Simulation study of spinal cord stimulation evoked compound action potential_Journal of Biomedical Engineering

Authors：

ZHANG Guanghao ^1,2 , ZHANG Cheng ^1,2 , WU Changzhe ¹ ,  HUO Xiaolin ^1,2

1. Beijing Key Laboratory of Bioelectromagnetism, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, P.R.China;
2. School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, P.R.China;

Corresponding author：

HUO Xiaolin, Email: huoxl@mail.iee.ac.cn

Keywords：

spinal cord stimulation; compartment model; finite element simulation model; close loop simulation; evoked compound action potential

DOI：

10.7507/1001-5515.202007016

Video：

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Spinal cord stimulation (SCS) for pain is usually implanted as an open loop system using unchanged parameters. To avoid the under and over stimulation caused by lead migration, evoked compound action potentials (ECAP) is used as feedback signal to change the stimulating parameters. This study established a simulation model of ECAP recording to investigate the relationship between ECAP component and dorsal column (DC) fiber recruitment. Finite element model of SCS and multi-compartment model of sensory fiber were coupled to calculate the single fiber action potential (SFAP) caused by single fiber in different spinal cord regions. The synthetized ECAP, superimposition of SFAP, could be considered as an index of DC fiber excitation degree, because the position of crests and amplitude of ECAP corresponds to different fiber diameters. When 10% or less DC fibers were excited, the crests corresponded to fibers with large diameters. When 20% or more DC fibers were excited, ECAP showed a slow conduction crest, which corresponded to fibers with small diameters. The amplitude of this slow conduction crest increased as the stimulating intensity increased while the amplitude of the fast conduction crest almost remained unchanged. Therefore, the simulated ECAP signal in this paper could be used to evaluate the degree of excitation of DC fibers. This SCS-ECAP model may provide theoretical basis for future clinical application of close loop SCS base on ECAP.

Citation： ZHANG Guanghao, ZHANG Cheng, WU Changzhe, HUO Xiaolin. Simulation study of spinal cord stimulation evoked compound action potential. Journal of Biomedical Engineering, 2021, 38(2): 232-240. doi: 10.7507/1001-5515.202007016 Copy

