A systematic review of computational models for the design of spinal cord stimulation therapies: from neural circuits to patient-specific simulations.

Seventy years ago, Hodgkin and Huxley published the first mathematical model that described action potential generation, laying the foundation for modern computational neuroscience. Since then, the field has evolved enormously with studies spanning from basic neuroscience to clinical neuromodulation applications. Computer models for neuromodulation have evolved in complexity and personalization, advancing clinical practice and novel neurostimulation therapies, such as spinal cord stimulation (SCS). SCS is a widely used therapy to treat chronic pain with rapidly expanding indications, such as restoring motor function. In general, simulations dramatically contributed to improved lead designs, stimulation configurations, waveform parameters, and programming procedures, as well as provided insight into potential mechanisms of action of electrical stimulation. However, while practical applications of neural models are relentlessly increasing in number and complexity, it is reasonable to ask whether this observed increase in complexity is necessary for improved accuracy and ultimately clinical efficacy. To this aim, we performed a systematic literature review with a qualitative meta-synthesis of the evolution of computational models, with a focus on complexity, personalization, and the use of medical imaging to capture realistic anatomy. Our review showed that increased model complexity improved both mechanistic as well as translational studies. More specifically, it enabled the development of patient-specific models that can help transform clinical practice in SCS. Finally, we combined our results to provide clear guidelines for standardization and expansion of computational models for SCS. Abstract figure legend Evolution of computational models of spinal cord stimulation. The use of computational models of spinal cord stimulation is rapidly expanding in the field of neuromodulation. Here, we evaluated the evolution of such models from the 1980s to 2022. Thanks to the advancement of medical images and computational tools, models evolved from 2D models (left) to 3D models with limited realism and tissue compartments (middle), then, to MRI-based patient specific models with high realism and complex tissue compartments (right). Model figures from left to right were adapted from Coburn 13, Capogrosso et al. 9, and Rowald et al. 62, respectively, with permission. Abbreviation key: gm-gray matter, wm-white matter, csf-cerebrospinal fluid, edf-epidural fat, root-roots and rootlets. This article is protected by copyright. All rights reserved.