Department of Biomedical Engineering, Hanoi University of Science and Technology, Hanoi, Vietnam. School of Electrical and Information Engineering, University of Sydney, Sydney, Australia.
Physiol Meas. 2019 Jul 1;40(6):065006. doi: 10.1088/1361-6579/ab1937.
Radiofrequency (RF) cardiac ablation is a commonly used method for treating cardiac arrhythmias in which the information of the dynamic lesion heating is critical to cardiologists but is currently lacking. Electrical impedance tomography (EIT) is a temporal modality of imaging the changes in the electrical properties within a measured object and hence might be able to track the electrical variation due to temperature changes within the myocardium. Within this paper, (1) a time-efficient algorithm with self-weighted NOSER-prior and (2) a measurement filtering process for optimizing the number of measurement were proposed for monitoring the lesion size during the cardiac RF ablation, taking advantage of internal catheter-based electrodes and the prior information of anatomical structure and the catheter location, which are usually available during the ablation course.
A tank model with a circular myocardium of 12 mm in thickness, 16 external electrodes on the boundary and three internal catheter-based electrodes positioned inside the endocardium were made. The ablations were simulated using Pennes' bioheat transfer equation and the simulated temperature gradients were then transferred to EIT measurements. The algorithm used one reference ablation for its optimization and then was tested with numerous 90 s ablations containing three disturbances: the catheter location mapping, the wide range of varied myocardium conductivity and the blood's cooling convection, and the Gaussian noises with 10-40 µV in standard deviation.
The results showed that, with the optimized number of 55 measurements, the algorithm still performed well when dealing with all three disturbances plus the random noises up 25 µV. Specifically, the lesion depth and width were measured within 1.6 mm and 3.2 mm in error respectively in at least 80% out of 100 simulated ablations.
The algorithm has successfully measured the lesion size with good accuracy and tolerances of noise and other system perturbations. More tests in vitro and in vivo are required in the future to confirm the algorithm's feasibility.
射频（RF）心脏消融是治疗心律失常的常用方法，其中动态病变加热信息对心脏病专家至关重要，但目前尚缺乏这种信息。电阻抗断层成像（EIT）是一种对测量对象内部电特性变化进行成像的时间模式，因此可能能够跟踪心肌内由于温度变化引起的电变化。在本文中，（1）提出了一种具有自加权 NOSER 先验的高效时间算法，（2）提出了一种测量滤波过程，用于优化测量数量，以利用内部基于导管的电极以及解剖结构和导管位置的先验信息，这些信息通常在消融过程中可用，从而监测心脏 RF 消融过程中的病变大小。
制作了一个具有 12mm 厚的圆形心肌、边界上有 16 个外部电极和三个位于心内膜内的基于导管的内部电极的水槽模型。使用 Pennes 生物传热方程模拟消融，并将模拟的温度梯度转换为 EIT 测量值。该算法使用一个参考消融进行优化，然后用包含三种干扰的多个 90s 消融进行测试：导管位置映射、广泛变化的心肌电导率和血液冷却对流以及标准差为 10-40µV 的高斯噪声。
结果表明，在优化的 55 次测量次数下，该算法在处理所有三种干扰以及高达 25µV 的随机噪声时仍能很好地工作。具体来说，在至少 80%的 100 次模拟消融中，病变深度和宽度的测量误差分别在 1.6mm 和 3.2mm 以内。
该算法成功地以良好的精度测量了病变大小，并具有良好的噪声和其他系统干扰容限。未来需要进行更多的体外和体内测试，以确认该算法的可行性。
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