Abstract
Noninvasive cardiac electrophysiological imaging (IECG), the effort to use body surface potential measurement to estimate subject-specific electrophysiological activity of the heart, traditionally is performed on detailed heart-torso models that are completely reconstructed from a large amount of images. This geometrical modeling brings high demands of operational time and data acquisition, rendering current IECG techniques clinically impractical. In this study, we investigate the feasibility to use an alternative geometrical model that excludes local details but captures subject-specific global geometrical parameters that have been regarded essential for reliable IECG solutions. This is done by using limited images and image metadata to customize a pre-defined, generic ventricle and electrode-array representation to subject-specific ventricle size, position, orientation and electrode position on the body surface. We apply this simplified geometrical modeling in IECG studies of post myocardial infarction patients; the results of transmembrane potential imaging and infarct quantitation are compared with the gold standard and results from the same IECG approach using traditional, detailed heart-torso model. This study shows that local geometrical details do not have significant impact on IECG solutions and excluding them from geometrical modeling might be of potential to drive cardiac electrophysiological imaging closer towards clinical practicability.
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Wang, L., Wong, K.C.L., Zhang, H., Liu, H., Shi, P. (2010). How Much Geometrical Detail Do We Need in Cardiac Electrophysiological Imaging? A Generic Heart-Torso Representation for Fast Subject-Specific Customization. In: Camara, O., Pop, M., Rhode, K., Sermesant, M., Smith, N., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. STACOM 2010. Lecture Notes in Computer Science, vol 6364. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15835-3_24
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DOI: https://doi.org/10.1007/978-3-642-15835-3_24
Publisher Name: Springer, Berlin, Heidelberg
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