PUBLICATION

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

Authors
Ding, Y., Abiri, A., Abiri, P., Li, S., Chang, C.C., Baek, K.I., Hsu, J.J., Sideris, E., Li, Y., Lee, J., Segura, T., Nguyen, T.P., Bui, A., Sevag Packard, R.R., Fei, P., Hsiai, T.K.
ID
ZDB-PUB-171205-13
Date
2017
Source
JCI insight   2(22): (Journal)
Registered Authors
Baek, Kyung
Keywords
Cardiology, Diagnostic imaging
MeSH Terms
  • Algorithms
  • Animals
  • Cardiac Imaging Techniques/methods*
  • Developmental Biology
  • Fibroblasts
  • Heart/diagnostic imaging*
  • Heart/physiology*
  • Hyaluronic Acid
  • Mechanics*
  • Mice
  • Mice, Inbred C57BL
  • Microscopy, Fluorescence/methods*
  • Models, Animal
  • Potassium Channels
  • Virtual Reality*
  • Zebrafish
PubMed
29202458 Full text @ JCI Insight
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.
Genes / Markers
Figures
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Antibodies
Orthology
Engineered Foreign Genes
Mapping