Argyrios Petras PhD , Gerard Amoros Figueras PhD , Zoraida Moreno Weidmann MD , Tomás García-Sánchez PhD , David Viladés Medel MD, PhD , Antoni Ivorra PhD , Jose M. Guerra MD, PhD , Luca Gerardo-Giorda PhD
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However, the predicted lesion anisotropy ratios (width over depth) vary extensively among recent studies, and these discrepancies remain a subject of discussion.</div></div><div><h3>Objective</h3><div>This work aims to evaluate the predicted lesion anisotropy ratios using a PFA computational model by applying it to an open-chest in vivo porcine model geometry.</div></div><div><h3>Methods</h3><div>Six domestic swine underwent epicardial PFA applications using a previously described waveform protocol. Animals were killed at least 3 hours after the last ablation, and lesions were assessed using triphenyltetrazolium chloride (TTC) staining. Numeric simulations were performed on a segmented and meshed porcine thoracic computed tomography (CT) scan, mimicking the open-chest experimental setup.</div></div><div><h3>Results</h3><div>The maximum width of all simulated lesions was observed at the epicardial surface. The anisotropy ratios (AR) of the experimental lesions were smaller than the simulated ones (AR experimental vs simulated, 1.0–1.7 vs 2–2.7; Q1–Q3 quartiles). Increasing the peak voltage resulted in larger lesions; however, the computational model clearly underestimated the increase in lesion depth compared with the experimental data.</div></div><div><h3>Conclusion</h3><div>Our computational model shows that a single lethal electric field threshold is insufficient to accurately predict both lesion depth and width in cardiac PFA. 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引用次数: 0
摘要
脉冲场消融(PFA)是一种基于不可逆电穿孔(IRE)的新型心脏消融技术。PFA计算模型依赖于致命电场阈值的识别来预测IRE区域。然而,在最近的研究中,预测的病变各向异性比率(宽度比深度)差异很大,这些差异仍然是讨论的主题。目的:利用PFA计算模型对猪开胸模型的几何形状进行预测,评估病变各向异性比率。方法6头家猪采用先前描述的波形方案进行心外膜PFA应用。动物在最后一次消融后至少3小时被杀死,并用三苯基四氮唑氯(TTC)染色评估病变。数值模拟在猪胸部分段和网格计算机断层扫描(CT)上进行,模拟开胸实验设置。结果所有模拟病灶的最大宽度均在心外膜表面。实验病变的各向异性比(AR)小于模拟病变(AR实验vs模拟,1.0 ~ 1.7 vs 2 ~ 2.7;Q1-Q3四分位数)。峰值电压越大,病变越大;然而,与实验数据相比,计算模型明显低估了病变深度的增加。结论我们的计算模型显示单一致死电场阈值不足以准确预测心脏PFA病变深度和宽度。我们的研究表明,对于给定的PFA波形,270至500 V/cm之间的阈值可以提供令人满意的病变深度估计,而790至1000 V/cm之间的更高阈值可以更好地捕获病变宽度。
Is a single lethal electric field threshold sufficient to characterize the lesion size in computational modeling of cardiac pulsed-field ablation?
Background
Pulsed-field ablation (PFA) is a novel cardiac ablation technology based on irreversible electroporation (IRE). PFA computational models rely on identification of a lethal electric field threshold to predict the IRE area. However, the predicted lesion anisotropy ratios (width over depth) vary extensively among recent studies, and these discrepancies remain a subject of discussion.
Objective
This work aims to evaluate the predicted lesion anisotropy ratios using a PFA computational model by applying it to an open-chest in vivo porcine model geometry.
Methods
Six domestic swine underwent epicardial PFA applications using a previously described waveform protocol. Animals were killed at least 3 hours after the last ablation, and lesions were assessed using triphenyltetrazolium chloride (TTC) staining. Numeric simulations were performed on a segmented and meshed porcine thoracic computed tomography (CT) scan, mimicking the open-chest experimental setup.
Results
The maximum width of all simulated lesions was observed at the epicardial surface. The anisotropy ratios (AR) of the experimental lesions were smaller than the simulated ones (AR experimental vs simulated, 1.0–1.7 vs 2–2.7; Q1–Q3 quartiles). Increasing the peak voltage resulted in larger lesions; however, the computational model clearly underestimated the increase in lesion depth compared with the experimental data.
Conclusion
Our computational model shows that a single lethal electric field threshold is insufficient to accurately predict both lesion depth and width in cardiac PFA. Our study suggests that for the given PFA waveforms, a threshold between 270 and 500 V/cm provides satisfactory lesion depth estimations, and a higher threshold between 790 and 1000 V/cm better captures the lesion width.