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
Link To Document :
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