4d-light-sheet-imaging-of-zebrafish-cardiac-contraction

4D Light-sheet Imaging of Zebrafish Cardiac Contraction

Zebrafish is an intriguing model organism known for its remarkable cardiac regeneration capacity. Studying the contracting heart in vivo is essential for ...

The University of Texas at Dallas

Light-sheet microscopy (LSM) enables us to strengthen the understanding of cardiac development, injury, and regeneration in mammalian models. This emerging technique decouples laser illumination and fluorescence detection to investigate cardiac micro-structure and function with a high spatial resolution while minimizing photodamage and maximizing penetration depth. To unravel the potential of volumetric imaging in cardiac development and repair, we sought to integrate our in-house LSM, Adipo-Clear, and virtual reality (VR) with neonatal mouse hearts. We demonstrate the use of Adipo-Clear to render mouse hearts transparent, the development of our in-house LSM to capture the myocardial architecture within the intact heart, and the integration of VR to explore, measure, and assess regions of interests in an interactive manner. Collectively, we have established an innovative and holistic strategy for image acquisition and interpretation, providing an entry point to assess myocardial micro-architecture throughout the entire mammalian heart for the understanding of cardiac morphogenesis.

Light sheet imaging and interactive analysis of the cardiac structure in neonatal mice.

Molecular imaging along with 3-dimensional (3-D) or 4-D (3-D spatial + 1-D temporal) visualization is widely used in clinical diagnosis and surgical planning. However, the pre-defined perspective and confined manipulation limit the in-depth exploration and analysis in 3-D / 4-D. To overcome this obstacle, we utilized virtual reality (VR) to interact with CT images of the cardiopulmonary system in a 3-D immersive environment. We implemented manipulative functionalities into the VR environment that altered the cardiopulmonary models to interactively generate new data analysis perspectives. We successfully sliced a CT cardiac model showing in-depth surface visualizations of the ventricles and atria. Our customized framework enables enhanced data interpretation interactivity of CT images and establishes a user-directed manipulative VR platform derived from imaging results for remote medical practices including training, education, and investigation.

Virtual Reality for Interactive Medical Analysis.

Extended reality (XR) refers to an umbrella of methods that allows users to be immersed in a three-dimensional (3D) or a 4D (spatial + temporal) virtual environment to different extents, including virtual reality (VR), augmented reality (AR), and mixed reality (MR). While VR allows a user to be fully immersed in a virtual environment, AR and MR overlay virtual objects over the real physical world. The immersion and interaction of XR provide unparalleled opportunities to extend our world beyond conventional lifestyles. While XR has extensive applications in fields such as entertainment and education, its numerous applications in biomedicine create transformative opportunities in both fundamental research and healthcare. This Primer outlines XR technology from instrumentation to software computation methods, delineating the biomedical applications that have been advanced by state-of-the-art techniques. We further describe the technical advances overcoming current limitations in XR and its applications, providing an entry point for professionals and trainees to thrive in this emerging field.

Extended reality for biomedicine.

Despite ongoing efforts in cardiovascular research, the acquisition of high-resolution and high-speed images for the purpose of assessing cardiac contraction remains challenging. Light-sheet fluorescence microscopy (LSFM) offers superior spatiotemporal resolution and minimal photodamage, providing an indispensable opportunity for the  study of cardiac micro-structure and contractile function in zebrafish larvae. To track the myocardial architecture and contractility, we have developed an imaging strategy ranging from LSFM system construction, retrospective synchronization, single cell tracking, to user-directed virtual reality (VR) analysis. Our system enables the four-dimensional (4D) investigation of individual cardiomyocytes across the entire atrium and ventricle during multiple cardiac cycles in a zebrafish larva at the cellular resolution. To enhance the throughput of our model reconstruction and assessment, we have developed a parallel computing-assisted algorithm for 4D synchronization, resulting in a nearly tenfold enhancement of reconstruction efficiency. The machine learning-based nuclei segmentation and VR-based interaction further allow us to quantify cellular dynamics in the myocardium from end-systole to end-diastole. Collectively, our strategy facilitates noninvasive cardiac imaging and user-directed data interpretation with improved efficiency and accuracy, holding great promise to characterize functional changes and regional mechanics at the single cell level during cardiac development and regeneration.

Sohail Hassan

Department of Bioengineering

The University of Texas at Dallas

4D Light-sheet Imaging of Zebrafish Cardiac Contraction

Sohail Hassan

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Bioengineering

The University of Texas at Dallas

4D Light-sheet Imaging of Zebrafish Cardiac Contraction

Department of Bioengineering