light-sheet-fluorescence-microscopy-to-capture-4-dimensional-images

Light-sheet Fluorescence Microscopy to Capture 4-Dimensional Images of the Effects of Modulating Shear Stress on the Developing Zebrafish Heart

The hemodynamic forces experienced by the heart influence cardiac development, especially trabeculation, which forms a network of branching outgrowths ...

light-sheet-fluorescence-microscopy-for-the-study-of-the-murine-heart

Light-sheet Fluorescence Microscopy for the Study of the Murine Heart

Light-sheet fluorescence microscopy has been widely used for rapid image acquisition with a high axial resolution from micrometer to millimeter scale. ...

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 ...

light-sheet-imaging-to-reveal-cardiac-structure-in-rodent-hearts

Light-Sheet Imaging to Reveal Cardiac Structure in Rodent Hearts

Light-sheet microscopy (LSM) plays a pivotal role in comprehending the intricate three-dimensional (3D) structure of the heart, providing crucial insights ...

UCLA

University of California Los Angeles

The University of Texas at Dallas

UT Southwestern Medical Center

Blood viscosity provides the rheological basis to elucidate shear stress underlying developmental cardiac mechanics and physiology. Zebrafish is a high throughput model for developmental biology, forward-genetics, and drug discovery. The micro-scale posed an experimental challenge to measure blood viscosity. To address this challenge, a microfluidic viscometer driven by surface tension was developed to reduce the sample volume required (3μL) for rapid (<2 min) and continuous viscosity measurement. By fitting the power-law fluid model to the travel distance of blood through the micro-channel as a function of time and channel configuration, the experimentally acquired blood viscosity was compared with a vacuum-driven capillary viscometer at high shear rates (>500 s), at which the power law exponent (n) of zebrafish blood was nearly 1 behaving as a Newtonian fluid. The measured values of whole blood from the micro-channel (4.17cP) and the vacuum method (4.22cP) at 500 s were closely correlated at 27 °C. A calibration curve was established for viscosity as a function of hematocrits to predict a rise and fall in viscosity during embryonic development. Thus, our rapid capillary pressure-driven micro-channel revealed the Newtonian fluid behavior of zebrafish blood at high shear rates and the dynamic viscosity during development.

A Rapid Capillary-Pressure Driven Micro-Channel to Demonstrate Newtonian Fluid Behavior of Zebrafish Blood at High Shear Rates.

Deep neural networks have become the mainstream approach for analyzing and interpreting histology images. In this study, we established and validated an interpretable DNN model to assess endomyocardial biopsy (EMB) data of patients with myocardial injury. Deep learning models were used to extract features and classify EMB histopathological images of heart failure cases diagnosed with either ischemic cardiomyopathy or idiopathic dilated cardiomyopathy and non-failing cases (organ donors without a history of heart failure). We utilized the gradient-weighted class activation mapping (Grad-CAM) technique to emphasize injured regions, providing an entry point to assess the dominant morphology in the process of a comprehensive evaluation. To visualize clustered regions of interest (ROI), we utilized uniform manifold approximation and projection (UMAP) embedding for dimension reduction. We further implemented a multi-model ensemble mechanism to improve the quantitative metric (area under the receiver operating characteristic curve, AUC) to 0.985 and 0.992 on ROI-level and case-level, respectively, outperforming the achievement of 0.971 ± 0.017 and 0.981 ± 0.020 based on the sub-models. Collectively, this new methodology provides a robust and interpretive framework to explore local histopathological patterns, facilitating the automatic and high-throughput quantification of cardiac EMB analysis.

Deep Neural Network-Aided Histopathological Analysis of Myocardial Injury.

Heart failure results in the high incidence and mortality all over the world. Mechanical properties of myocardium are critical determinants of cardiac function, with regional variations in myocardial contractility demonstrated within infarcted ventricles. Quantitative assessment of cardiac contractile function is therefore critical to identify myocardial infarction for the early diagnosis and therapeutic intervention.

Computational Analysis of Cardiac Contractile Function.

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.

Article Total : 4	Year
Publication title	2018
Publication title	2018
Publication title	2024
Publication title	2024

Article	Year
A Rapid Capillary-Pressure Driven Micro-Channel to Demonstrate Newtonian Fluid Behavior of Zebrafish Blood at High Shear Rates. Scientific reports\| PubMed ID: 28512313	2017
Deep Neural Network-Aided Histopathological Analysis of Myocardial Injury. Frontiers in cardiovascular medicine\| PubMed ID: 35083295	2021
Computational Analysis of Cardiac Contractile Function. Current cardiology reports\| PubMed ID: 36301405	2022
Light sheet imaging and interactive analysis of the cardiac structure in neonatal mice. Journal of biophotonics\| PubMed ID: 36624523	2023
Virtual Reality for Interactive Medical Analysis. Frontiers in virtual reality\| PubMed ID: 36711187	2022
Extended reality for biomedicine. Nature reviews. Methods primers\| PubMed ID: 37051227	2023
4D Light-sheet imaging and interactive analysis of cardiac contractility in zebrafish larvae. APL bioengineering\| PubMed ID: 37351330	2023

Yichen Ding

Biography

JoVE Journal Publications

Other Publications