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Ye L, Chang CC, Li Q, Tintut Y, Hsu JJ. Advanced Imaging Techniques for Atherosclerosis and Cardiovascular Calcification in Animal Models. J Cardiovasc Dev Dis 2024; 11:410. [PMID: 39728300 DOI: 10.3390/jcdd11120410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2024] [Revised: 12/13/2024] [Accepted: 12/18/2024] [Indexed: 12/28/2024] Open
Abstract
The detection and assessment of atherosclerosis and cardiovascular calcification can inform risk stratification and therapies to reduce cardiovascular morbidity and mortality. In this review, we provide an overview of current and emerging imaging techniques for assessing atherosclerosis and cardiovascular calcification in animal models. Traditional imaging modalities, such as computed tomography (CT) and magnetic resonance imaging (MRI), offer non-invasive approaches of visualizing atherosclerotic calcification in vivo; integration of these techniques with positron emission tomography (PET) imaging adds molecular imaging capabilities, such as detection of metabolically active microcalcifications with 18F-sodium fluoride. Photoacoustic imaging provides high contrast that enables in vivo evaluation of plaque composition, yet this method is limited by optical penetration depth. Light-sheet fluorescence microscopy provides high-resolution, three-dimensional imaging of cardiovascular structures and has been used for ex vivo assessment of atherosclerotic calcification, but its limited tissue penetration and requisite complex sample preparation preclude its use in vivo to evaluate cardiac tissue. Overall, with these evolving imaging tools, our understanding of cardiovascular calcification development in animal models is improving, and the combination of traditional imaging techniques with emerging molecular imaging modalities will enhance our ability to investigate therapeutic strategies for atherosclerotic calcification.
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Affiliation(s)
- Lifang Ye
- Heart Center, Department of Cardiovascular Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou 310014, China
- Department of Medicine, University of California, 650 Charles E Young Dr. S, Center for Health Sciences, Room A2-237, Los Angeles, CA 90095, USA
| | - Chih-Chiang Chang
- Department of Medicine, University of California, 650 Charles E Young Dr. S, Center for Health Sciences, Room A2-237, Los Angeles, CA 90095, USA
- Department of Bioengineering, University of California, Los Angeles, CA 90095, USA
| | - Qian Li
- Department of Medicine, University of California, 650 Charles E Young Dr. S, Center for Health Sciences, Room A2-237, Los Angeles, CA 90095, USA
| | - Yin Tintut
- Department of Medicine, University of California, 650 Charles E Young Dr. S, Center for Health Sciences, Room A2-237, Los Angeles, CA 90095, USA
- Department of Physiology, University of California, Los Angeles, CA 90095, USA
- Department of Orthopedic Surgery, University of California, Los Angeles, CA 90404, USA
| | - Jeffrey J Hsu
- Department of Medicine, University of California, 650 Charles E Young Dr. S, Center for Health Sciences, Room A2-237, Los Angeles, CA 90095, USA
- Department of Bioengineering, University of California, Los Angeles, CA 90095, USA
- Department of Medicine, Veterans Affairs Greater Los Angeles Health Care System, Los Angeles, CA 90073, USA
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Saberigarakani A, Patel RP, Almasian M, Zhang X, Brewer J, Hassan SS, Chai J, Lee J, Fei B, Yuan J, Carroll K, Ding Y. Volumetric imaging and computation to explore contractile function in zebrafish hearts. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.11.14.623621. [PMID: 39605398 PMCID: PMC11601419 DOI: 10.1101/2024.11.14.623621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2024]
Abstract
Despite advancements in cardiovascular engineering, heart diseases remain a leading cause of mortality. The limited understanding of the underlying mechanisms of cardiac dysfunction at the cellular level restricts the development of effective screening and therapeutic methods. To address this, we have developed a framework that incorporates light field detection and individual cell tracking to capture real-time volumetric data in zebrafish hearts, which share structural and electrical similarities with the human heart and generate 120 to 180 beats per minute. Our results indicate that the in-house system achieves an acquisition speed of 200 volumes per second, with resolutions of up to 5.02 ± 0.54 µm laterally and 9.02 ± 1.11 µm axially across the entire depth, using the estimated-maximized-smoothed deconvolution method. The subsequent deep learning-based cell trackers enable further investigation of contractile dynamics, including cellular displacement and velocity, followed by volumetric tracking of specific cells of interest from end-systole to end-diastole in an interactive environment. Collectively, our strategy facilitates real-time volumetric imaging and assessment of contractile dynamics across the entire ventricle at the cellular resolution over multiple cycles, providing significant potential for exploring intercellular interactions in both health and disease.
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Zhu E, Li YR, Margolis S, Wang J, Wang K, Zhang Y, Wang S, Park J, Zheng C, Yang L, Chu A, Zhang Y, Gao L, Hsiai TK. Frontiers in artificial intelligence-directed light-sheet microscopy for uncovering biological phenomena and multi-organ imaging. VIEW 2024; 5:20230087. [PMID: 39478956 PMCID: PMC11521201 DOI: 10.1002/viw.20230087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 07/18/2024] [Indexed: 11/02/2024] Open
Abstract
Light-sheet fluorescence microscopy (LSFM) introduces fast scanning of biological phenomena with deep photon penetration and minimal phototoxicity. This advancement represents a significant shift in 3-D imaging of large-scale biological tissues and 4-D (space + time) imaging of small live animals. The large data associated with LSFM requires efficient imaging acquisition and analysis with the use of artificial intelligence (AI)/machine learning (ML) algorithms. To this end, AI/ML-directed LSFM is an emerging area for multi-organ imaging and tumor diagnostics. This review will present the development of LSFM and highlight various LSFM configurations and designs for multi-scale imaging. Optical clearance techniques will be compared for effective reduction in light scattering and optimal deep-tissue imaging. This review will further depict a diverse range of research and translational applications, from small live organisms to multi-organ imaging to tumor diagnosis. In addition, this review will address AI/ML-directed imaging reconstruction, including the application of convolutional neural networks (CNNs) and generative adversarial networks (GANs). In summary, the advancements of LSFM have enabled effective and efficient post-imaging reconstruction and data analyses, underscoring LSFM's contribution to advancing fundamental and translational research.
