Computational modeling of paresthesia generated by SCS using a percutaneous lead: a proof-of-concept theoretical model based on an arbitrary somatotopic distribution

<i>Objectives</i>.Chronic pain affects over two billion people worldwide, significantly reducing quality of life and placing a substantial burden on healthcare systems and society. Neuropathic painoriginates from lesions of the central or peripheral nervous system. Despite pharmacological, surgical and paramedical management, many patients continue experiencing persistent pain. Epidural Spinal Cord Stimulation (SCS) has become an effective alternative treatment for neuropathic pain. That said, SCS efficacy is dependent on many parameters, including optimized spatial targeting based on paresthesia generated by chosen and tuned SCS. In this context, iterative programming designed to optimize targeting and pain relief puts a major burden on health-care professionals. The leveraging of FEM and other computational techniques would enhance understanding of SCS mechanisms, optimize parameter selection, and ultimately improve patient outcomes.<i>Approach</i>. In this work, we present parametrizable computational model that facilitates the study of computed paresthesia. This model used the typical workflow of two-step simulation often employed for electrical stimulation of neural structures. First, the electrical field generated within the spinal cord and its surroundings was computed using the Finite-Element Method (FEM). The effects this electric field had on axons were then assessed with Ordinary Differential Equations (ODEs). The geometry of this model was based on a section of the PAM50 template of the spinal cord and its surroundings. Somatotopy of the spinal cord is explicitly represented by the fiber's trajectories. A<i>β</i>myelinated fibers of the dorsal columns and roots are modelled using the McIntyre-Richardson-Grill (MRG) double cable model.<i>Main results.</i>The computational model produced paresthesia maps which generally followed expected projections in terms of lead laterality and rostro-caudal placement in paresthesia. Some interesting effects of rostro-caudal lead placement ata vertebral level were also observed and will be discussed.<i>Significance</i>. The computed paresthesia maps, which can be directly correlated to felt or measured paresthesia maps, represent a step towards clinical validation of in silico computational models of SCS.

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Journal
Biomedical Physics & Engineering Express
Published
2026-03-05
DOI
https://doi.org/10.1088/2057-1976/ae4df4
Primary Topic
Pain Management and Treatment
Type
article
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article

Computational modeling of paresthesia generated by SCS using a percutaneous lead: a proof-of-concept theoretical model based on an arbitrary somatotopic distribution

Michel Rochette, Arnaud Germaneau, Tom Le Tutour, Maxime Billot et al.
Biomedical Physics & Engineering Express
Pain Management and Treatment
article

Computational modeling of paresthesia generated by SCS using a percutaneous lead: a proof-of-concept theoretical model based on an arbitrary somatotopic distribution

Michel Rochette, Arnaud Germaneau, Tom Le Tutour, Maxime Billot, Karim El Houari, Philippe Rigoard
article en

Abstract

<i>Objectives</i>.Chronic pain affects over two billion people worldwide, significantly reducing quality of life and placing a substantial burden on healthcare systems and society. Neuropathic painoriginates from lesions of the central or peripheral nervous system. Despite pharmacological, surgical and paramedical management, many patients continue experiencing persistent pain. Epidural Spinal Cord Stimulation (SCS) has become an effective alternative treatment for neuropathic pain. That said, SCS efficacy is dependent on many parameters, including optimized spatial targeting based on paresthesia generated by chosen and tuned SCS. In this context, iterative programming designed to optimize targeting and pain relief puts a major burden on health-care professionals. The leveraging of FEM and other computational techniques would enhance understanding of SCS mechanisms, optimize parameter selection, and ultimately improve patient outcomes.<i>Approach</i>. In this work, we present parametrizable computational model that facilitates the study of computed paresthesia. This model used the typical workflow of two-step simulation often employed for electrical stimulation of neural structures. First, the electrical field generated within the spinal cord and its surroundings was computed using the Finite-Element Method (FEM). The effects this electric field had on axons were then assessed with Ordinary Differential Equations (ODEs). The geometry of this model was based on a section of the PAM50 template of the spinal cord and its surroundings. Somatotopy of the spinal cord is explicitly represented by the fiber's trajectories. A<i>β</i>myelinated fibers of the dorsal columns and roots are modelled using the McIntyre-Richardson-Grill (MRG) double cable model.<i>Main results.</i>The computational model produced paresthesia maps which generally followed expected projections in terms of lead laterality and rostro-caudal placement in paresthesia. Some interesting effects of rostro-caudal lead placement ata vertebral level were also observed and will be discussed.<i>Significance</i>. The computed paresthesia maps, which can be directly correlated to felt or measured paresthesia maps, represent a step towards clinical validation of in silico computational models of SCS.

Biomedical Physics & Engineering ExpressVol. 12(2)
Université de Tours (FR), Centre National de la Recherche Scientifique (FR), Institut Pprime (FR), Université de Poitiers (FR), Centre Hospitalier Universitaire de Poitiers (FR), Predict (France) (FR), Ansys (France) (FR)
Openalex Percentile: Top 35%
Pain Management and Treatment
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