Quantifying three-dimensional preclinical myocardial deformation in vivo currently remains a challenging task, as non-invasive cardiac imaging methods are often restricted to two-dimensional projections suffering from limited reproducibility. Here, we introduce a 4D (3D + time) imaging and analysis platform that integrates a benchtop high-frame rate, modular light-sheet microscope (LSM) integrated with a deep-learning-enabled cardiomyocyte tracking pipeline. Our LSM achieves cellular resolution up to millimeter-scale field-of-view (FOV) at millisecond temporal sampling, allowing reconstruction of 4D trajectories of individual cardiomyocyte nuclei within embryonic zebrafish. To address segmentation failures arising from spatially overlapping nuclei within multilayered myocardium, we incorporated a difference-of-Gaussian and watershed-based preprocessing module into a 3D nnU-Net framework, enabling robust separation of cell-cell contact and mitigating nucleus-merging artifacts. This workflow supports reproducible extraction of myocardial deformation metrics and provides a scalable foundation for disease-specific biomechanical modeling. Together, our approach demonstrates how combining advanced LSM instrumentation with deep-learning-driven reconstruction pipelines can accelerate autonomous, high-throughput imaging of cardiac microstructure in vivo.

We investigate volumetric reconstruction for compressive sensing light-sheet microscopy (CS-LSM), where fast volumetric imaging is achieved by encoding multiple axial planes into each camera exposure. To recover the underlying volume from highly multiplexed measurements, we propose a plug-and-play (PnP) framework that flexibly incorporates any user-specified denoiser into the reconstruction process. Building on a slice-based formulation, we further introduce an axial-coupled model that exploits correlations between adjacent slices to improve volumetric continuity. For efficient computation, we derive a Woodbury-based update for the data-consistency step in both the slice-based and axial-coupled formulations, and employ a Gauss-Seidel sweep for the denoising step in the axial-coupled model. Under a weakly convex regularization assumption, we establish subsequential convergence of the proposed algorithm. Experiments on synthetic and real zebrafish-heart data demonstrate that the proposed framework successfully recovers cellular structures from compressed measurements, and provide practical insights into the comparative performance of commonly used denoisers within the PnP framework under the CS-LSM setup.

Investigating cardiac dynamics, including contractile function and intracardiac flow, requires volumetric imaging capable of resolving whole-organ events at micrometer resolution and millisecond timescales. However, the limited readout bandwidth of detectors imposes fundamental trade-offs among spatial sampling, field of view, and achievable volume rates. Here we introduce compressive axial-integrated planar scanning (CAPS) microscopy, a computational imaging framework that combines rapid light-sheet scanning, detection-side axial multiplexing with model-based reconstruction to enhance detector bandwidth utilization for high-speed volumetric imaging. Using widely accessible optical sensors and components, CAPS achieves cellular-scale resolving power across heart chambers at 200 volumes per second with an effective detector pixel rate of 5.82 GHz, representing a ∼15-fold increase in spatiotemporal throughput relative to uncompressed volumetric acquisition. Coordinated high-speed encoding and computational reconstruction further mitigate rolling-shutter distortions in CMOS sensors while preserving frame rate and intrinsic optical sectioning. We demonstrate that CAPS enables beat-resolved imaging of single-cell cardiomyocyte kinematics, chamber-scale contractile dynamics, and intracardiac hemodynamics in zebrafish larvae under both healthy and pharmacologically perturbed conditions. Collectively, these advances establish CAPS as a powerful framework for quantitative, in vivo characterization of coordinated and disrupted cardiac dynamics at cellular resolution, supporting high-speed volumetric interrogation of organ-level function and disease progression.

Image resolution and field of view in far-field optical microscopy are often inversely proportional to one another due to digital sampling limitations imposed by the magnification of the system and the pixel size of the sensor. We present a method including a spatial shifting mechanism and a reconstruction algorithm that bypasses this trade-off by shifting the sample to be imaged by subpixel increments, before registering the images via phase correlation and combining the resulting registered images using the shift-and-add approach. Importantly, this method requires no specific optical components that are uncommon to commercially available or custom-built microscope systems. The findings of the presented study demonstrate an improvement to spatial resolution of ∼42% while maintaining the system's field of view (FOV), leading to a more than twofold improvement to the system's space-bandwidth product (SBP).