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Affiliation(s)
- Enbo Zhu
- Department of Bioengineering, UCLA, California, 90095, USA
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, UCLA, California, 90095, USA
- Department of Medicine, Greater Los Angeles VA Healthcare System, California, 90073, USA
- Department of Microbiology, Immunology & Molecular Genetics, UCLA, California, 90095, USA
| | - Yan-Ruide Li
- Department of Microbiology, Immunology & Molecular Genetics, UCLA, California, 90095, USA
| | - Samuel Margolis
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, UCLA, California, 90095, USA
| | - Jing Wang
- Department of Bioengineering, UCLA, California, 90095, USA
| | - Kaidong Wang
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, UCLA, California, 90095, USA
- Department of Medicine, Greater Los Angeles VA Healthcare System, California, 90073, USA
| | - Yaran Zhang
- Department of Bioengineering, UCLA, California, 90095, USA
| | - Shaolei Wang
- Department of Bioengineering, UCLA, California, 90095, USA
| | - Jongchan Park
- Department of Bioengineering, UCLA, California, 90095, USA
| | - Charlie Zheng
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, UCLA, California, 90095, USA
| | - Lili Yang
- Department of Microbiology, Immunology & Molecular Genetics, UCLA, California, 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, UCLA, California, 90095, USA
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, UCLA, California, 90095, USA
- Molecular Biology Institute, UCLA, California, 90095, USA
| | - Alison Chu
- Division of Neonatology and Developmental Biology, Department of Pediatrics, David Geffen School of Medicine, UCLA, California, 90095, USA
| | - Yuhua Zhang
- Doheny Eye Institute, Department of Ophthalmology, UCLA, California, 90095, USA
| | - Liang Gao
- Department of Bioengineering, UCLA, California, 90095, USA
| | - Tzung K. Hsiai
- Department of Bioengineering, UCLA, California, 90095, USA
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, UCLA, California, 90095, USA
- Department of Medicine, Greater Los Angeles VA Healthcare System, California, 90073, USA
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Gudapati V, Chen A, Meyer S, Jay Kuo CC, Ding Y, Hsiai TK, Wang M. Development of a Machine Learning-Enabled Virtual Reality Tool for Preoperative Planning of Functional Endoscopic Sinus Surgery. J Neurol Surg Rep 2024; 85:e118-e123. [PMID: 39104747 PMCID: PMC11300101 DOI: 10.1055/a-2358-8928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 05/16/2024] [Indexed: 08/07/2024] Open
Abstract
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 computed tomography (CT) scans using minimal training data, and the resulting data were reconstructed into three-dimensional (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. Conclusion By offering an automatic means of preparing VR models from a patient's raw CT scans, this pipeline takes a key step toward 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.
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Affiliation(s)
- Varun Gudapati
- David Geffen School of Medicine, UCLA, Los Angeles, California, United States
| | - Alexander Chen
- David Geffen School of Medicine, UCLA, Los Angeles, California, United States
| | - Scott Meyer
- David Geffen School of Medicine, UCLA, Los Angeles, California, United States
| | - Chung-Chieh Jay Kuo
- Ming-Hsieh Department of Electrical Engineering, USC, Los Angeles, California, United States
| | - Yichen Ding
- David Geffen School of Medicine, UCLA, Los Angeles, California, United States
| | - Tzung K. Hsiai
- David Geffen School of Medicine, UCLA, Los Angeles, California, United States
| | - Marilene Wang
- David Geffen School of Medicine, UCLA, Los Angeles, California, United States
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Zhang X, Saberigarakani A, Almasian M, Hassan S, Nekkanti M, Ding Y. 4D Light-sheet Imaging of Zebrafish Cardiac Contraction. J Vis Exp 2024:10.3791/66263. [PMID: 38251787 PMCID: PMC10939705 DOI: 10.3791/66263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2024] Open
Abstract
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.
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Affiliation(s)
- Xinyuan Zhang
- Department of Bioengineering, The University of Texas at Dallas
| | | | - Milad Almasian
- Department of Bioengineering, The University of Texas at Dallas
| | - Sohail Hassan
- Department of Bioengineering, The University of Texas at Dallas
| | - Manasa Nekkanti
- Department of Bioengineering, The University of Texas at Dallas
| | - Yichen Ding
- Department of Bioengineering, The University of Texas at Dallas; Center for Imaging and Surgical Innovation, The University of Texas at Dallas; Hamon Center for Regenerative Science and Medicine, UT Southwestern Medical Center;
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Zhang X, Almasian M, Hassan SS, Jotheesh R, Kadam VA, Polk AR, Saberigarakani A, Rahat A, Yuan J, Lee J, Carroll K, Ding Y. 4D Light-sheet imaging and interactive analysis of cardiac contractility in zebrafish larvae. APL Bioeng 2023; 7:026112. [PMID: 37351330 PMCID: PMC10283270 DOI: 10.1063/5.0153214] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 06/05/2023] [Indexed: 06/24/2023] Open
Abstract
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 in vivo 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.
