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Cardiac Position Sensitivity Study in the Electrocardiographic Forward Problem Using Stochastic Collocation and Boundary Element Methods

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Abstract

The electrocardiogram (ECG) is ubiquitously employed as a diagnostic and monitoring tool for patients experiencing cardiac distress and/or disease. It is widely known that changes in heart position resulting from, for example, posture of the patient (sitting, standing, lying) and respiration significantly affect the body-surface potentials; however, few studies have quantitatively and systematically evaluated the effects of heart displacement on the ECG. The goal of this study was to evaluate the impact of positional changes of the heart on the ECG in the specific clinical setting of myocardial ischemia. To carry out the necessary comprehensive sensitivity analysis, we applied a relatively novel and highly efficient statistical approach, the generalized polynomial chaos-stochastic collocation method, to a boundary element formulation of the electrocardiographic forward problem, and we drove these simulations with measured epicardial potentials from whole-heart experiments. Results of the analysis identified regions on the body-surface where the potentials were especially sensitive to realistic heart motion. The standard deviation (STD) of ST-segment voltage changes caused by the apex of a normal heart, swinging forward and backward or side-to-side was approximately 0.2 mV. Variations were even larger, 0.3 mV, for a heart exhibiting elevated ischemic potentials. These variations could be large enough to mask or to mimic signs of ischemia in the ECG. Our results suggest possible modifications to ECG protocols that could reduce the diagnostic error related to postural changes in patients possibly suffering from myocardial ischemia.

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Acknowledgments

The authors would like to thank Dr. Dongbin Xiu of Purdue University (USA) for his generous help with generalized polynomial chaos and Dr. Tom Fletcher for his mathematical insights. We also appreciate the input on clinical electrocardiography from Ravi Ranjan, MD/PhD and Chris McGann, MD. We also gratefully acknowledge the computational support and resources provided by the Scientific Computing and Imaging Institute. This work was funded by a University of Utah Seed Grant Award, NSF Career Award (Kirby) NSF-CCF0347791, NSF IIS-0914564, and the NIH NCRR Center for Integrative Biomedical Computing (http://www.sci.utah.edu/cibc), NIH NCRR Grant No. P41-RR12553-12. Support for the acquisition of the experiment data came from the Nora Eccles Treadwell Foundation.

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Authors and Affiliations

  1. Department of Bioengineering, University of Utah, Salt Lake City, UT, USA

    Darrell J. Swenson & Rob S. MacLeod

  2. Scientific Computing and Imaging Institute, Salt Lake City, UT, USA

    Darrell J. Swenson, Sarah E. Geneser, Jeroen G. Stinstra, Robert M. Kirby & Rob S. MacLeod

  3. Nora Eccles Harrison Cardiovascular Research and Training Institute, Salt Lake City, UT, USA

    Rob S. MacLeod

  4. School of Computing, University of Utah, Salt Lake City, UT, USA

    Robert M. Kirby

Authors
  1. Darrell J. Swenson
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  2. Sarah E. Geneser
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  3. Jeroen G. Stinstra
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  4. Robert M. Kirby
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  5. Rob S. MacLeod
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Corresponding authors

Correspondence to Darrell J. Swenson, Robert M. Kirby or Rob S. MacLeod.

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Associate Editor Joan Greve oversaw the review of this article.

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Swenson, D.J., Geneser, S.E., Stinstra, J.G. et al. Cardiac Position Sensitivity Study in the Electrocardiographic Forward Problem Using Stochastic Collocation and Boundary Element Methods. Ann Biomed Eng 39, 2900–2910 (2011). https://doi.org/10.1007/s10439-011-0391-5

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  • DOI: https://doi.org/10.1007/s10439-011-0391-5

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