TY - GEN
T1 - A framework for the pre-clinical validation of LBM-EP for the planning and guidance of ventricular tachycardia ablation
AU - Mansi, Tommaso
AU - Beinart, Roy
AU - Zettinig, Oliver
AU - Rapaka, Saikiran
AU - Georgescu, Bogdan
AU - Kamen, Ali
AU - Dori, Yoav
AU - Zviman, M. Muz
AU - Herzka, Daniel A.
AU - Halperin, Henry R.
AU - Comaniciu, Dorin
PY - 2014
Y1 - 2014
N2 - This manuscript presents a framework for the pre-clinical validation of LBM-EP, a fast cardiac electrophysiology model based on the lattice-Boltzmann method (LBM). The overarching goal is to assess whether the model is able to predict ventricular tachycardia (VT) induction given lead location and stimulation protocol. First, the randomwalk algorithm is used to interactively segment the heart ventricles from delayed-enhancement magnetic resonance images (DE-MRI). Scar and border zone are visually delineated using image thresholding. Then, a detailed anatomical model is generated, comprising fiber architecture and spatial distribution of action potential duration. That information is rasterized to a Cartesian grid, and the cardiac potentials are computed. The framework is illustrated on one swine data, for which two different pacing protocols at four different sites were tested. Each of the protocols were then virtually tested by computing seven seconds of heart beat. Model predictions in terms of VT induction were compared with what was observed in the animal. Our parallel implementation on graphics processing units required a total computation time of about two minutes at an isotropic grid resolution of 0.8 mm (21s at a resolution of 1.5 mm), thus enabling interactive VT testing.
AB - This manuscript presents a framework for the pre-clinical validation of LBM-EP, a fast cardiac electrophysiology model based on the lattice-Boltzmann method (LBM). The overarching goal is to assess whether the model is able to predict ventricular tachycardia (VT) induction given lead location and stimulation protocol. First, the randomwalk algorithm is used to interactively segment the heart ventricles from delayed-enhancement magnetic resonance images (DE-MRI). Scar and border zone are visually delineated using image thresholding. Then, a detailed anatomical model is generated, comprising fiber architecture and spatial distribution of action potential duration. That information is rasterized to a Cartesian grid, and the cardiac potentials are computed. The framework is illustrated on one swine data, for which two different pacing protocols at four different sites were tested. Each of the protocols were then virtually tested by computing seven seconds of heart beat. Model predictions in terms of VT induction were compared with what was observed in the animal. Our parallel implementation on graphics processing units required a total computation time of about two minutes at an isotropic grid resolution of 0.8 mm (21s at a resolution of 1.5 mm), thus enabling interactive VT testing.
UR - http://www.scopus.com/inward/record.url?scp=84898926965&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-54268-8_30
DO - 10.1007/978-3-642-54268-8_30
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AN - SCOPUS:84898926965
SN - 9783642542671
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 253
EP - 261
BT - Statistical Atlases and Computational Models of the Heart
PB - Springer Verlag
T2 - 4th International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges, STACOM 2013, Held in Conjunction with MICCAI 2013
Y2 - 26 September 2013 through 26 September 2013
ER -