1.	陈旭辉, 张玥, 张传汉. 脊髓电刺激在慢性疼痛中的应用和研究进展. 中国疼痛医学杂志, 2017, 23(12): 931-934.
2.	Melzack R, Wall P D. Pain mechanisms - a new theory. Science, 1965, 150(3699): 971-979.
3.	Schultz D M, Webster L, Kosek P, et al. Sensor-driven position-adaptive spinal cord stimulation for chronic pain. Pain Physician, 2012, 15(1): 1-12.
4.	Ross E, Abejon D. Improving patient experience with spinal cord stimulation: implications of position-related changes in neurostimulation. Neuromodulation, 2014, 17(S1): 36-41.
5.	Parker J L, Karantonis D M, Single P S, et al. Compound action potentials recorded in the human spinal cord during neurostimulation for pain relief. Pain, 2012, 153(3): 593-601.
6.	Parker J L, Karantonis D M, Single P S, et al. Electrically evoked compound action potentials recorded from the sheep spinal cord. Neuromodulation, 2013, 16(4): 295-303.
7.	Ertekin C. Studies on human evoked electrospinogram. 1. The origin of segmental evoked-potentials. Acta Neurol Scand, 1976, 53(1): 3-20.
8.	Ertekin C. Studies on human evoked electrospinogram. 2. The conduction-velocity along dorsal funiculus. Acta Neurol Scand, 1976, 53(1): 21-38.
9.	Maruyama Y, Shimoji K, Shimizu H, et al. Human spinal-cord potentials-evoked by different sources of stimulation and conduction velocities along the cord. J Neurophysiol, 1982, 48(5): 1098-1107.
10.	Mekhail N, Levy R M, Deer T R, et al. Long-term safety and efficacy of closed-loop spinal cord stimulation to treat chronic back and leg pain (Evoke): a double-blind, randomised, controlled trial. Lancet Neurol, 2020, 19(2): 123-134.
11.	Russo M, Cousins M J, Brooker C, et al. Effective relief of pain and associated symptoms with closed-loop spinal cord stimulation system: preliminary results of the avalon study. Neuromodulation, 2018, 21(1): 38-47.
12.	Hodgkin A L, Huxley A F. A quantitative description of membrane current and its application to conduction and excitation in nerve. J Physiol, 1952, 117(4): 500-544.
13.	McNeal D R. Analysis of a model for excitation of myelinated nerve. IEEE Trans Biomed Eng, 1976, 23(4): 329-337.
14.	Hines M L, Davison A P, Muller E. NEURON and Python. Front Neuroinform, 2019, 3: 1.
15.	Holsheimer J. Which neuronal elements are activated directly by spinal cord stimulation. Neuromodulation, 2002, 5(1): 25-31.
16.	Lee D, Hershey B, Bradley K, et al. Predicted effects of pulse width programming in spinal cord stimulation: a mathematical modeling study. Med Biol Eng Comput, 2011, 49(7): 765-774.
17.	Laird J H, Parker J L. A model of evoked potentials in spinal cord stimulation. Annu Int Conf IEEE Eng Med Biol Soc, 2013, 2013: 6555-6558.
18.	Lempka S F, McIntyre C C, Kilgore K L, et al. Computational analysis of kilohertz frequency spinal cord stimulation for chronic pain management. Anesthesiology, 2015, 122(6): 1362-1376.
19.	Parker J L, Laird-Wah J, Cousins M J. Comparison of a simple model of dorsal column axons with the electrically evoked compound action potential. Bioelectron Med, 2018, 1(2): 117-130.
