, T; Nguyen, TP; Bui, A; Sevag Packard, RR; Fei, P; Hsiai, TK

Published Date

  • November 16, 2017

Published In

Volume / Issue

  • 2 / 22

PubMed ID

  • 29202458

Pubmed Central ID

  • 29202458

Electronic International Standard Serial Number (EISSN)

  • 2379-3708

International Standard Serial Number (ISSN)

  • 2379-3708

Digital Object Identifier (DOI)

  • 10.1172/jci.insight.97180

Language

  • eng