A systematic review of computational models for the design of spinal cord stimulation therapies: from neural circuits to patient-specific simulations
Liang, Lucy; Damiani, Arianna; Del Brocco, Matteo; Rogers, Evan R.; Jantz, Maria K.; Fisher, Lee E.; Gaunt, Robert A.; Capogrosso, Marco; Lempka, Scott F.; Pirondini, Elvira
2023-08
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Liang, Lucy; Damiani, Arianna; Del Brocco, Matteo; Rogers, Evan R.; Jantz, Maria K.; Fisher, Lee E.; Gaunt, Robert A.; Capogrosso, Marco; Lempka, Scott F.; Pirondini, Elvira (2023). "A systematic review of computational models for the design of spinal cord stimulation therapies: from neural circuits to patient-specific simulations." The Journal of Physiology 601(15): 3103-3121.
Abstract
Seventy years ago, Hodgkin and Huxley published the first mathematical model to describe 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 applications for neuromodulation. Computer models of neuromodulation have evolved in complexity and personalization, advancing clinical practice and novel neurostimulation therapies, such as spinal cord stimulation. Spinal cord stimulation is a therapy widely used to treat chronic pain, with rapidly expanding indications, such as restoring motor function. In general, simulations contributed dramatically to improve lead designs, stimulation configurations, waveform parameters and programming procedures and provided insight into potential mechanisms of action of electrical stimulation. Although the implementation 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, for clinical efficacy. With this aim, we performed a systematic literature review and 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 and personalization improved both mechanistic and translational studies. More specifically, the use of medical imaging enabled the development of patient-specific models that can help to transform clinical practice in spinal cord stimulation. Finally, we combined our results to provide clear guidelines for standardization and expansion of computational models for spinal cord stimulation.Abstract figure legend Evolution of computational models of spinal cord stimulation. The use of computational models of spinal cord stimulation is expanding rapidly 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 have evolved from two-dimensional (2D) models (left) to three-dimensional (3D) models with limited realism and tissue compartments (middle), then to magnetic resonance imaging (MRI)-based patient-specific models with high realism and complex tissue compartments (right). Model figures were adapted from Capogrosso et al. (2013), Coburn (1980), and Rowald et al. (2022), with permission. Abbreviations: csf, cerebrospinal fluid; edf, epidural fat; gm, grey matter; root, roots and rootlets; wm, white matter.Publisher
Springer Wiley Periodicals, Inc.
ISSN
0022-3751 1469-7793
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