Understanding cardiac microstructure and vascular networks in their entirety is critical for assessing cardiovascular development, disease progression, and therapeutic interventions. Light-sheet microscopy combined with tissue clearing enables high-resolution volumetric imaging of intact organs but faces limitations in trabeculated myocardium due to trade-offs among light-sheet thickness, effective range, and frame rate. We exploit temporal dynamics that govern illumination-detection interplay to maintain uniform resolution across specimens. Building on this, we implemented high-speed dithered light-sheet (DiLS) illumination, extending the confocal region by over 40% and enhancing the space-bandwidth product while preserving optical sectioning. Integration of DiLS with a sweeping approach establishes the axially swept dithered light-sheet (AS-DiLS), which enhances imaging throughput while preserving axial resolution and enables uniform illumination up to 12.5-millimeter range. AS-DiLS delivers near-isotropic resolution (~2.5 μm) for investigating intricate ventricular trabeculae, vasculature, and extracellular matrix, providing a scalable platform for comprehensive cardiovascular morphology and topology assessment from embryos to adults. Teaser:Volumetric imaging reveals microstructure and vascular networks in their entirety with near-isotropic resolution.

This review discusses current trends in the implementation and application of two emerging optical microscopy techniques—light-sheet microscopy (LSM) and light-field microscopy (LFM)—in cardiovascular research. It covers the principles and advantages of these imaging modalities, highlighting their current and potential applications that are new to researchers in the cardiovascular field. LSM and LFM have proven invaluable in studying cardiac development, regeneration, and aging in health and disease. Recent advances include investigations of structural features such as heart valves, trabecular networks, and aortic arch in murine models; dynamic processes like cardiac contraction, hemodynamics, remodeling, and neural activities in zebrafish models; and disease models including myocardial infarction using cardiac organoids. With their high-speed volumetric acquisition capabilities, these imaging methods are particularly suited to assessing cardiac structures and functions in three dimension and four dimensions during cardiac morphogenesis, as well as its aberrant processes. Given the unique advantages of LSM and LFM, their respective utilizations uncover structural and functional insights, underscoring a hitherto untapped potential to facilitate fundamental cardiovascular research.

The development of engraftable, long-term reconstituting hematopoietic stem cells (LT-HSC) from human pluripotent stem cells (hPSC) has been a long-sought goal. Since HSCs are formed by a subset of endothelial cells in the ventral part of the dorsal aorta, we analyzed heartbeat-mediated pulsatile displacement experienced by the walls of the dorsal aorta in zebrafish embryos. We found that pulsation-mediated circumferential stretch was restricted to the ventral part of the dorsal aorta and activated Piezo1 to stimulate LT-HSC formation. Stimulation of pulsation or Yoda1-mediated Piezo1 activation promoted the formation of de novo LT-HSCs from hemogenic endothelial cells derived from murine embryos or human pluripotent stem cells. These HSCs gave long-term multilineage reconstitution of hematopoietic cells upon transplantation into immunocompromised mice. The formation of transgene-free human LT-HSCs that can engraft and reconstitute the hematopoietic system will facilitate the generation of off-the-shelf HSCs from hPSCs for use in cellular therapies.

Cardiac contraction is a rapid, coordinated process that unfolds across three-dimensional tissue on millisecond timescales. Traditional optical imaging is often inadequate for capturing dynamic cellular structure in the beating heart because of a fundamental trade-off between spatial and temporal resolution. To overcome these limitations, we propose a high-performance computational imaging framework that integrates Compressive Sensing (CS) with Light-Sheet Microscopy (LSM) for efficient, low-phototoxic cardiac imaging. The system performs compressed acquisition of fluorescence signals via random binary mask coding using a Digital Micromirror Device (DMD). We propose a Plug-and-Play (PnP) framework, solved using the alternating direction method of multipliers (ADMM), which flexibly incorporates advanced denoisers, including Tikhonov, Total Variation (TV), and BM3D. To preserve structural continuity in dynamic imaging, we further introduce temporal regularization enforcing smoothness between adjacent z-slices. Experimental results on zebrafish heart imaging under high compression ratios demonstrate that the proposed method successfully reconstructs cellular structures with excellent denoising performance and image clarity, validating the effectiveness and robustness of our algorithm in real-world high-speed, low-light biological imaging scenarios.