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Affiliation(s)
- Xinyuan Zhang
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, Texas 75080, USA
| | - Milad Almasian
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, Texas 75080, USA
| | - Sohail S. Hassan
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, Texas 75080, USA
| | - Rosemary Jotheesh
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, Texas 75080, USA
| | - Vinay A. Kadam
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, Texas 75080, USA
| | - Austin R. Polk
- Department of Computer Science, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, Texas 75080, USA
| | - Alireza Saberigarakani
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, Texas 75080, USA
| | - Aayan Rahat
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, Texas 75080, USA
| | - Jie Yuan
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, Texas 75080, USA
| | - Juhyun Lee
- Department of Bioengineering, The University of Texas at Arlington, Arlington, Texas 76019, USA
| | - Kelli Carroll
- Department of Biology, Austin College, Sherman, Texas 75090, USA
| | - Yichen Ding
- Author to whom correspondence should be addressed:. Tel.: 972–883-7217
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7
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Sodimu O, Almasian M, Gan P, Hassan S, Zhang X, Liu N, Ding Y. Light sheet imaging and interactive analysis of the cardiac structure in neonatal mice. JOURNAL OF BIOPHOTONICS 2023; 16:e202200278. [PMID: 36624523 PMCID: PMC10192002 DOI: 10.1002/jbio.202200278] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 11/25/2022] [Accepted: 12/24/2022] [Indexed: 05/17/2023]
Abstract
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.
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Affiliation(s)
- Oluwatofunmi Sodimu
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Milad Almasian
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Peiheng Gan
- Hamon Center for Regenerative Science and Medicine, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Sohail Hassan
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Xinyuan Zhang
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Ning Liu
- Hamon Center for Regenerative Science and Medicine, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Yichen Ding
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX 75080, USA
- Hamon Center for Regenerative Science and Medicine, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Center for Imaging and Surgical Innovation, The University of Texas at Dallas, Richardson, TX, 75080, USA
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Yuan J, Hassan SS, Wu J, Koger CR, Packard RRS, Shi F, Fei B, Ding Y. Extended reality for biomedicine. NATURE REVIEWS. METHODS PRIMERS 2023; 3:15. [PMID: 37051227 PMCID: PMC10088349 DOI: 10.1038/s43586-023-00208-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
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.
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Affiliation(s)
- Jie Yuan
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX, United States
| | - Sohail S. Hassan
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX, United States
| | - Jiaojiao Wu
- Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
| | - Casey R. Koger
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX, United States
| | - René R. Sevag Packard
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
- Ronald Reagan UCLA Medical Center, Los Angeles, CA United States
- Veterans Affairs West Los Angeles Medical Center, Los Angeles, CA, United States
| | - Feng Shi
- Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
| | - Baowei Fei
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX, United States
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States
- Center for Imaging and Surgical Innovation, The University of Texas at Dallas, Richardson, TX, United States
| | - Yichen Ding
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX, United States
- Center for Imaging and Surgical Innovation, The University of Texas at Dallas, Richardson, TX, United States
- Hamon Center for Regenerative Science and Medicine, UT Southwestern Medical Center, Dallas, TX, United States
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Abstract
PURPOSE OF REVIEW 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. RECENT FINDINGS Current advancement of cardiac functional assessments is in pace with the development of imaging techniques. The methods tailored to advanced imaging have been widely used in cardiac magnetic resonance, echocardiography, and optical microscopy. In this review, we introduce fundamental concepts and applications of representative methods for each imaging modality used in both fundamental research and clinical investigations. All these methods have been designed or developed to quantify time-dependent 2-dimensional (2D) or 3D cardiac mechanics, holding great potential to unravel global or regional myocardial deformation and contractile function from end-systole to end-diastole. Computational methods to assess cardiac contractile function provide a quantitative insight into the analysis of myocardial mechanics during cardiac development, injury, and remodeling.
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Koger CR, Hassan SS, Yuan J, Ding Y. Virtual Reality for Interactive Medical Analysis. FRONTIERS IN VIRTUAL REALITY 2022; 3:782854. [PMID: 36711187 PMCID: PMC9881036 DOI: 10.3389/frvir.2022.782854] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
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.
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Affiliation(s)
- Casey R. Koger
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Sohail S. Hassan
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Jie Yuan
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Yichen Ding
- Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX 75080, USA
- Hamon Center for Regenerative Science and Medicine, UT Southwestern Medical Center, Dallas, TX 75390, USA
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11
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Javaid M, Khan IH. Virtual Reality (VR) Applications in Cardiology: A Review. JOURNAL OF INDUSTRIAL INTEGRATION AND MANAGEMENT 2021. [DOI: 10.1142/s2424862221300015] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Virtual reality (VR) has applications in cardiology to create enhancement, thereby improving the quality of associated planning, treatment and surgery. The need is to study different applications of this technology in the field of cardiology. We have studied research papers on VR and its applications in cardiology through a detailed bibliometric analysis. The study identified five significant steps for proper implementation of this technology in cardiology. Some challenges are to be undertaken by using this technology, and they can provide some benefits; thus, authors contemplate extensive research and development. This study also identifies 10 major VR technology applications in cardiology and provided a brief description. This innovative technology helps a heart surgeon to perform complex heart surgery effectively. Thus, VR applications have the potential for improving decision-making, which helps save human life. VR plays a significant role in the development of a surgical procedure. This technology undertakes 3D heart model information in full colour, which helps to analyze the overall heart vane, blockage and blood flow. With the help of this digital technology, a surgeon can improve the accuracy of heart surgery, and he can simulate the surgery. A surgeon can undertake surgery in a virtual environment on a virtual patient. The unique purpose of this technology is to practice pre-operatively on the specific circumstance. A cardiologist can also check the proper status of inner and outer heart wall layer. Thus, by using this 3D information, the surgeon can now interact with heart data/information without any physical touch. This technology opens a new opportunity to improve the heart surgery and development in cardiovascular treatment to improve patient outcome.
