Computational analysis of kilohertz frequency spinal cord stimulation for chronic pain management.

Abstract

BACKGROUND Kilohertz frequency spinal cord stimulation (KHFSCS) is an emerging therapy for treating refractory neuropathic pain. Although KHFSCS has the potential to improve the lives of patients experiencing debilitating pain, its mechanisms of action are unknown and thus it is difficult to optimize its development. Therefore, the goal of this study was to use a computer model to investigate the direct effects of KHFSCS on specific neural elements of the spinal cord. METHODS This computer model consisted of two main components: (1) finite element models of the electric field generated by KHFSCS and (2) multicompartment cable models of axons in the spinal cord. Model analysis permitted systematic investigation into a number of variables (e.g., dorsal cerebrospinal fluid thickness, lead location, fiber collateralization, and fiber size) and their corresponding effects on excitation and conduction block thresholds during KHFSCS. RESULTS The results of this study suggest that direct excitation of large-diameter dorsal column or dorsal root fibers require high stimulation amplitudes that are at the upper end or outside of the range used in clinical KHFSCS (i.e., 0.5 to 5 mA). Conduction block was only possible within the clinical range for a thin dorsal cerebrospinal fluid layer. CONCLUSIONS These results suggest that clinical KHFSCS may not function through direct activation or conduction block of dorsal column or dorsal root fibers. Although these results should be validated with further studies, the authors propose that additional concepts and/or alternative hypotheses should be considered when examining the pain relief mechanisms of KHFSCS.

DOI: 10.1097/ALN.0000000000000649

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Cite this paper

@article{Lempka2015ComputationalAO, title={Computational analysis of kilohertz frequency spinal cord stimulation for chronic pain management.}, author={Scott Lempka and Cameron C. McIntyre and Kevin L. Kilgore and Andre G. Machado}, journal={Anesthesiology}, year={2015}, volume={122 6}, pages={1362-76} }