Carlos J Anaya1,2, Hans J Zander1,2, Robert D Graham1,2, Vishwanath Sankarasubramanian1,2, Scott F Lempka1,2,3. 1. Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA. 2. Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA. 3. Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA.
Abstract
OBJECTIVES: Spinal cord stimulation (SCS) for pain is typically implemented in an open-loop manner using parameters that remain largely unchanged. To improve the overall efficacy and consistency of SCS, one closed-loop approach proposes to use evoked compound action potentials (ECAPs) recorded from the SCS lead(s) as a feedback control signal to guide parameter selection. The goal of this study was to use a computational modeling approach to investigate the source of these ECAP recordings and technical and physiological factors that affect their composition. METHODS: We developed a computational model that coupled a finite element model of lower thoracic SCS with multicompartment models of sensory axons within the spinal cord. We used a reciprocity-based approach to calculate SCS-induced ECAPs recorded from the SCS lead. RESULTS: Our model ECAPs contained a triphasic, P1, N1, P2 morphology. The model P2-N1 amplitudes and conduction velocities agreed with previous experimental data from human subjects. Model results suggested that the ECAPs are dominated by the activation of axons with diameters 8.7-10.0 μm located in the dorsal aspect of the spinal cord. We also observed changes in the ECAP amplitude and shape due to the electrode location relative to the vertebrae and spinal cord. CONCLUSION: Our modeling results suggest that clinically effective SCS relies on the activation of numerous axons within a narrow fiber diameter range and that several factors affect the composition of the ECAP recordings. These results can improve how we interpret and implement these recordings in a potential closed-loop approach to SCS.
OBJECTIVES: Spinal cord stimulation (SCS) for pain is typically implemented in an open-loop manner using parameters that remain largely unchanged. To improve the overall efficacy and consistency of SCS, one closed-loop approach proposes to use evoked compound action potentials (ECAPs) recorded from the SCS lead(s) as a feedback control signal to guide parameter selection. The goal of this study was to use a computational modeling approach to investigate the source of these ECAP recordings and technical and physiological factors that affect their composition. METHODS: We developed a computational model that coupled a finite element model of lower thoracic SCS with multicompartment models of sensory axons within the spinal cord. We used a reciprocity-based approach to calculate SCS-induced ECAPs recorded from the SCS lead. RESULTS: Our model ECAPs contained a triphasic, P1, N1, P2 morphology. The model P2-N1 amplitudes and conduction velocities agreed with previous experimental data from human subjects. Model results suggested that the ECAPs are dominated by the activation of axons with diameters 8.7-10.0 μm located in the dorsal aspect of the spinal cord. We also observed changes in the ECAP amplitude and shape due to the electrode location relative to the vertebrae and spinal cord. CONCLUSION: Our modeling results suggest that clinically effective SCS relies on the activation of numerous axons within a narrow fiber diameter range and that several factors affect the composition of the ECAP recordings. These results can improve how we interpret and implement these recordings in a potential closed-loop approach to SCS.
Authors: Julie G Pilitsis; Krishnan V Chakravarthy; Andrew J Will; Karen C Trutnau; Kristin N Hageman; David A Dinsmoor; Leonid M Litvak Journal: Front Neurosci Date: 2021-07-12 Impact factor: 4.677