Noninvasive identification of three-dimensional myocardial infarctions from inversely reconstructed equivalent current density

CinC(2014)

Cited 23|Views11
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Abstract
The study presents a new approach to non-invasively identify the 3-dimensional MI substrate from the equivalent current densities (ECDs) that is inversely reconstructed from body surface potential maps (BSPMs). The MI substrate was characterized using a threshold determined from the ECD magnitude. A total of 114 sites of transmural infarctions, 91 sites of epicardial infarctions, and 36 sites of endocardial infarctions were simulated. The results show that: 1)With 205 BSPM electrodes and 10 μV Gaussian white noise, the averaged accuracies for transmural MI are sensitivity = 83.4%, specificity = 82.2%, and the distance between the centers of gravity (DCG) = 6.5mm. Epicardial infarctions (sensitivity = 81.6%, specificity = 75.8%, and DCG = 7.5mm) obtained similar accuracies to endocardial infarctions (sensitivity = 80.0%, specificity = 77.0%, and DCG = 10.4 mm). A reasonably good imaging performance was obtained under a higher noise level, fewer BSPM electrodes, and mild volume conductor modeling error, respectively. The results suggest that this method is capable of imaging the transmural and surface infarction.
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Key words
gaussian noise,bioelectric phenomena,biomedical electrodes,cardiovascular system,diseases,image denoising,medical computing,muscle,patient diagnosis,surface potential,3-dimensional mi substrate,3d mi substrate,3d myocardial infarctions,bspm electrodes,ecd magnitude,gaussian white noise,mi substrate characterization,body surface potential maps,distance between the centers of gravity,endocardial infarction simulation,epicardial infarction simulation,equivalent current densities,imaging noise level,inversely reconstructed ecd,inversely reconstructed equivalent current density,mild volume conductor modeling error,noninvasive myocardial infarction identification,surface infarction imaging,three-dimensional myocardial infarctions,transmural mi imaging,transmural mi sensitivity,transmural mi specificity,transmural infarction simulation,imaging,electrodes,computational modeling
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