Novel insights into cardiac contractile dysfunction at the cellular level could deepen understanding of arrhythmia and heart injury, which are leading causes of morbidity and mortality worldwide. We present a comprehensive experimental and computational framework combining light-field microscopy and single-cell tracking to investigate real-time volumetric data in live zebrafish hearts, which share structural and electrical similarities to the human heart. Our system acquires 200 vol/s with lateral resolution of up to 5.02 ± 0.54 μm and axial resolution of 9.02 ± 1.11 μm across the whole depth using an expectation-maximization-smoothed deconvolution algorithm. We apply a deep-learning approach to quantify cell displacement and velocity in blood flow and myocardial motion and to perform real-time volumetric tracking from end-systole to end-diastole within a virtual reality environment. This capability delivers high-speed and high-resolution imaging of cardiac contractility at single-cell resolution over multiple cycles, supporting in-depth investigation of intercellular interactions in health and disease.

Hypertrophic cardiomyopathy (HCM) is often caused by genetic mutations, resulting in abnormal thickening of ventricular muscle, particularly the septum, and causing left ventricular outflow tract (LVOT) obstruction and inferior cardiac performance. The cell and microstructural abnormalities are believed to be the cause of the altered tissue mechanical properties and inferior performance. However, there is a lack of detailed biomechanical assessments of human hypertrophied septum and a lack of understanding of the structural-mechanical relationship between altered biomechanical properties and cellular hypertrophy, fibrotic overexpression, and microstructural disruptions. In this study, we performed thorough biomechanical and microstructural characterizations on the human hypertrophied septum and compared this with healthy septum. We found that the hypertrophied human septum was stiffer at the initial phase of tissue loading, but less nonlinear, less stiff in the linear region, and much weaker in mechanical strength when compared to the healthy human septum. The fibrosis-induced initial stiffening in the hypertrophied septum paradoxically coexists with compromised mechanical strength and integrity under physiological demands, correlating with the clinical observations of diastolic dysfunction and susceptibility to myocardial damage in HCM patients despite ventricular wall thickening. We also discovered that the human hypertrophied septum had significantly larger stress relaxation and slightly larger creep when compared to healthy septum. Moreover, the abnormal, disorganized cell-collagen microstructures in the hypertrophied septum make short-term stress release more difficult and require longer relaxation times to reach equilibrium. Biaxial testing performed at the initial phase of tissue loading showed that both the healthy septum and hypertrophied septum had nonlinear anisotropic stress-strain behavior and confirmed that, in the longitudinal direction, the hypertrophied septum was stiffer than the healthy septum. Our microstructural quantifications via histology and light-sheet microscopy revealed that (i) the heterogeneous cardiomyocyte enlargement and disarray, combined with disorganized collagen overexpression, create a mechanically inefficient tissue architecture in the hypertrophied septum, and (ii) the observed cell-collagen microstructural disruptions provide mechanistic explanations for the deteriorated biomechanical properties. Our viscoelastic mechanical data and microstructural characterizations build a strong foundation to understand the altered tissue behavior of the hypertrophied septum, the degree of deviation from the normal septum, and the underlying structural mechanisms.

This is the first study detailing normal lymphatic vessel distribution at various cardiac anatomical sites using a lymphatic reporter mouse model, multiple markers, and modern imaging modalities, providing a blueprint for future studies. We also performed integrated single-cell RNA sequencing (scRNA-Seq) analysis to define the cellular and transcriptional heterogeneity of cardiac lymphatic endothelial cells. Finally, our study underscores the nonspecific nature of lymphatic markers and emphasizes the necessity of using at least two markers to identify lymphatic vessels.

Light Sheet Microscopy (LSM) in conjunction with embryonic zebrafish, is rapidly advancing three-dimensional, in vivo characterization of myocardial contractility. Preclinical cardiac deformation imaging is predominantly restricted to a low-order dimensionality image space (2D) or suffers from poor reproducibility. In this regard, LSM has enabled high throughput, non-invasive 4D (3d+time) characterization of dynamic organogenesis within the transparent zebrafish model. More importantly, LSM offers cellular resolution across large imaging Field-of-Views at millisecond camera frame rates, enabling single cell localization for global cardiac deformation analysis. However, manual labeling of cells within multilayered tissue is a time-consuming task and requires substantial expertise. In this study, we applied the 3D nnU-Net with Linear Assignment Problem (LAP) framework for automated segmentation and tracking of myocardial cells. Using binarized labels from the neural network, we quantified myocardial deformation of the zebrafish ventricle across 4-6 days post fertilization (dpf). Our study offers tremendous promise for developing highly scalable and disease-specific biomechanical quantification of myocardial microstructures.

