A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.
Harvard Medical School, Boston, Massachusetts, USA.
Magn Reson Med. 2023 Oct;90(4):1594-1609. doi: 10.1002/mrm.29717. Epub 2023 Jun 8.
Modern high-amplitude gradient systems can be limited by the International Electrotechnical Commission 60601-2-33 cardiac stimulation (CS) limit, which was set in a conservative manner based on electrode experiments and E-field simulations in uniform ellipsoidal body models. Here, we show that coupled electromagnetic-electrophysiological modeling in detailed body and heart models can predict CS thresholds, suggesting that such modeling might lead to more detailed threshold estimates in humans. Specifically, we compare measured and predicted CS thresholds in eight pigs.
We created individualized porcine body models using MRI (Dixon for the whole body, CINE for the heart) that replicate the anatomy and posture of the animals used in our previous experimental CS study. We model the electric fields induced along cardiac Purkinje and ventricular muscle fibers and predict the electrophysiological response of these fibers, yielding CS threshold predictions in absolute units for each animal. Additionally, we assess the total modeling uncertainty through a variability analysis of the 25 main model parameters.
Predicted and experimental CS thresholds agree within 19% on average (normalized RMS error), which is smaller than the 27% modeling uncertainty. No significant difference was found between the modeling predictions and experiments (p < 0.05, paired t-test).
Predicted thresholds matched the experimental data within the modeling uncertainty, supporting the model validity. We believe that our modeling approach can be applied to study CS thresholds in humans for various gradient coils, body shapes/postures, and waveforms, which is difficult to do experimentally.
现代高振幅梯度系统可能会受到国际电工委员会 60601-2-33 心脏刺激 (CS) 限制的限制，该限制是基于电极实验和均匀椭球体模型中的 E 场模拟以保守方式设定的。在这里，我们表明，在详细的身体和心脏模型中进行的电磁-电生理联合建模可以预测 CS 阈值，这表明这种建模可能会导致对人类更详细的阈值估计。具体来说，我们比较了八头猪的测量和预测 CS 阈值。
我们使用 MRI（Dixon 用于整个身体，CINE 用于心脏）创建了个体化的猪体模型，该模型复制了我们之前进行的 CS 实验中使用的动物的解剖结构和姿势。我们对心脏浦肯野纤维和心室肌纤维感应的电场进行建模，并预测这些纤维的电生理反应，从而为每个动物提供绝对单位的 CS 阈值预测。此外，我们通过对 25 个主要模型参数的变异性分析来评估总建模不确定性。
平均而言，预测和实验 CS 阈值相差 19%（归一化 RMS 误差），这小于 27%的建模不确定性。模型预测与实验之间没有发现显着差异（p<0.05，配对 t 检验）。
预测阈值与建模不确定性内的实验数据匹配，支持模型的有效性。我们相信，我们的建模方法可以应用于研究各种梯度线圈、身体形状/姿势和波形下的人体 CS 阈值，这在实验中很难做到。