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Affiliation(s)
- Mohd Javaid
- Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi, India
| | - Ibrahim Haleem Khan
- School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi, India
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12
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Chang CC, Chu A, Meyer S, Ding Y, Sun MM, Abiri P, Baek KI, Gudapati V, Ding X, Guihard P, Bostrom KI, Li S, Gordon LK, Zheng JJ, Hsiai TK. Three-dimensional Imaging Coupled with Topological Quantification Uncovers Retinal Vascular Plexuses Undergoing Obliteration. Theranostics 2021; 11:1162-1175. [PMID: 33391527 PMCID: PMC7738897 DOI: 10.7150/thno.53073] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 10/19/2020] [Indexed: 02/06/2023] Open
Abstract
Introduction: Murine models provide microvascular insights into the 3-D network disarray seen in retinopathy and cardiovascular diseases. Light-sheet fluorescence microscopy (LSFM) has emerged to capture retinal vasculature in 3-D, allowing for assessment of the progression of retinopathy and the potential to screen new therapeutic targets in mice. We hereby coupled LSFM, also known as selective plane illumination microscopy, with topological quantification, to characterize the retinal vascular plexuses undergoing preferential obliteration. Method and Result: In postnatal mice, we revealed the 3-D retinal microvascular network in which the vertical sprouts bridge the primary (inner) and secondary (outer) plexuses, whereas, in an oxygen-induced retinopathy (OIR) mouse model, we demonstrated preferential obliteration of the secondary plexus and bridging vessels with a relatively unscathed primary plexus. Using clustering coefficients and Euler numbers, we computed the local versus global vascular connectivity. While local connectivity was preserved (p > 0.05, n = 5 vs. normoxia), the global vascular connectivity in hyperoxia-exposed retinas was significantly reduced (p < 0.05, n = 5 vs. normoxia). Applying principal component analysis (PCA) for auto-segmentation of the vertical sprouts, we corroborated the obliteration of the vertical sprouts bridging the secondary plexuses, as evidenced by impaired vascular branching and connectivity, and reduction in vessel volumes and lengths (p < 0.05, n = 5 vs. normoxia). Conclusion: Coupling 3-D LSFM with topological quantification uncovered the retinal vasculature undergoing hyperoxia-induced obliteration from the secondary (outer) plexus to the vertical sprouts. The use of clustering coefficients, Euler's number, and PCA provided new network insights into OIR-associated vascular obliteration, with translational significance for investigating therapeutic interventions to prevent visual impairment.
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Affiliation(s)
- Chih-Chiang Chang
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA
| | - Alison Chu
- Division of Neonatology and Developmental Biology, Department of Pediatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Scott Meyer
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Yichen Ding
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Michel M. Sun
- Department of Ophthalmology, Stein Eye Institute, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Parinaz Abiri
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Kyung In Baek
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Varun Gudapati
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Xili Ding
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA
| | - Pierre Guihard
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Kristina I. Bostrom
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA
- Greater Los Angeles VA Healthcare System, Los Angeles, CA
| | - Song Li
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA
| | - Lynn K. Gordon
- Department of Ophthalmology, Stein Eye Institute, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Jie J. Zheng
- Department of Ophthalmology, Stein Eye Institute, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Tzung K. Hsiai
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA
- Greater Los Angeles VA Healthcare System, Los Angeles, CA
- Medical Engineering, California Institute of Technology, Pasadena, CA
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13
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Ding Y, Gudapati V, Lin R, Fei Y, Sevag Packard RR, Song S, Chang CC, Baek KI, Wang Z, Roustaei M, Kuang D, Jay Kuo CC, Hsiai TK. Saak Transform-Based Machine Learning for Light-Sheet Imaging of Cardiac Trabeculation. IEEE Trans Biomed Eng 2021; 68:225-235. [PMID: 32365015 PMCID: PMC7606319 DOI: 10.1109/tbme.2020.2991754] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
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.
