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.

Light Sheet Fluorescence Microscopy (LSFM) enables multi-dimensional and multi-scale imaging via illuminating specimens with a separate thin sheet of laser. It allows rapid plane illumination for reduced photo-damage and superior axial resolution and contrast. We hereby demonstrate cardiac LSFM (c-LSFM) imaging to assess the functional architecture of zebrafish embryos with a retrospective cardiac synchronization algorithm for four-dimensional reconstruction (3-D space + time). By combining our approach with tissue clearing techniques, we reveal the entire cardiac structures and hypertrabeculation of adult zebrafish hearts in response to doxorubicin treatment. By integrating the resolution enhancement technique with c-LSFM to increase the resolving power under a large field-of-view, we demonstrate the use of low power objective to resolve the entire architecture of large-scale neonatal mouse hearts, revealing the helical orientation of individual myocardial fibers. Therefore, our c-LSFM imaging approach provides multi-scale visualization of architecture and function to drive cardiovascular research with translational implication in congenital heart diseases.

Hemodynamic shear forces are intimately linked with cardiac development, during which trabeculae form a network of branching outgrowths from the myocardium. Mutations that alter Notch signaling also result in trabeculation defects. Here, we assessed whether shear stress modulates trabeculation to influence contractile function. Specifically, we acquired 4D (3D + time) images with light sheets by selective plane illumination microscopy (SPIM) for rapid scanning and deep axial penetration during zebrafish morphogenesis. Reduction of blood viscosity via gata1a morpholino oligonucleotides (MO) reduced shear stress, resulting in downregulation of Notch signaling and attenuation of trabeculation. Arrest of cardiomyocyte contraction either by troponin T type 2a (tnnt2a) MO or in weak atriumm58 (wea) mutants resulted in reduced shear stress and downregulation of Notch signaling and trabeculation. Integrating 4D SPIM imaging with synchronization algorithm demonstrated that coinjection of neuregulin1 mRNA with gata1 MO rescued trabeculation to restore contractile function in association with upregulation of Notch-related genes. Crossbreeding of Tg(flk:mCherry) fish, which allows visualization of the vascular system with the Tg(tp1:gfp) Notch reporter line, revealed that shear stress-mediated Notch activation localizes to the endocardium. Deleting endocardium via the clochesk4 mutants downregulated Notch signaling, resulting in nontrabeculated ventricle. Subjecting endothelial cells to pulsatile flow in the presence of the ADAM10 inhibitor corroborated shear stress-activated Notch signaling to modulate trabeculation.

Objective

Recent advances in light-sheet fluorescence microscopy (LSFM) enable 3-dimensional (3-D) imaging of cardiac architecture and mechanics in toto. However, segmentation of the cardiac trabecular network to quantify cardiac injury remains a challenge.

Methods

We hereby employed "subspace approximation with augmented kernels (Saak) transform" for accurate and efficient quantification of the light-sheet image stacks following chemotherapy-treatment. We established a machine learning framework with augmented kernels based on the Karhunen-Loeve Transform (KLT) to preserve linearity and reversibility of rectification.

Results

The Saak transform-based machine learning enhances computational efficiency and obviates iterative optimization of cost function needed for neural networks, minimizing the number of training datasets for segmentation in our scenario. The integration of forward and inverse Saak transforms can also serve as a light-weight module to filter adversarial perturbations and reconstruct estimated images, salvaging robustness of existing classification methods. The accuracy and robustness of the Saak transform are evident following the tests of dice similarity coefficients and various adversary perturbation algorithms, respectively. The addition of edge detection further allows for quantifying the surface area to volume ratio (SVR) of the myocardium in response to chemotherapy-induced cardiac remodeling.

Conclusion

The combination of Saak transform, random forest, and edge detection augments segmentation efficiency by 20-fold as compared to manual processing.

Significance

This new methodology establishes a robust framework for post light-sheet imaging processing, and creating a data-driven machine learning for automated quantification of cardiac ultra-structure.