Computational approaches to optimize spinal cord stimulation for chronic pain
Spinal cord stimulation (SCS) is a prevalent neuromodulation therapy for neuropathic painthat is refractory to conventional treatments. SCS first emerged in the 1960s as a direct clinical application of the gate control theory of pain. However, after decades of clinical use and dramatic technological improvements, SCS still achieves limited success. To help address these limited outcomes, several exciting new forms of SCS are making their way into the clinic. However, we still do not understand how SCS relieves pain and this knowledge gap will continue to limit the success of SCS technologies. Due to the complexities of chronic pain, it is unlikely that clinical and preclinical investigations alone will be able to uncover the therapeutic mechanisms of SCS. We propose that solving this problem requires coupling clinical and experimental measurements with detailed computational models. Computational models provide a valuable tool to investigate physiological and technical factors related to neurostimulation therapies. These computational tools can improve our scientific understanding of neurostimulation for chronic pain and provide scientific guidance to individualize and optimize several components of these neurostimulation technologies.
Scott Lempka, PhD, was born in Lincoln, Nebraska in 1982. Scott earned the B.S. degree in Biomedical Engineering from Saint Louis University in 2004 and the Ph.D. degree in Biomedical Engineering from Case Western Reserve University in 2010. His dissertation work focused on the use of computational and experimental techniques to characterize the interface between neural stimulation and recording electrodes and the surrounding tissue. He performed his postdoctoral training at the Cleveland Clinic and the Louis Stokes Cleveland VAs Medical Center in the area of neurostimulation for chronic pain management. In 2017, Dr. Lempka moved to the University of Michigan in Ann Arbor, MI. Dr. Lempka is currently an Assistant Professor in the Department of Biomedical Engineering and the Director of the Neuromodulation Laboratory. The Neuromodulation Lab implements engineering approaches, such as computational modeling, to study the mechanism of action of clinical neuromodulation therapies for chronic pain management and other neurological disorders. The fundamental goal of the research program is to innovate future neuromostimulation technologies that dramatically improve patients’ lives.