Title :
Noninvasive identification of three-dimensional myocardial infarctions from inversely reconstructed equivalent current density
Author :
Zhaoye Zhou ; Chengzong Han ; Bin He
Author_Institution :
Dept. of Biomed. Eng., Univ. of Minnesota, Minneapolis, MN, USA
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.
Keywords :
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; Abstracts; Biological system modeling; Computational modeling; Electrodes; Imaging; Size measurement; Weight measurement;
Conference_Titel :
Computing in Cardiology Conference (CinC), 2014
Print_ISBN :
978-1-4799-4346-3