Chinchapatnam P P, Rhode K S, King A, Gao G, Ma Y, Schaeffter T, Hawkes D, Razavi R S, Hill D L G, Arridge S, Sermesant M
University College London, Centre for Medical Image Computing, UK.
Med Image Comput Comput Assist Interv. 2007;10(Pt 1):575-83. doi: 10.1007/978-3-540-75757-3_70.
Cardiac arrhythmias are increasingly being treated using ablation procedures. Development of fast electrophysiological models and estimation of parameters related to conduction pathologies can aid in the investigation of better treatment strategies during Radio-frequency ablations. We present a fast electrophysiological model incorporating anisotropy of the cardiac tissue. A global-local estimation procedure is also outlined to estimate a hidden parameter (apparent electrical conductivity) present in the model. The proposed model is tested on synthetic and real data derived using XMR imaging. We demonstrate a qualitative match between the estimated conductivity parameter and possible pathology locations. This approach opens up possibilities to directly integrate modelling in the intervention room.
心律失常越来越多地通过消融手术进行治疗。快速电生理模型的开发以及与传导病理相关参数的估计有助于在射频消融过程中研究更好的治疗策略。我们提出了一种纳入心脏组织各向异性的快速电生理模型。还概述了一种全局-局部估计程序,以估计模型中存在的一个隐藏参数(表观电导率)。所提出的模型在使用XMR成像获得的合成数据和真实数据上进行了测试。我们展示了估计的电导率参数与可能的病理位置之间的定性匹配。这种方法为在手术室直接整合建模开辟了可能性。