Lesion size estimator of cardiac radiofrequency ablation at different common locations with different tip temperatures

被引:28
作者
Lai, YC
Bin Choy, Y
Haemmerich, D
Vorperian, VR
Webster, JG
机构
[1] Univ Wisconsin, Dept Biomed Engn, Madison, WI 53706 USA
[2] Univ Wisconsin, Dept Elect & Comp Engn, Madison, WI 53706 USA
[3] Univ Illinois, Dept Elect & Comp Engn, Urbana, IL 61801 USA
[4] Univ Wisconsin, Dept Surg, Madison, WI 53792 USA
[5] Univ Wisconsin, Dept Med, Madison, WI 53792 USA
关键词
ablation; bio-heat equation; cardiac ablation; finite element method; RF ablation; temperature-controlled ablation;
D O I
10.1109/TBME.2004.831529
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Finite element method (FEM) analysis has become a common method to analyze the lesion formation during temperature-controlled radiofrequency (RF) cardiac ablation. We present a process of FEM modeling a system including blood, myocardium, and an ablation catheter with a thermistor embedded at the tip. The simulation used a simple proportionalintegral (PI) controller to control the entire process operated in temperature-controlled mode. Several factors affect the lesion size such as target temperature, blood flow rate, and application time. We simulated the time response of RF ablation at different locations by using different target temperatures. The applied sites were divided into two groups each with a different convective heat transfer coefficient. The first group was high-flow such as the atrioventricular (AV) node and the atrial aspect of the AV annulus, and the other was low-flow such as beneath the valve or inside the coronary sinus. Results showed the change of lesion depth and lesion width with time, under different conditions. We collected data for all conditions and used it to create a database. We implemented a user-interface, the lesion size estimator, where the user enters set temperature and location. Based on the database, the software estimated lesion dimensions during different applied durations. This software could be used as a first-step predictor to help the electrophysiologist choose treatment parameters.
引用
收藏
页码:1859 / 1864
页数:6
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