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Annals of biomedical engineering
Dec, 2018;46 (12): 2177-2188.

Simulating Developmental Cardiac Morphology in Virtual Reality Using a Deformable Image Registration Approach.

Arash Abiri, Yichen Ding, Parinaz Abiri, René R Sevag Packard, Vijay Vedula, Alison Marsden, C-C Jay Kuo, Tzung K Hsiai
Author Information
  1. Arash Abiri: Department of Bioengineering, University of California, Los Angeles, CA, 90095, USA.
  2. Yichen Ding: Department of Bioengineering, University of California, Los Angeles, CA, 90095, USA.
  3. Parinaz Abiri: Department of Bioengineering, University of California, Los Angeles, CA, 90095, USA.
  4. René R Sevag Packard: Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA.
  5. Vijay Vedula: Department of Pediatrics (Cardiology), Stanford University, Stanford, CA, 94305, USA.
  6. Alison Marsden: Department of Pediatrics (Cardiology), Stanford University, Stanford, CA, 94305, USA.
  7. C-C Jay Kuo: Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA.
  8. Tzung K Hsiai: Department of Bioengineering, University of California, Los Angeles, CA, 90095, USA. THsiai@mednet.ucla.edu.
PMID: 30112710 DOI: 10.1007/s10439-018-02113-z

Abstract

While virtual reality (VR) has potential in enhancing cardiovascular diagnosis and treatment, prerequisite labor-intensive image segmentation remains an obstacle for seamlessly simulating 4-dimensional (4-D, 3-D + time) imaging data in an immersive, physiological VR environment. We applied deformable image registration (DIR) in conjunction with 3-D reconstruction and VR implementation to recapitulate developmental cardiac contractile function from light-sheet fluorescence microscopy (LSFM). This method addressed inconsistencies that would arise from independent segmentations of time-dependent data, thereby enabling the creation of a VR environment that fluently simulates cardiac morphological changes. By analyzing myocardial deformation at high spatiotemporal resolution, we interfaced quantitative computations with 4-D VR. We demonstrated that our LSFM-captured images, followed by DIR, yielded average dice similarity coefficients of 0.92 ± 0.05 (n = 510) and 0.93 ± 0.06 (n = 240) when compared to ground truth images obtained from Otsu thresholding and manual segmentation, respectively. The resulting VR environment simulates a wide-angle zoomed-in view of motion in live embryonic zebrafish hearts, in which the cardiac chambers are undergoing structural deformation throughout the cardiac cycle. Thus, this technique allows for an interactive micro-scale VR visualization of developmental cardiac morphology to enable high resolution simulation for both basic and clinical science.

Keywords

Cardiology Dynamic imaging Image registration Light-sheet imaging Medical simulation Surgical simulation

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Grants

  1. 5R01HL083015-10/National Institutes of Health
  2. 1R01HL118650/National Institutes of Health
  3. R01 HL129727/NHLBI NIH HHS
  4. 1R01HL129727/National Institutes of Health
  5. R01 HL118650/NHLBI NIH HHS
  6. 7R01HL111437/National Institutes of Health
  7. 16SDG30910007/American Heart Association
  8. R01 HL111437/NHLBI NIH HHS
  9. R01 HL121754/NHLBI NIH HHS
  10. R01 HL083015/NHLBI NIH HHS

MeSH Term

Animals
Embryo, Nonmammalian
Heart
Image Processing, Computer-Assisted
Microscopy, Fluorescence
Virtual Reality
Zebrafish
Journal Article
Article has an altmetric score of 3

Word Cloud

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