High-Resolution Multi-Scale Computational Model for Non-Invasive Cervical Vagus Nerve Stimulation.
High-Resolution Multi-Scale Computational Model for Non-Invasive Cervical Vagus Nerve Stimulation.
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DOI：
10.1111/ner.12706
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发表时间：
2018-04
期刊：
影响因子：
--
通讯作者：
Bikson M
中科院分区：
文献类型：
--
作者：
Mourdoukoutas AP;Truong DQ;Adair DK;Simon BJ;Bikson M
建立第一个高分辨率、多尺度的颈部无创迷走神经刺激(NVNS)模型，并预测迷走神经纤维的激活类型，给出临床相关的流变学阈值。为了准确模拟关键的宏观组织成分(如皮肤、软组织、肌肉)和介观组织成分(如颈椎增大、椎弓孔、脑脊液、神经鞘)，建立了基于MRI的有限元模型，以预测迷走神经沿线的细胞外电位、电场(E-field)和激活功能。为了比较不同大小的轴突(Aα纤维、Aβ纤维和Aδ纤维、B纤维和C纤维)的大小，建立了轴突的微观生物物理模型。Rhebase阈值估计基于阶跃函数波形。宏观尺度的精度决定迷走神经周围的电场大小，而中尺度的精度决定电场的变化(激活功能)。捕捉迷走神经穿过不断变化的组织环境(如骨到软组织)的中观解剖细节显著增强了预测的轴突敏感性，而包裹在同质组织(如神经鞘)中的轴突对nVNS的敏感性减弱。这些发现表明，需要在宏观和中观尺度上进行真实和精确的建模，以定量预测迷走神经的激活。基于这一方法，我们预测传统的颈椎NVNS方案可以激活A和B-纤维，但不能激活C-纤维。我们最先进的跨规模实施方案同样适用于脊髓刺激模型、皮质/深部脑刺激模型和其他外周/脑神经模型。
To develop the first high-resolution, multi-scale model of cervical non-invasive vagus nerve stimulation (nVNS) and to predict vagus fiber type activation, given clinically relevant rheobase thresholds. An MRI-derived Finite Element Method (FEM) model was developed to accurately simulate key macroscopic (e.g. skin, soft tissue, muscle) and mesoscopic (cervical enlargement, vertebral arch and foramen, CSF, nerve sheath) tissue components to predict extracellular potential, electric field (E-Field), and activating function along the vagus nerve. Microscopic scale biophysical models of axons were developed to compare axons of varying size (Aα-, Aβ- and Aδ-, B, and C-fibers). Rheobase threshold estimates were based on a step function waveform. Macro-scale accuracy was found to determine electric field magnitudes around the vagus nerve, while meso-scale precision determined E-field changes (activating function). Mesoscopic anatomical details that capture vagus nerve passage through a changing tissue environment (e.g. bone to soft tissue) profoundly enhanced predicted axon sensitivity while encapsulation in homogenous tissue (e.g. nerve sheath) dulled axon sensitivity to nVNS. These findings indicate that realistic and precise modeling at both macroscopic and mesoscopic scales are needed for quantitative predictions of vagus nerve activation. Based on this approach, we predict conventional cervical nVNS protocols can activate A- and B- but not C-fibers. Our state-of-the-art implementation across scales is equally valuable for models of spinal cord stimulation, cortex/deep brain stimulation, and other peripheral/cranial nerve models.
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