TY - JOUR
T1 - Simulation of the electromechanical activity of the heart using XMR interventional imaging
AU - Sermesant, Maxime
AU - Rhode, Kawal
AU - Anjorin, Angela
AU - Hegde, Sanjeet
AU - Sanchez-Ortiz, Gerardo
AU - Rueckert, Daniel
AU - Lambiase, Pier
AU - Bucknall, Clifford
AU - Hill, Derek
AU - Razavi, Reza
PY - 2004
Y1 - 2004
N2 - Simulating cardiac electromechanical activity is of great interest for a better understanding of pathologies and therapy planning. Design and validation of such models is difficult due to the lack of clinical data. XMR systems are a new type of interventional facility in which patients can be rapidly transferred between x-ray and MR systems. Our goal is to design and validate an electromechanical model of the myocardium, using this XMR system. The proposed model is computationally fast and uses clinically observable parameters. We present the integration of anatomy, electrophysiology, and motion from patients. Pathologies are introduced in the model and the simulations are compared to measured data. Initial qualitative comparison is encouraging. Quantitative local validation is in progress. Once validated, these models will make it possible to simulate different interventional strategies.
AB - Simulating cardiac electromechanical activity is of great interest for a better understanding of pathologies and therapy planning. Design and validation of such models is difficult due to the lack of clinical data. XMR systems are a new type of interventional facility in which patients can be rapidly transferred between x-ray and MR systems. Our goal is to design and validate an electromechanical model of the myocardium, using this XMR system. The proposed model is computationally fast and uses clinically observable parameters. We present the integration of anatomy, electrophysiology, and motion from patients. Pathologies are introduced in the model and the simulations are compared to measured data. Initial qualitative comparison is encouraging. Quantitative local validation is in progress. Once validated, these models will make it possible to simulate different interventional strategies.
UR - https://www.scopus.com/pages/publications/20344374406
U2 - 10.1007/978-3-540-30136-3_96
DO - 10.1007/978-3-540-30136-3_96
M3 - Conference article
AN - SCOPUS:20344374406
SN - 0302-9743
VL - 3217
SP - 786
EP - 794
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
IS - 1 PART 2
T2 - Medical Image Computing and Computer-Assisted Intervention, MICCAI 2004 - 7th International Conference, Proceedings
Y2 - 26 September 2004 through 29 September 2004
ER -