Abstract
Spinal cord stimulation (SCS) is a widely-used therapy for chronic pain management. Computational models provide a valuable tool to study the effects of SCS on the nervous system. However, it is critical that these models include sufficient detail to correlate model predictions with clinical effects, including patient-specific data. Therefore, in this study, we developed a patient-specific computer model for a patient undergoing SCS to treat neuropathic pain. The patient-specific model predicted sensory threshold estimates that were consistent with the corresponding clinical measurements. These results demonstrate the potential for patient-specific computer models to quantitatively describe the axonal response to SCS and to address scientific questions related to clinical SCS.
This work was supported by the National Institutes of Health (NIH R01 NS089530), Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, USA, and the Cleveland Clinic Research Program Committees, Cleveland, OH, USA. This research was supported in part through computational resources and services provided by Advanced Research Computing at the University of Michigan, Ann Arbor, MI, USA.
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Acknowledgments
S. F. Lempka would like to thank Fang Dong (Cleveland Clinic, Cleveland, OH, USA) for help developing the CT protocol, Stephen E. Jones (Cleveland Clinic) for assistance with image segmentation, and Kabilar Gunalan (Case Western Reserve University, Cleveland, OH, USA) for assistance with computer simulations.
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Lempka, S.F., Zander, H., Anaya, C.J., Wyant, A., Ozinga, J.G., Machado, A.G. (2019). Model-Based Analysis of Spinal Cord Stimulation for Chronic Pain. In: Masia, L., Micera, S., Akay, M., Pons, J. (eds) Converging Clinical and Engineering Research on Neurorehabilitation III. ICNR 2018. Biosystems & Biorobotics, vol 21. Springer, Cham. https://doi.org/10.1007/978-3-030-01845-0_8
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DOI: https://doi.org/10.1007/978-3-030-01845-0_8
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