Alireza Saberigarakani, Riya P Patel, Milad Almasian, Xinyuan Zhang, Jonathan Brewer, Sohail S Hassan, Jichen Chai, Juhyun Lee, Baowei Fei, Jie Yuan, Kelli Carroll, Yichen Ding
{"title":"斑马鱼心脏收缩功能的体积成像与计算研究。","authors":"Alireza Saberigarakani, Riya P Patel, Milad Almasian, Xinyuan Zhang, Jonathan Brewer, Sohail S Hassan, Jichen Chai, Juhyun Lee, Baowei Fei, Jie Yuan, Kelli Carroll, Yichen Ding","doi":"10.1016/j.crmeth.2025.101113","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101113"},"PeriodicalIF":4.5000,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12461643/pdf/","citationCount":"0","resultStr":"{\"title\":\"Volumetric imaging and computation to explore contractile function in zebrafish hearts.\",\"authors\":\"Alireza Saberigarakani, Riya P Patel, Milad Almasian, Xinyuan Zhang, Jonathan Brewer, Sohail S Hassan, Jichen Chai, Juhyun Lee, Baowei Fei, Jie Yuan, Kelli Carroll, Yichen Ding\",\"doi\":\"10.1016/j.crmeth.2025.101113\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":29773,\"journal\":{\"name\":\"Cell Reports Methods\",\"volume\":\" \",\"pages\":\"101113\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2025-08-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12461643/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cell Reports Methods\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.crmeth.2025.101113\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/7/23 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell Reports Methods","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.crmeth.2025.101113","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/23 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
Volumetric imaging and computation to explore contractile function in zebrafish hearts.
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.