DocumentCode
74007
Title
Noninvasive Imaging of 3-Dimensional Myocardial Infarction From the Inverse Solution of Equivalent Current Density in Pathological Hearts
Author
Zhaoye Zhou ; Chengzong Han ; Ting Yang ; Bin He
Author_Institution
Dept. of Biomed. Eng., Univ. of Minnesota, Minneapolis, MN, USA
Volume
62
Issue
2
fYear
2015
fDate
Feb. 2015
Firstpage
468
Lastpage
476
Abstract
We propose a new approach to noninvasively image the 3-D myocardial infarction (MI) substrates based on equivalent current density (ECD) distribution that is estimated from the body surface potential maps (BSPMs) during S-T segment. The MI substrates were identified using a predefined threshold of ECD. Computer simulations were performed to assess the performance with respect to: 1) MI locations; 2) MI sizes; 3) measurement noise; 4) numbers of BSPM electrodes; and 5) volume conductor modeling errors. A total of 114 sites of transmural infarctions, 91 sites of epicardial infarctions, and 36 sites of endocardial infarctions were simulated. The simulation results show that: 1) Under 205 electrodes and 10-μV noise, the averaged accuracies of imaging transmural MI are 83.4% for sensitivity, 82.2% for specificity, 65.0% for Dice´s coefficient, and 6.5 mm for distances between the centers of gravity (DCG). 2) For epicardial infarction, the averaged imaging accuracies are 81.6% for sensitivity, 75.8% for specificity, 45.3% for Dice´s coefficient, and 7.5 mm for DCG; while for endocardial infarction, the imaging accuracies are 80.0% for sensitivity, 77.0% for specificity, 39.2% for Dice´s coefficient, and 10.4 mm for DCG. 3) A reasonably good imaging performance was obtained under higher noise levels, fewer BSPM electrodes, and mild volume conductor modeling errors. The present results suggest that this method has the potential to aid in the clinical identification of the MI substrates.
Keywords
bioelectric potentials; biomedical electrodes; diseases; electrocardiography; error analysis; feature extraction; image reconstruction; inverse problems; medical image processing; noise; statistical analysis; substrates; 3-dimensional myocardial infarction; 3D MI substrate imaging; 3D myocardial infarction substrate imaging; BSPM electrode number; Dice coefficient; ECD distribution estimation; ECD threshold; MI location; MI size; S-T segment; averaged imaging accuracy; averaged transmural MI imaging accuracy; body surface potential map; clinical MI substrate identification; computer simulation; endocardial infarction site simulation; epicardial infarction site simulation; equivalent current density distribution; imaging performance assessment; inverse solution; measurement noise; noninvasive imaging; pathological heart; transmural infarction site simulation; volume conductor modeling error; Computer simulation; Electric potential; Heart; Imaging; Myocardium; Sensitivity; Substrates; BSPM; ECG; Inverse problem; myocardial infarction (MI); three-dimensional electrocardiographic imaging;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/TBME.2014.2358618
Filename
6901202
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