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Affiliation(s)
- Yichen Ding
- Henry Samueli School of Engineering and David Geffen School of Medicine, University of California, Los Angeles, CA 90095 USA
| | - Varun Gudapati
- Henry Samueli School of Engineering and David Geffen School of Medicine, University of California, Los Angeles, CA 90095 USA
| | - Ruiyuan Lin
- Ming-Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90089 USA
| | - Yanan Fei
- Ming-Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90089 USA
| | - René R Sevag Packard
- Henry Samueli School of Engineering and David Geffen School of Medicine, University of California, Los Angeles, CA 90095 USA
| | - Sibo Song
- Ming-Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90089 USA
| | - Chih-Chiang Chang
- Henry Samueli School of Engineering and David Geffen School of Medicine, University of California, Los Angeles, CA 90095 USA
| | - Kyung In Baek
- Henry Samueli School of Engineering and David Geffen School of Medicine, University of California, Los Angeles, CA 90095 USA
| | - Zhaoqiang Wang
- Henry Samueli School of Engineering and David Geffen School of Medicine, University of California, Los Angeles, CA 90095 USA
| | - Mehrdad Roustaei
- Henry Samueli School of Engineering and David Geffen School of Medicine, University of California, Los Angeles, CA 90095 USA
| | - Dengfeng Kuang
- Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology, and Institute of Modern Optics, Nankai University, Tianjin 300350, China
| | - C.-C. Jay Kuo
- Ming-Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90089 USA
| | - Tzung K. Hsiai
- Henry Samueli School of Engineering and David Geffen School of Medicine, University of California, Los Angeles, CA 90095 USA
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14
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Chen B, Zhang JP. Three-dimensional integrated quantitative modeling and fluorescent imaging of doxorubicin-induced cardiotoxicity in a whole organ using a deconvolution microscope. J Pharmacol Toxicol Methods 2020; 101:106662. [DOI: 10.1016/j.vascn.2019.106662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Revised: 11/12/2019] [Accepted: 11/16/2019] [Indexed: 11/30/2022]
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15
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Li R, Baek KI, Chang CC, Zhou B, Hsiai TK. Mechanosensitive Pathways Involved in Cardiovascular Development and Homeostasis in Zebrafish. J Vasc Res 2019; 56:273-283. [PMID: 31466069 DOI: 10.1159/000501883] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2018] [Accepted: 07/03/2019] [Indexed: 11/19/2022] Open
Abstract
Cardiovascular diseases such as coronary heart disease, myocardial infarction, and cardiac arrhythmia are the leading causes of morbidity and mortality in developed countries and are steadily increasing in developing countries. Fundamental mechanistic studies at the molecular, cellular, and animal model levels are critical for the diagnosis and treatment of these diseases. Despite being phylogenetically distant from humans, zebrafish share remarkable similarity in the genetics and electrophysiology of the cardiovascular system. In the last 2 decades, the development and deployment of innovative genetic manipulation techniques greatly facilitated the application of zebrafish as an animal model for studying basic biology and diseases. Hemodynamic shear stress is intimately involved in vascular development and homeostasis. The critical mechanosensitive signaling pathways in cardiovascular development and pathophysiology previously studied in mammals have been recapitulated in zebrafish. In this short article, we reviewed recent knowledge about the role of mechanosensitive pathways such as Notch, PKCε/PFKFB3, and Wnt/Ang2 in cardiovas-cular development and homeostasis from studies in the -zebrafish model.
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Affiliation(s)
- Rongsong Li
- College of Health Sciences and Environmental Engineering, Shenzhen Technology University, Shenzhen, China,
| | - Kyung In Baek
- Department of Bioengineering,University of California, Los Angeles, California, USA
| | - Chih-Chiang Chang
- Department of Bioengineering,University of California, Los Angeles, California, USA
| | - Bill Zhou
- Department of Radiology, University of California, Los Angeles, California, USA
| | - Tzung K Hsiai
- Department of Bioengineering,University of California, Los Angeles, California, USA.,Department of Medicine (Cardiology) and Bioengineering, University of California, Los Angeles, California, USA
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16
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Chen J, Ding Y, Chen M, Gau J, Jen N, Nahal C, Tu S, Chen C, Zhou S, Chang CC, Lyu J, Xu X, Hsiai TK, Packard RRS. Displacement analysis of myocardial mechanical deformation (DIAMOND) reveals segmental susceptibility to doxorubicin-induced injury and regeneration. JCI Insight 2019; 4:125362. [PMID: 30996130 PMCID: PMC6538350 DOI: 10.1172/jci.insight.125362] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Accepted: 02/27/2019] [Indexed: 12/27/2022] Open
Abstract
Zebrafish are increasingly utilized to model cardiomyopathies and regeneration. Current methods evaluating cardiac function have known limitations, fail to reliably detect focal mechanics, and are not readily feasible in zebrafish. We developed a semiautomated, open-source method - displacement analysis of myocardial mechanical deformation (DIAMOND) - for quantitative assessment of 4D segmental cardiac function. We imaged transgenic embryonic zebrafish in vivo using a light-sheet fluorescence microscopy system with 4D cardiac motion synchronization. Our method permits the derivation of a transformation matrix to quantify the time-dependent 3D displacement of segmental myocardial mass centroids. Through treatment with doxorubicin, and by chemically and genetically manipulating the myocardial injury-activated Notch signaling pathway, we used DIAMOND to demonstrate that basal ventricular segments adjacent to the atrioventricular canal display the highest 3D displacement and are also the most susceptible to doxorubicin-induced injury. Thus, DIAMOND provides biomechanical insights into in vivo segmental cardiac function scalable to high-throughput research applications.
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Affiliation(s)
- Junjie Chen
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Sciences
| | - Yichen Ding
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine
| | - Michael Chen
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Sciences
| | - Jonathan Gau
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine
| | - Nelson Jen
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine
| | - Chadi Nahal
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Sciences
| | - Sally Tu
- Department of Neuroscience, College of Letters and Science, University of California, Los Angeles, California, USA
| | - Cynthia Chen
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Sciences
| | - Steve Zhou
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine
| | - Chih-Chiang Chang
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Sciences
| | - Jintian Lyu
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Sciences
| | - Xiaolei Xu
- Department of Biochemistry and Molecular Biology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Tzung K. Hsiai
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Sciences
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine
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17
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Hsu JJ, Vedula V, Baek KI, Chen C, Chen J, Chou MI, Lam J, Subhedar S, Wang J, Ding Y, Chang CC, Lee J, Demer LL, Tintut Y, Marsden AL, Hsiai TK. Contractile and hemodynamic forces coordinate Notch1b-mediated outflow tract valve formation. JCI Insight 2019; 5:124460. [PMID: 30973827 DOI: 10.1172/jci.insight.124460] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Biomechanical forces and endothelial-to-mesenchymal transition (EndoMT) are known to mediate valvulogenesis. However, the relative contributions of myocardial contractile and hemodynamic shear forces remain poorly understood. We integrated 4-D light-sheet imaging of transgenic zebrafish models with moving-domain computational fluid dynamics to determine effects of changes in contractile forces and fluid wall shear stress (WSS) on ventriculobulbar (VB) valve development. Augmentation of myocardial contractility with isoproterenol increased both WSS and Notch1b activity in the developing outflow tract (OFT) and resulted in VB valve hyperplasia. Increasing WSS in the OFT, achieved by increasing blood viscosity through EPO mRNA injection, also resulted in VB valve hyperplasia. Conversely, decreasing myocardial contractility by Tnnt2a morpholino oligonucleotide (MO) administration, 2,3-butanedione monoxime treatment, or Plcγ1 inhibition completely blocked VB valve formation, which could not be rescued by increasing WSS or activating Notch. Decreasing WSS in the OFT, achieved by slowing heart rate with metoprolol or reducing viscosity with Gata1a MO, did not affect VB valve formation. Immunofluorescent staining with the mesenchymal marker, DM-GRASP, revealed that biomechanical force-mediated Notch1b activity is implicated in EndoMT to modulate valve morphology. Altogether, increases in WSS result in Notch1b- EndoMT-mediated VB valve hyperplasia, whereas decreases in contractility result in reduced Notch1b activity, absence of EndoMT, and VB valve underdevelopment. Thus, we provide developmental mechanotransduction mechanisms underlying Notch1b-mediated EndoMT in the OFT.
