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Zenger B, Bergquist JA, Busatto A, Good WW, Rupp LC, Sharma V, MacLeod RS. Tipping the scales of understanding: An engineering approach to design and implement whole-body cardiac electrophysiology experimental models. Front Physiol 2023; 14:1100471. [PMID: 36744034 PMCID: PMC9893785 DOI: 10.3389/fphys.2023.1100471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 01/02/2023] [Indexed: 01/21/2023] Open
Abstract
The study of cardiac electrophysiology is built on experimental models that span all scales, from ion channels to whole-body preparations. Novel discoveries made at each scale have contributed to our fundamental understanding of human cardiac electrophysiology, which informs clinicians as they detect, diagnose, and treat complex cardiac pathologies. This expert review describes an engineering approach to developing experimental models that is applicable across scales. The review also outlines how we applied the approach to create a set of multiscale whole-body experimental models of cardiac electrophysiology, models that are driving new insights into the response of the myocardium to acute ischemia. Specifically, we propose that researchers must address three critical requirements to develop an effective experimental model: 1) how the experimental model replicates and maintains human physiological conditions, 2) how the interventions possible with the experimental model capture human pathophysiology, and 3) what signals need to be measured, at which levels of resolution and fidelity, and what are the resulting requirements of the measurement system and the access to the organs of interest. We will discuss these requirements in the context of two examples of whole-body experimental models, a closed chest in situ model of cardiac ischemia and an isolated-heart, torso-tank preparation, both of which we have developed over decades and used to gather valuable insights from hundreds of experiments.
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Affiliation(s)
- Brian Zenger
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States,Nora Eccles Harrison Cardiovascular Research and Training Institute, The University of Utah, Salt Lake City, UT, United States,Spencer Eccles School of Medicine, University of Utah, Salt Lake City, UT, United States,*Correspondence: Brian Zenger,
| | - Jake A. Bergquist
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States,Nora Eccles Harrison Cardiovascular Research and Training Institute, The University of Utah, Salt Lake City, UT, United States,Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
| | - Anna Busatto
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States,Nora Eccles Harrison Cardiovascular Research and Training Institute, The University of Utah, Salt Lake City, UT, United States,Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
| | | | - Lindsay C. Rupp
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States,Nora Eccles Harrison Cardiovascular Research and Training Institute, The University of Utah, Salt Lake City, UT, United States,Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
| | - Vikas Sharma
- Spencer Eccles School of Medicine, University of Utah, Salt Lake City, UT, United States
| | - Rob S. MacLeod
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States,Nora Eccles Harrison Cardiovascular Research and Training Institute, The University of Utah, Salt Lake City, UT, United States,Department of Biomedical Engineering, College of Engineering, University of Utah, Salt Lake City, UT, United States
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Bergquist J, Rupp L, Zenger B, Brundage J, Busatto A, MacLeod RS. Body Surface Potential Mapping: Contemporary Applications and Future Perspectives. HEARTS 2021; 2:514-542. [PMID: 35665072 PMCID: PMC9164986 DOI: 10.3390/hearts2040040] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/01/2023] Open
Abstract
Body surface potential mapping (BSPM) is a noninvasive modality to assess cardiac bioelectric activity with a rich history of practical applications for both research and clinical investigation. BSPM provides comprehensive acquisition of bioelectric signals across the entire thorax, allowing for more complex and extensive analysis than the standard electrocardiogram (ECG). Despite its advantages, BSPM is not a common clinical tool. BSPM does, however, serve as a valuable research tool and as an input for other modes of analysis such as electrocardiographic imaging and, more recently, machine learning and artificial intelligence. In this report, we examine contemporary uses of BSPM, and provide an assessment of its future prospects in both clinical and research environments. We assess the state of the art of BSPM implementations and explore modern applications of advanced modeling and statistical analysis of BSPM data. We predict that BSPM will continue to be a valuable research tool, and will find clinical utility at the intersection of computational modeling approaches and artificial intelligence.
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Affiliation(s)
- Jake Bergquist
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA
- Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Lindsay Rupp
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA
- Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Brian Zenger
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA
- Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, UT 84112, USA
- School of Medicine, University of Utah, Salt Lake City, UT 84112, USA
| | - James Brundage
- School of Medicine, University of Utah, Salt Lake City, UT 84112, USA
| | - Anna Busatto
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Rob S. MacLeod
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA
- Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, Salt Lake City, UT 84112, USA
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