20.	Durá J L, Solanes C, Andrés J, et al. Computational study of the effect of electrode polarity on neural activation related to paresthesia coverage in spinal cord stimulation therapy. Neuromodulation, 2019, 22(3): 269-279.
21.	Sheldon B, Staudt M D, Williams L, et al. Spinal cord stimulation programming: a crash course. Neurosurg Rev, 2020. DOI: 10.1007/s10143-020-01299-y.
22.	Fradet L, Arnoux P J, Ranjeva J P, et al. Morphometrics of the entire human spinal cord and spinal canal measured from in vivo high-resolution anatomical magnetic resonance imaging. Spine, 2014, 39(4): E262-E269.
23.	Feirabend H K P, Choufoer H, Ploeger S, et al. Morphometry of human superficial dorsal and dorsolateral column fibres: significance to spinal cord stimulation. Brain, 2002, 125(5): 1137-1149.
24.	Reina M A, Lopez-Garcia A, Dittmann M, et al. Structural analysis of the thickness of human dura mater with scanning electron microscopy. Rev Esp Anestesiol Reanim, 1996, 43(4): 135-137.
25.	Westbrook J L, Renowden S A, Carrie L E S. Study of the anatomy of the extradural region using magnetic-resonance-imaging. Br J Anaesth, 1993, 71(4): 495-498.
26.	Struijk J J, Holsheimer J, Boom H B K. Excitation of dorsal-root fibers in spinal-cord stimulation - a theoretical-study. IEEE Trans Biomed Eng, 1993, 40(7): 632-639.
27.	Ladenbauer J, Minassian K, Hofstoetter U S, et al. Stimulation of the human lumbar spinal cord with implanted and surface electrodes: a computer simulation study. IEEE Trans Neural Syst Rehabil Eng, 2010, 18(6): 637-645.
28.	Lempka S F, Zander H J, Anaya C J, et al. Patient-specific analysis of neural activation during spinal cord stimulation for pain. Neuromodulation, 2020, 23(5): 572-593.
29.	McIntyre C C, Richardson A G, Grill W M. Modeling the excitability of mammalian nerve fibers: Influence of afterpotentials on the recovery cycle. J Neurophysiol, 2002, 87(2): 995-1006.
30.	Warman E N, Grill W M, Durand D. Modeling the effects of electric fields on nerve fibers: Determination of excitation thresholds. IEEE Trans Biomed Eng, 1992, 39(12): 1244-1254.
31.	Anaya C J, Zander H J, Graham R D, et al. Evoked potentials recorded from the spinal cord during neurostimulation for pain: a computational modeling study. Neuromodulation, 2020, 23(1): 64-73.
32.	Capogrosso M. A computational model for epidural electrical stimulation of spinal sensorimotor circuits. J Neurosci, 2013, 33(49): 19326-19340.
33.	Howell B, Lad S P, Grill W M. Evaluation of intradural stimulation efficiency and selectivity in a computational model of spinal cord stimulation. PLoS One, 2014, 9(12): e114938.
34.	He J, Barolat G, Ketcik B. Stimulation usage range for chronic pain management. Analgesia, 1994, 1(1): 75-80.
35.	Gaines J L, Finn K E, Slopsema J P, et al. A model of motor and sensory axon activation in the median nerve using surface electrical stimulation. J Comput Neurosci, 2018, 45(1): 29-43.
36.	Graham R D, Bruns T M, Duan B, et al. Dorsal root ganglion stimulation for chronic pain modulates A beta-fiber activity but not C-fiber activity: A computational modeling study. Clin Neurophysiol, 2019, 130(6): 941-951.