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Affiliation(s)
- Jeffrey J Hsu
- Division of Cardiology, Department of Medicine, UCLA, Los Angeles, California, USA
| | - Vijay Vedula
- Departments of Pediatrics and Bioengineering, Stanford University, Stanford, California, USA
| | - Kyung In Baek
- Department of Bioengineering, UCLA, Los Angeles, California, USA
| | - Cynthia Chen
- Department of Bioengineering, UCLA, Los Angeles, California, USA
| | - Junjie Chen
- Department of Bioengineering, UCLA, Los Angeles, California, USA
| | - Man In Chou
- Department of Bioengineering, UCLA, Los Angeles, California, USA
| | - Jeffrey Lam
- Department of Bioengineering, UCLA, Los Angeles, California, USA
| | - Shivani Subhedar
- Department of Bioengineering, UCLA, Los Angeles, California, USA
| | - Jennifer Wang
- Department of Bioengineering, UCLA, Los Angeles, California, USA
| | - Yichen Ding
- Department of Bioengineering, UCLA, Los Angeles, California, USA
| | | | - Juhyun Lee
- Department of Bioengineering, University of Texas - Arlington, Arlington, Texas, USA
| | - Linda L Demer
- Division of Cardiology, Department of Medicine, UCLA, Los Angeles, California, USA.,Department of Bioengineering, UCLA, Los Angeles, California, USA.,Department of Physiology, UCLA, Los Angeles, California, USA
| | - Yin Tintut
- Division of Cardiology, Department of Medicine, UCLA, Los Angeles, California, USA.,Department of Physiology, UCLA, Los Angeles, California, USA
| | - Alison L Marsden
- Departments of Pediatrics and Bioengineering, Stanford University, Stanford, California, USA
| | - Tzung K Hsiai
- Division of Cardiology, Department of Medicine, UCLA, Los Angeles, California, USA.,Department of Bioengineering, UCLA, Los Angeles, California, USA
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18
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Baek KI, Ding Y, Chang CC, Chang M, Sevag Packard RR, Hsu JJ, Fei P, Hsiai TK. Advanced microscopy to elucidate cardiovascular injury and regeneration: 4D light-sheet imaging. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2018; 138:105-115. [PMID: 29752956 PMCID: PMC6226366 DOI: 10.1016/j.pbiomolbio.2018.05.003] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 04/30/2018] [Accepted: 05/04/2018] [Indexed: 12/20/2022]
Abstract
The advent of 4-dimensional (4D) light-sheet fluorescence microscopy (LSFM) has provided an entry point for rapid image acquisition to uncover real-time cardiovascular structure and function with high axial resolution and minimal photo-bleaching/-toxicity. We hereby review the fundamental principles of our LSFM system to investigate cardiovascular morphogenesis and regeneration after injury. LSFM enables us to reveal the micro-circulation of blood cells in the zebrafish embryo and assess cardiac ventricular remodeling in response to chemotherapy-induced injury using an automated segmentation approach. Next, we review two distinct mechanisms underlying zebrafish vascular regeneration following tail amputation. We elucidate the role of endothelial Notch signaling to restore vascular regeneration after exposure to the redox active ultrafine particles (UFP) in air pollutants. By manipulating the blood viscosity and subsequently, endothelial wall shear stress, we demonstrate the mechanism whereby hemodynamic shear forces impart both mechanical and metabolic effects to modulate vascular regeneration. Overall, the implementation of 4D LSFM allows for the elucidation of mechanisms governing cardiovascular injury and regeneration with high spatiotemporal resolution.
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Affiliation(s)
- Kyung In Baek
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA.
| | - Yichen Ding
- Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, CA 90095, USA.
| | - Chih-Chiang Chang
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA.
| | - Megan Chang
- Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, CA 90095, USA.
| | - René R Sevag Packard
- Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, CA 90095, USA.
| | - Jeffrey J Hsu
- Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, CA 90095, USA.
| | - Peng Fei
- School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
| | - Tzung K Hsiai
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, CA 90095, USA; Medical Engineering, California Institute of Technology, Pasadena, CA 91106, USA.
