Characterizing the Effects of SCS Through a Combination of Computer and Experimental Models Across Species

Introduction: Spinal cord stimulation (SCS) is used for managing intractable chronic pain. While SCS may be effective in some patients, it is not effective in all and may lose efficacy over time. Many preclinical SCS studies have investigated its mechanisms of action; however, there are gross anatomical differences across species, leading to improper scaling of stimulation parameters between preclinical and clinical conditions. To address these scaling issues, we utilized a combined experimental and computational modeling approach to help translate preclinical experimental findings to clinical conditions and improve our understanding of the neuromodulatory effects of SCS.

Methods: We delivered epidural SCS to the low thoracic spinal cord in Sprague-Dawley rats and recorded evoked compound action potentials (ECAPs) via rostral electrodes. We applied symmetric biphasic square-wave stimulation, varying pulse width (50-300 µs) and frequency (2-10,000 Hz). We then employed a hybrid computational modeling approach, utilizing finite element method models to calculate the potential fields generated by SCS and multicompartment axon models to simulate the corresponding neural response and ECAPs. We utilized this approach in a computational model that replicated our preclinical experiments and in a human-scale computational model to simulate clinical conditions.

Results: Our rat-scale computational model showed strong agreement between experimental and theoretical ECAP recordings, validating its accuracy in predicting neural recruitment. The rat computational model was able to correctly predict experimental ECAP thresholds and conduction velocities, as well as reproduce experimental trends in ECAP amplitude as a function of pulse width and pulse frequency. We then used our human-scale computational model to estimate the electric field strength generated within the spinal cord at clinical stimulation amplitudes (e.g., 1 mA). Finally, we used our rat computational model to estimate the stimulation amplitudes needed to mimic clinical field strengths in rat experiments. This analysis revealed a ~1% scaling ratio (e.g., clinical SCS with 1 mA could be mimicked in preclinical experiments using a stimulation amplitude of 0.01 mA).

Conclusion: While our findings are specific to our experimental design, they suggest many prior studies utilized stimulation parameters and electrode configurations that lack clinical relevance. To enhance translational value and mechanistic insights into SCS pain therapy, preclinical studies should prioritize replicating clinical conditions and neural recruitment levels. Proper scaling of stimulation parameters between preclinical and clinical scales will improve our understanding of SCS and accelerate optimized therapies for improved patient outcomes.