Paper
31 January 2017 Identification of border-zone corridors in the left ventricle using the core expansion method
L. Serra, R. M. Figueras i Ventura, X. Planes, M. Steghöfer, J. Fernández-Armenta, D. Penela, J. Acosta, A. Berruezo
Author Affiliations +
Proceedings Volume 10160, 12th International Symposium on Medical Information Processing and Analysis; 1016011 (2017) https://doi.org/10.1117/12.2255817
Event: 12th International Symposium on Medical Information Processing and Analysis, 2016, Tandil, Argentina
Abstract
This article presents the Core Expansion method to automatically detect border-zone corridors in MRI images of the left ventricle, to serve as guidance to Ventricular Tachycardia (VT) ablation. The method relies on the fact that the different gray level intensities of Delayed Contrast-Enhanced Magnetic Resonance Images (DE-MRI) encode information about the fibrotic tissue. These differences in intensities among tissue types allow separating dense scar from healthy areas of the myocardium, and identify the border-zone region. After generating an onion-like layer-based 3D model of the left ventricle, the method detects potential corridors in the border-zone that can become electrical circuits of low conductivity. These circuits can be responsible for arrhythmic events. The method has been tested both in phantoms and patients. In patients there was a high degree of correlation between the channels detected and those visually identified by an expert on the MRI. Whenever electroanatomical maps were available post-intervention, the MRI detected channels were found to have a high degree of correlation with them.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
L. Serra, R. M. Figueras i Ventura, X. Planes, M. Steghöfer, J. Fernández-Armenta, D. Penela, J. Acosta, and A. Berruezo "Identification of border-zone corridors in the left ventricle using the core expansion method", Proc. SPIE 10160, 12th International Symposium on Medical Information Processing and Analysis, 1016011 (31 January 2017); https://doi.org/10.1117/12.2255817
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KEYWORDS
Tissues

Magnetic resonance imaging

Visualization

3D modeling

Heart

Optical spheres

Image segmentation

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