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19
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Dvornikov AV, de Tombe PP, Xu X. Phenotyping cardiomyopathy in adult zebrafish. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2018; 138:116-125. [PMID: 29884423 PMCID: PMC6269218 DOI: 10.1016/j.pbiomolbio.2018.05.013] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2018] [Revised: 04/26/2018] [Accepted: 05/29/2018] [Indexed: 12/21/2022]
Abstract
Hypertrophic cardiomyopathy (HCM) is usually manifested by increased myofilament Ca2+ sensitivity, excessive contractility, and impaired relaxation. In contrast, dilated cardiomyopathy (DCM) originates from insufficient sarcomere contractility and reduced cardiac pump function, subsequently resulting in heart failure. The zebrafish has emerged as a new model of human cardiomyopathy with high-throughput screening, which will facilitate the discovery of novel genetic factors and the development of new therapies. Given the small hearts of zebrafish, better phenotyping tools are needed to discern different types of cardiomyopathy, such as HCM and DCM. This article reviews the existing models of cardiomyopathy, available morphologic and functional methods, and current understanding of the different types of cardiomyopathy in adult zebrafish.
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Affiliation(s)
- Alexey V Dvornikov
- Department of Biochemistry and Molecular Biology, Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
| | - Pieter P de Tombe
- University of Illinois at Chicago, Department of Physiology and Biophysics, Chicago, IL, USA; Magdi Yacoub Institute, Cardiac Biophysics Division, Harefield, UK; Imperial College, Heart and Lung Institute, London, UK; Freiburg University, Institute for Experimental Cardiovascular Medicine, Germany
| | - Xiaolei Xu
- Department of Biochemistry and Molecular Biology, Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
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20
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Ding Y, Bailey Z, Messerschmidt V, Nie J, Bryant R, Rugonyi S, Fei P, Lee J, Hsiai TK. Light-sheet Fluorescence Microscopy for the Study of the Murine Heart. J Vis Exp 2018. [PMID: 30272656 DOI: 10.3791/57769] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Light-sheet fluorescence microscopy has been widely used for rapid image acquisition with a high axial resolution from micrometer to millimeter scale. Traditional light-sheet techniques involve the use of a single illumination beam directed orthogonally at sample tissue. Images of large samples that are produced using a single illumination beam contain stripes or artifacts and suffer from a reduced resolution due to the scattering and absorption of light by the tissue. This study uses a dual-sided illumination beam and a simplified CLARITY optical clearing technique for the murine heart. These techniques allow for deeper imaging by removing lipids from the heart and produce a large field of imaging, greater than 10 x 10 x 10 mm3. As a result, this strategy enables us to quantify the ventricular dimensions, track the cardiac lineage, and localize the spatial distribution of cardiac-specific proteins and ion-channels from the post-natal to adult mouse hearts with sufficient contrast and resolution.
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Affiliation(s)
- Yichen Ding
- Department of Bioengineering, University of California Los Angeles
| | - Zachary Bailey
- Department of Bioengineering, University of Texas at Arlington
| | | | - Jun Nie
- School of Optical and Electronic Information, Huazhong University of Science and Technology
| | - Richard Bryant
- Department of Bioengineering, University of Texas at Arlington
| | | | - Peng Fei
- School of Optical and Electronic Information, Huazhong University of Science and Technology
| | - Juhyun Lee
- Department of Bioengineering, University of California Los Angeles; Department of Bioengineering, University of Texas at Arlington;
| | - Tzung K Hsiai
- Department of Bioengineering, University of California Los Angeles;
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21
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Ding Y, Ma J, Langenbacher AD, Baek KI, Lee J, Chang CC, Hsu JJ, Kulkarni RP, Belperio J, Shi W, Ranjbarvaziri S, Ardehali R, Tintut Y, Demer LL, Chen JN, Fei P, Packard RRS, Hsiai TK. Multiscale light-sheet for rapid imaging of cardiopulmonary system. JCI Insight 2018; 3:121396. [PMID: 30135307 PMCID: PMC6141183 DOI: 10.1172/jci.insight.121396] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The ability to image tissue morphogenesis in real-time and in 3-dimensions (3-D) remains an optical challenge. The advent of light-sheet fluorescence microscopy (LSFM) has advanced developmental biology and tissue regeneration research. In this review, we introduce a LSFM system in which the illumination lens reshapes a thin light-sheet to rapidly scan across a sample of interest while the detection lens orthogonally collects the imaging data. This multiscale strategy provides deep-tissue penetration, high-spatiotemporal resolution, and minimal photobleaching and phototoxicity, allowing in vivo visualization of a variety of tissues and processes, ranging from developing hearts in live zebrafish embryos to ex vivo interrogation of the microarchitecture of optically cleared neonatal hearts. Here, we highlight multiple applications of LSFM and discuss several studies that have allowed better characterization of developmental and pathological processes in multiple models and tissues. These findings demonstrate the capacity of multiscale light-sheet imaging to uncover cardiovascular developmental and regenerative phenomena.
