Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA.
Department of Medicine, Case Western Reserve University, Cleveland, OH, USA.
Neuromodulation. 2022 Dec;25(8):1317-1329. doi: 10.1111/ner.13415. Epub 2022 Jun 14.
High-frequency spinal cord stimulation (HF-SCS) is a potential method to provide natural and effective inspiratory muscle pacing in patients with ventilator-dependent spinal cord injuries. Experimental data have demonstrated that HF-SCS elicits physiological activation of the diaphragm and inspiratory intercostal muscles via spinal cord pathways. However, the activation thresholds, extent of activation, and optimal electrode configurations (i.e., lead separation, contact spacing, and contact length) to activate these neural elements remain unknown. Therefore, the goal of this study was to use a computational modeling approach to investigate the direct effects of HF-SCS on the spinal cord and to optimize electrode design and stimulation parameters.
We developed a computer model of HF-SCS that consisted of two main components: 1) finite element models of the electric field generated during HF-SCS, and 2) multicompartment cable models of axons and motoneurons within the spinal cord. We systematically evaluated the neural recruitment during HF-SCS for several unique electrode designs and stimulation configurations to optimize activation of these neural elements. We then evaluated our predictions by testing two of these lead designs with in vivo canine experiments.
Our model results suggested that within physiological stimulation amplitudes, HF-SCS activates both axons in the ventrolateral funiculi (VLF) and inspiratory intercostal motoneurons. We used our model to predict a lead design to maximize HF-SCS activation of these neural targets. We evaluated this lead design via in vivo experiments, and our computational model predictions demonstrated excellent agreement with our experimental testing.
Our computational modeling and experimental results support the potential advantages of a lead design with longer contacts and larger edge-to-edge contact spacing to maximize inspiratory muscle activation during HF-SCS at the T2 spinal level. While these results need to be further validated in future studies, we believe that the results of this study will help improve the efficacy of HF-SCS technologies for inspiratory muscle pacing.
高频脊髓刺激(HF-SCS)是为依赖呼吸机的脊髓损伤患者提供自然有效的吸气肌起搏的潜在方法。实验数据表明,HF-SCS 通过脊髓途径诱发出膈神经和吸气肋间肌的生理激活。然而,激活阈值、激活程度以及最佳电极配置(即导联分离、接触间距和接触长度)来激活这些神经元件仍不清楚。因此,本研究的目的是使用计算建模方法研究 HF-SCS 对脊髓的直接影响,并优化电极设计和刺激参数。
我们开发了一种 HF-SCS 的计算机模型,该模型由两个主要组件组成:1)HF-SCS 过程中产生的电场的有限元模型,2)脊髓内轴突和运动神经元的多室电缆模型。我们系统地评估了几种独特的电极设计和刺激配置下 HF-SCS 期间的神经募集,以优化这些神经元件的激活。然后,我们通过在体内犬实验中测试其中两种导联设计来评估我们的预测。
我们的模型结果表明,在生理刺激幅度内,HF-SCS 会激活腹外侧索(VLF)中的轴突和吸气肋间运动神经元。我们使用我们的模型来预测一种导联设计,以最大限度地激活这些神经靶标。我们通过体内实验评估了这种导联设计,我们的计算模型预测与我们的实验测试结果非常吻合。
我们的计算建模和实验结果支持使用具有更长接触和更大边缘到边缘接触间距的导联设计的潜在优势,以最大限度地提高 T2 脊髓水平 HF-SCS 期间吸气肌的激活。虽然这些结果需要在未来的研究中进一步验证,但我们相信本研究的结果将有助于提高 HF-SCS 技术用于吸气肌起搏的疗效。