Advanced understanding of cardiac structure and function is crucial for uncovering the underlying mechanism of injury and arrhythmias. To explore cues to structural and functional abnormalities in extensively established animal models, we have developed optical imaging and computational methods tailored to investigate intact hearts of zebrafish and rodents at cellular resolution. Our cardiac light-field microscopy allows us to capture instantaneous dynamics such as calcium transients, irregular contraction, and blood flow at 200 volumes per second in zebrafish larvae 1 . To improve the spatial resolution and enable the study of rodent models, we have customized two light-sheet imaging systems. One system is empowered by the retrospective synchronization and machine learning for the study of contractile function and focal myocardial mechanics from end-systole to end-diastole 2 , while the other integrates tissue clearing and axially scanning approaches for the exploration of ventricular trabeculation and myocardial compaction 3 . These methods aim to overcome the trade-off in spatial resolution, imaging speed, field of view across the atria and ventricles with minimal photo-damage and maximal penetration depth, enabling long-term investigation of cardiac development and regenerative processes. To further interpret the large volume of datasets, we have customized a successive subspace learning and virtual reality-based platform for interactive image analysis 4 . Collectively, our multi-scale strategy has opened up new landscapes for exploring the cardiac micro-structure and contractile function, both in health and disease. References 1. Saberigarakani A, et al. Light-field microscopy to study cardiac arrhythmias in zebrafish larvae. In: Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXXI. 2024. p. 48–55. 2. Zhang X, et al. 4D Light-sheet imaging and interactive analysis of cardiac contractility in zebrafish larvae. APL Bioeng . 2023;7:26112. 3. Almasian M, et al. 3D isotropic light-sheet imaging to reveal the structure of neonatal mouse hearts. In: Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXXI. 2024. p. PC128480F. 4. Yuan J, et al. Extended reality for biomedicine. Nat Rev Methods Prim . 2023;3:14.

Light-sheet microscopy (LSM) plays a pivotal role in comprehending the intricate three-dimensional (3D) structure of the heart, providing crucial insights into fundamental cardiac physiology and pathologic responses. We hereby delve into the development and implementation of the LSM technique to elucidate the micro-architecture of the heart in mouse models. The methodology integrates a customized LSM system with tissue clearing techniques, mitigating light scattering within cardiac tissues for volumetric imaging. The combination of conventional LSM with image stitching and multiview deconvolution approaches allows for the capture of the entire heart. To address the inherent trade-off between axial resolution and field of view (FOV), we further introduce an axially swept light-sheet microscopy (ASLM) method to minimize out-of-focus light and uniformly illuminate the heart across the propagation direction. In the meanwhile, tissue clearing methods such as iDISCO enhance light penetration, facilitating the visualization of deep structures and ensuring a comprehensive examination of the myocardium throughout the entire heart. The combination of the proposed LSM and tissue clearing methods presents a promising platform for researchers in resolving cardiac structures in rodent hearts, holding great potential for the understanding of cardiac morphogenesis and remodeling.

The neonatal mouse heart in contrast to the adults has the ability to regenerate after myocardial infarction. The investigation of cardiac morphogenesis is critical to uncover the underlying mechanism of cardiac regeneration. Hence, we have developed a light-sheet microscope (LSM) along with the tissue-clearing method to investigate the 3-dimensional (3D) architecture of the intact neonatal mouse heart. We improved our imaging system by incorporating an axially swept remote focusing arm with a voice coil actuator for isotropic imaging. Our LSM offers a lateral resolution of 2.08 ± 0.11 μm and an axial resolution of 2.84 ± 0.19 μm. Using this strategy, we can take optical sections throughout the intact heart and enabling us to reveal the cardiac structure of the neonatal mouse.