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Affiliation(s)
- Yichen Ding
- Department of Medicine, David Geffen School of Medicine at UCLA, and
- Department of Bioengineering, UCLA, Los Angeles, California, USA
| | - Jianguo Ma
- Department of Medicine, David Geffen School of Medicine at UCLA, and
- School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing, China
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beijing, China
| | - Adam D. Langenbacher
- Department of Molecular, Cell and Developmental Biology, UCLA, Los Angeles, California, USA
| | - Kyung In Baek
- Department of Bioengineering, UCLA, Los Angeles, California, USA
| | - Juhyun Lee
- Department of Bioengineering, UCLA, Los Angeles, California, USA
| | | | - Jeffrey J. Hsu
- Department of Medicine, David Geffen School of Medicine at UCLA, and
| | - Rajan P. Kulkarni
- Department of Medicine, David Geffen School of Medicine at UCLA, and
| | - John Belperio
- Department of Medicine, David Geffen School of Medicine at UCLA, and
| | - Wei Shi
- Developmental Biology and Regenerative Medicine Program, Department of Surgery, Children’s Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | | | - Reza Ardehali
- Department of Medicine, David Geffen School of Medicine at UCLA, and
| | - Yin Tintut
- Department of Medicine, David Geffen School of Medicine at UCLA, and
| | - Linda L. Demer
- Department of Medicine, David Geffen School of Medicine at UCLA, and
| | - Jau-Nian Chen
- Department of Molecular, Cell and Developmental Biology, UCLA, Los Angeles, California, USA
| | - Peng Fei
- Department of Medicine, David Geffen School of Medicine at UCLA, and
- School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, China
| | | | - Tzung K. Hsiai
- Department of Medicine, David Geffen School of Medicine at UCLA, and
- Department of Bioengineering, UCLA, Los Angeles, California, USA
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22
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Abiri A, Ding Y, Abiri P, Packard RRS, Vedula V, Marsden A, Kuo CCJ, Hsiai TK. Simulating Developmental Cardiac Morphology in Virtual Reality Using a Deformable Image Registration Approach. Ann Biomed Eng 2018; 46:2177-2188. [PMID: 30112710 DOI: 10.1007/s10439-018-02113-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Accepted: 08/07/2018] [Indexed: 10/28/2022]
Abstract
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.
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Affiliation(s)
- Arash Abiri
- Department of Bioengineering, University of California, Los Angeles, CA, 90095, USA.,Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA.,Department of Biomedical Engineering, University of California, Irvine, CA, 92697, USA
| | - Yichen Ding
- Department of Bioengineering, University of California, Los Angeles, CA, 90095, USA.,Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Parinaz Abiri
- Department of Bioengineering, University of California, Los Angeles, CA, 90095, USA.,Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - René R Sevag Packard
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Vijay Vedula
- Department of Pediatrics (Cardiology), Stanford University, Stanford, CA, 94305, USA
| | - Alison Marsden
- Department of Pediatrics (Cardiology), Stanford University, Stanford, CA, 94305, USA.,Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA.,Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, 94305, USA
| | - C-C Jay Kuo
- Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Tzung K Hsiai
- Department of Bioengineering, University of California, Los Angeles, CA, 90095, USA. .,Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA. .,Medical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA.
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23
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Ding Y, Lee J, Hsu JJ, Chang CC, Baek KI, Ranjbarvaziri S, Ardehali R, Packard RRS, Hsiai TK. Light-Sheet Imaging to Elucidate Cardiovascular Injury and Repair. Curr Cardiol Rep 2018; 20:35. [PMID: 29574550 DOI: 10.1007/s11886-018-0979-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
PURPOSE OF REVIEW Real-time 3-dimensional (3-D) imaging of cardiovascular injury and regeneration remains challenging. We introduced a multi-scale imaging strategy that uses light-sheet illumination to enable applications of cardiovascular injury and repair in models ranging from zebrafish to rodent hearts. RECENT FINDINGS Light-sheet imaging enables rapid data acquisition with high spatiotemporal resolution and with minimal photo-bleaching or photo-toxicity. We demonstrated the capacity of this novel light-sheet approach for scanning a region of interest with specific fluorescence contrast, thereby providing axial and temporal resolution at the cellular level without stitching image columns or pivoting illumination beams during one-time imaging. This cutting-edge imaging technique allows for elucidating the differentiation of stem cells in cardiac regeneration, providing an entry point to discover novel micro-circulation phenomenon with clinical significance for injury and repair. These findings demonstrate the multi-scale applications of this novel light-sheet imaging strategy to advance research in cardiovascular development and regeneration.
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Affiliation(s)
- Yichen Ding
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA.,Department of Bioengineering, University of California, Los Angeles, CA, 90095, USA
| | - Juhyun Lee
- Department of Bioengineering, University of California, Los Angeles, CA, 90095, USA.,Department of Bioengineering, University of Texas at Arlington, Arlington, TX, 76010, USA
| | - Jeffrey J Hsu
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Chih-Chiang Chang
- Department of Bioengineering, University of California, Los Angeles, CA, 90095, USA
| | - Kyung In Baek
- Department of Bioengineering, University of California, Los Angeles, CA, 90095, USA
| | - Sara Ranjbarvaziri
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Reza Ardehali
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - René R Sevag Packard
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Tzung K Hsiai
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA. .,Department of Bioengineering, University of California, Los Angeles, CA, 90095, USA. .,Medical Engineering, California Institute of Technology, Pasadena, CA, 91106, USA.
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24
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The molecular basis of immune regulation in autoimmunity. Clin Sci (Lond) 2018; 132:43-67. [PMID: 29305419 DOI: 10.1042/cs20171154] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2017] [Revised: 11/21/2017] [Accepted: 11/27/2017] [Indexed: 12/11/2022]
Abstract
Autoimmune diseases can be triggered and modulated by various molecular and cellular characteristics. The mechanisms of autoimmunity and the pathogenesis of autoimmune diseases have been investigated for several decades. It is well accepted that autoimmunity is caused by dysregulated/dysfunctional immune susceptible genes and environmental factors. There are multiple physiological mechanisms that regulate and control self-reactivity, but which can also lead to tolerance breakdown when in defect. The majority of autoreactive T or B cells are eliminated during the development of central tolerance by negative selection. Regulatory cells such as Tregs (regulatory T) and MSCs (mesenchymal stem cells), and molecules such as CTLA-4 (cytotoxic T-lymphocyte associated antigen 4) and IL (interleukin) 10 (IL-10), help to eliminate autoreactive cells that escaped to the periphery in order to prevent development of autoimmunity. Knowledge of the molecular basis of immune regulation is needed to further our understanding of the underlying mechanisms of loss of tolerance in autoimmune diseases and pave the way for the development of more effective, specific, and safer therapeutic interventions.
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