1. 陈旭辉, 张玥, 张传汉. 脊髓电刺激在慢性疼痛中的应用和研究进展. 中国疼痛医学杂志, 2017, 23(12): 931-934.
2. Melzack R, Wall P D. Pain mechanisms - a new theory. Science, 1965, 150(3699): 971-979.
3. Schultz D M, Webster L, Kosek P, et al. Sensor-driven position-adaptive spinal cord stimulation for chronic pain. Pain Physician, 2012, 15(1): 1-12.
4. Ross E, Abejon D. Improving patient experience with spinal cord stimulation: implications of position-related changes in neurostimulation. Neuromodulation, 2014, 17(S1): 36-41.
5. Parker J L, Karantonis D M, Single P S, et al. Compound action potentials recorded in the human spinal cord during neurostimulation for pain relief. Pain, 2012, 153(3): 593-601.
6. Parker J L, Karantonis D M, Single P S, et al. Electrically evoked compound action potentials recorded from the sheep spinal cord. Neuromodulation, 2013, 16(4): 295-303.
7. Ertekin C. Studies on human evoked electrospinogram. 1. The origin of segmental evoked-potentials. Acta Neurol Scand, 1976, 53(1): 3-20.
8. Ertekin C. Studies on human evoked electrospinogram. 2. The conduction-velocity along dorsal funiculus. Acta Neurol Scand, 1976, 53(1): 21-38.
9. Maruyama Y, Shimoji K, Shimizu H, et al. Human spinal-cord potentials-evoked by different sources of stimulation and conduction velocities along the cord. J Neurophysiol, 1982, 48(5): 1098-1107.
10. Mekhail N, Levy R M, Deer T R, et al. Long-term safety and efficacy of closed-loop spinal cord stimulation to treat chronic back and leg pain (Evoke): a double-blind, randomised, controlled trial. Lancet Neurol, 2020, 19(2): 123-134.
11. Russo M, Cousins M J, Brooker C, et al. Effective relief of pain and associated symptoms with closed-loop spinal cord stimulation system: preliminary results of the avalon study. Neuromodulation, 2018, 21(1): 38-47.
12. Hodgkin A L, Huxley A F. A quantitative description of membrane current and its application to conduction and excitation in nerve. J Physiol, 1952, 117(4): 500-544.
13. McNeal D R. Analysis of a model for excitation of myelinated nerve. IEEE Trans Biomed Eng, 1976, 23(4): 329-337.
14. Hines M L, Davison A P, Muller E. NEURON and Python. Front Neuroinform, 2019, 3: 1.
15. Holsheimer J. Which neuronal elements are activated directly by spinal cord stimulation. Neuromodulation, 2002, 5(1): 25-31.
16. Lee D, Hershey B, Bradley K, et al. Predicted effects of pulse width programming in spinal cord stimulation: a mathematical modeling study. Med Biol Eng Comput, 2011, 49(7): 765-774.
17. Laird J H, Parker J L. A model of evoked potentials in spinal cord stimulation. Annu Int Conf IEEE Eng Med Biol Soc, 2013, 2013: 6555-6558.
18. Lempka S F, McIntyre C C, Kilgore K L, et al. Computational analysis of kilohertz frequency spinal cord stimulation for chronic pain management. Anesthesiology, 2015, 122(6): 1362-1376.
19. Parker J L, Laird-Wah J, Cousins M J. Comparison of a simple model of dorsal column axons with the electrically evoked compound action potential. Bioelectron Med, 2018, 1(2): 117-130.
20. Durá J L, Solanes C, Andrés J, et al. Computational study of the effect of electrode polarity on neural activation related to paresthesia coverage in spinal cord stimulation therapy. Neuromodulation, 2019, 22(3): 269-279.
21. Sheldon B, Staudt M D, Williams L, et al. Spinal cord stimulation programming: a crash course. Neurosurg Rev, 2020. DOI: 10.1007/s10143-020-01299-y.
22. Fradet L, Arnoux P J, Ranjeva J P, et al. Morphometrics of the entire human spinal cord and spinal canal measured from in vivo high-resolution anatomical magnetic resonance imaging. Spine, 2014, 39(4): E262-E269.
23. Feirabend H K P, Choufoer H, Ploeger S, et al. Morphometry of human superficial dorsal and dorsolateral column fibres: significance to spinal cord stimulation. Brain, 2002, 125(5): 1137-1149.
24. Reina M A, Lopez-Garcia A, Dittmann M, et al. Structural analysis of the thickness of human dura mater with scanning electron microscopy. Rev Esp Anestesiol Reanim, 1996, 43(4): 135-137.
25. Westbrook J L, Renowden S A, Carrie L E S. Study of the anatomy of the extradural region using magnetic-resonance-imaging. Br J Anaesth, 1993, 71(4): 495-498.
26. Struijk J J, Holsheimer J, Boom H B K. Excitation of dorsal-root fibers in spinal-cord stimulation - a theoretical-study. IEEE Trans Biomed Eng, 1993, 40(7): 632-639.
27. Ladenbauer J, Minassian K, Hofstoetter U S, et al. Stimulation of the human lumbar spinal cord with implanted and surface electrodes: a computer simulation study. IEEE Trans Neural Syst Rehabil Eng, 2010, 18(6): 637-645.
28. Lempka S F, Zander H J, Anaya C J, et al. Patient-specific analysis of neural activation during spinal cord stimulation for pain. Neuromodulation, 2020, 23(5): 572-593.
29. McIntyre C C, Richardson A G, Grill W M. Modeling the excitability of mammalian nerve fibers: Influence of afterpotentials on the recovery cycle. J Neurophysiol, 2002, 87(2): 995-1006.
30. Warman E N, Grill W M, Durand D. Modeling the effects of electric fields on nerve fibers: Determination of excitation thresholds. IEEE Trans Biomed Eng, 1992, 39(12): 1244-1254.
31. Anaya C J, Zander H J, Graham R D, et al. Evoked potentials recorded from the spinal cord during neurostimulation for pain: a computational modeling study. Neuromodulation, 2020, 23(1): 64-73.
32. Capogrosso M. A computational model for epidural electrical stimulation of spinal sensorimotor circuits. J Neurosci, 2013, 33(49): 19326-19340.
33. Howell B, Lad S P, Grill W M. Evaluation of intradural stimulation efficiency and selectivity in a computational model of spinal cord stimulation. PLoS One, 2014, 9(12): e114938.
34. He J, Barolat G, Ketcik B. Stimulation usage range for chronic pain management. Analgesia, 1994, 1(1): 75-80.
35. Gaines J L, Finn K E, Slopsema J P, et al. A model of motor and sensory axon activation in the median nerve using surface electrical stimulation. J Comput Neurosci, 2018, 45(1): 29-43.
36. Graham R D, Bruns T M, Duan B, et al. Dorsal root ganglion stimulation for chronic pain modulates A beta-fiber activity but not C-fiber activity: A computational modeling study. Clin Neurophysiol, 2019, 130(6): 941-951.

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Simulation study of spinal cord stimulation evoked compound action potential

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