Paroxysmal arrhythmias caused by medications are challenging to be prospectively identified. Zebrafish have emerged as an ideal model organism for screening small molecule compounds to study cardiac abnormalities, due to their rapid development, optical transparency during early stages, and similarities to the human heart. To overcome the challenges associated with observing cardiac abnormalities in zebrafish, we sought to develop a light-field microscope, a rapid imaging method with high photon efficiency, for the volumetric acquisition in a single snapshot. This method, along with its variations, utilizes a multi-lens array (MLA) to capture angular information. We have customized a light-field system and developed a pipeline to incorporate the MLA into the detection path. A program based on wave optics has also been developed to calculate the point spread function at different depths. The program involves two main steps: calculating the wide-field PSF and applying the MLA effect as a mask. This enables us to simulate the impact of the MLA on the imaging system. The comparison between the simulated and experimental data allows for the determination of MLA position. We aim to capture drug-induced arrhythmias in zebrafish larvae using this method, exploring the contractile dysfunction across the atrium and ventricle during multiple cardiac cycles. This research aims to deepen our understanding of the mechanisms underlying these arrhythmias and their connection to drug effects.

For a long time, search and rescue operations during natural disasters and man-made catastrophes have been a major challenge. Due to the rapidly changing environment in disasters, deploying rescue teams for search missions entails significant risks. With advancements in technology, the latest innovations can be applied to search and rescue tasks to reduce these risks. LiDAR (Light Detection and Ranging) sensors can be installed on unmanned search and rescue vehicles to explore the space. This article utilizes solid-state LiDAR technology, along with various algorithms like SLAM (Simultaneous Localization and Mapping) and EKF (Extended Kalman Filter), to design a remotely controlled unmanned exploration vehicle. By capturing point cloud data, it enables modelling and recording of indoor or outdoor spaces, allowing for space exploration and the identification of trapped individuals and other important rescue-related information before rescue personnel enter the premises. This significantly reduces the risks and time involved in search and rescue operations. The prototype vehicle designed in this paper possesses the advantages of low cost and high flexibility, making it feasible for direct deployment after minor optimization. Finally, the author provides a summary and outlook for this research.

Objectives: Virtual reality (VR) is an increasingly valuable teaching tool, but current simulators are not typically clinically scalable due to their reliance on inefficient manual segmentation. The objective of this project was to leverage a high-throughput and accurate machine learning method to automate data preparation for a patient-specific VR simulator used to explore preoperative sinus anatomy Methods: An endoscopic VR simulator was designed in Unity to enable interactive exploration of sinus anatomy. The Saak transform, a data-efficient machine learning method, was adapted to accurately segment sinus CT scans using minimal training data, and the resulting data was reconstructed into 3D patient-specific models that could be explored in the simulator. Results: Using minimal training data, the Saak transform-based machine learning method offers accurate soft-tissue segmentation. When explored with an endoscope in the VR simulator, the anatomical models generated by the algorithm accurately capture key sinus structures and showcase patient-specific variability in anatomy. Conclusions: By offering an automatic means of preparing VR models from a patient’s raw CT scans, this pipeline takes a key step towards clinical scalability. In addition to preoperative planning, this system also enables virtual endoscopy—a tool that is particularly useful in the COVID-19 era. As VR technology inevitably continues to develop, such a foundation will help ensure that future innovations remain clinically accessible.

Zebrafish is an intriguing model organism known for its remarkable cardiac regeneration capacity. Studying the contracting heart in vivo is essential for gaining insights into structural and functional changes in response to injuries. However, obtaining high-resolution and high-speed 4-dimensional (4D, 3D spatial + 1D temporal) images of the zebrafish heart to assess cardiac architecture and contractility remains challenging. In this context, an in-house light-sheet microscope (LSM) and customized computational analysis are used to overcome these technical limitations. This strategy, involving LSM system construction, retrospective synchronization, single cell tracking, and user-directed analysis, enables one to investigate the micro-structure and contractile function across the entire heart at the single-cell resolution in the transgenic Tg(myl7:nucGFP) zebrafish larvae. Additionally, we are able to further incorporate microinjection of small molecule compounds to induce cardiac injury in a precise and controlled manner. Overall, this framework allows one to track physiological and pathophysiological changes, as well as the regional mechanics at the single-cell level during cardiac morphogenesis and regeneration.