Simulating Developmental Cardiac Morphology in Virtual Reality Using a Deformable Image Registration Approach
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.
© 2018 Biomedical Engineering Society. Received: 01 May 2018; Accepted: 07 August 2018; First Online: 15 August 2018. This work was supported by the National Institutes of Health (5R01HL083015-10, 1R01HL118650, 1R01HL129727, 7R01HL111437) and the American Heart Association (Career Development Award 18CDA34110338, Scientist Development Grant 16SDG30910007). The authors declare no competing financial interests.
Supplemental Material - 10439_2018_2113_MOESM1_ESM.mov
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