Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America. Biointerfaces Institute, University of Michigan, Ann Arbor, MI, United States of America.
J Neural Eng. 2020 Jun 12;17(3):036019. doi: 10.1088/1741-2552/ab8fc4.
Spinal cord stimulation (SCS) is a common neurostimulation therapy to treat chronic pain. Computational models represent a valuable tool to study the potential mechanisms of action of SCS and to optimize the design and implementation of SCS technologies. However, it is imperative that these computational models include the appropriate level of detail to accurately predict the neural response to SCS and to correlate model predictions with clinical outcomes. Therefore, the goal of this study was to investigate several anatomic and technical factors that may affect model-based predictions of neural activation during thoracic SCS.
We developed computational models that consisted of detailed finite element models of the lower thoracic spinal cord, surrounding tissues, and implanted SCS electrode arrays. We positioned multicompartment models of sensory axons within the spinal cord to calculate the activation threshold for each sensory axon. We then investigated how activation thresholds changed as a function of several anatomical variables (e.g. spine geometry, dorsal rootlet anatomy), stimulation type (i.e. voltage-controlled vs. current-controlled), electrode impedance, lead position, lead type, and electrical properties of surrounding tissues (e.g. dura conductivity, frequency-dependent conductivity).
Several anatomic and modeling factors produced significant percent differences or errors in activation thresholds. Rostrocaudal positioning of the cathode with respect to the vertebrae had a large effect (up to 32%) on activation thresholds. Variability in electrode impedance produced significant changes in activation thresholds for voltage-controlled stimulation (38% to 51%), but had little effect on activation thresholds for current-controlled stimulation (less than 13%). Changing the dura conductivity also produced significant differences in activation thresholds.
This study demonstrates several anatomic and technical factors that can affect the neural response to SCS. These factors should be considered in clinical implementation and in future computational modeling studies of thoracic SCS.
脊髓刺激(SCS)是一种治疗慢性疼痛的常见神经刺激疗法。计算模型是研究 SCS 潜在作用机制和优化 SCS 技术设计和实施的有价值的工具。然而,至关重要的是,这些计算模型包含适当的细节水平,以准确预测 SCS 对神经的反应,并将模型预测与临床结果相关联。因此,本研究的目的是研究几种解剖学和技术因素,这些因素可能会影响 SCS 期间神经激活的基于模型的预测。
我们开发了计算模型,这些模型由下胸段脊髓、周围组织和植入的 SCS 电极阵列的详细有限元模型组成。我们将感觉轴突的多腔室模型定位在脊髓内,以计算每个感觉轴突的激活阈值。然后,我们研究了激活阈值如何随几个解剖学变量(例如脊柱几何形状、背根干解剖)、刺激类型(即电压控制与电流控制)、电极阻抗、导联位置、导联类型以及周围组织的电学特性(例如硬脑膜导电性、频率相关导电性)而变化。
几个解剖学和建模因素导致激活阈值的百分比差异或误差很大。与椎体相比,阴极的头尾位置对激活阈值有很大影响(高达 32%)。电极阻抗的变化对电压控制刺激的激活阈值产生了显著变化(38%至 51%),但对电流控制刺激的激活阈值影响很小(小于 13%)。改变硬脑膜导电性也会导致激活阈值产生显著差异。
本研究表明,有几个解剖学和技术因素会影响 SCS 的神经反应。这些因素应在临床实施和未来的 SCS 计算模型研究中加以考虑。