Why the study?
Does the bidomain model and body surface potential maps (BSPMs) algorithm accurately identify the size and position of ischemic regions in patients?
Does the bidomain model and body surface potential maps (BSPMs) algorithm accurately identify the size and position of ischemic regions in patients?
The bidomain model using body surface potential maps can identify the size and position of ischemic regions with results comparable to perfusion scintigraphy.
Hypothesis-generating for BSPM ischemia mapping; prospective validation needed before clinical adoption.
We investigate whether it is possible to use the bidomain model and body surface potential maps (BSPMs) to compute the size and position of ischemic regions in the human heart. This leads to a severely ill posed inverse problem for a potential equation. We do not use the classical inverse problems of electrocardiography, in which the unknown sources are the epicardial potential distribution or the activation sequence. Instead we employ the bidomain theory to obtain a model that also enables identification of ischemic regions transmurally. This approach makes it possible to distinguish between subendocardial and transmural cases, only using the BSPM data. The main focus is on testing a previously published algorithm on clinical data, and the results are compared with images taken with perfusion scintigraphy. For the four patients involved in this study, the two modalities produce results that are rather similar: The relative differences between the center of mass and the size of the ischemic regions, suggested by the two modalities, are 10.8% ± 4.4% and 7.1% ± 4.6%, respectively. We also present some simulations which indicate that the methodology is robust with respect to uncertainties in important model parameters. However, in contrast to what has been observed in investigations only involving synthetic data, inequality constraints are needed to obtain sound results.
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Nielsen et al. (2013) studied this question.
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