4D Light-sheet imaging and interactive analysis of cardiac contractility in zebrafish larvae

Author:

Zhang Xinyuan1ORCID,Almasian Milad1ORCID,Hassan Sohail S.1ORCID,Jotheesh Rosemary1ORCID,Kadam Vinay A.1ORCID,Polk Austin R.2ORCID,Saberigarakani Alireza1ORCID,Rahat Aayan1ORCID,Yuan Jie1ORCID,Lee Juhyun3ORCID,Carroll Kelli4ORCID,Ding Yichen156ORCID

Affiliation:

1. Department of Bioengineering, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas 1 , Richardson, Texas 75080, USA

2. Department of Computer Science, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas 2 , Richardson, Texas 75080, USA

3. Department of Bioengineering, The University of Texas at Arlington 3 , Arlington, Texas 76019, USA

4. Department of Biology, Austin College 4 , Sherman, Texas 75090, USA

5. Center for Imaging and Surgical Innovation, The University of Texas at Dallas 5 , Richardson, Texas 75080, USA

6. Hamon Center for Regenerative Science and Medicine, UT Southwestern Medical Center 6 , Dallas, Texas 75390, USA

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.

Funder

National Heart, Lung, and Blood Institute

Publisher

AIP Publishing

Subject

Biomedical Engineering,Biomaterials,Biophysics,Bioengineering

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3