Realistic anatomically detailed open-source spinal cord stimulation (RADO-SCS) model

Abstract

Objective. Computational current flow models of spinal cord stimulation (SCS) are widely used in device development, clinical trial design, and patient programming. Proprietary models of varied sophistication have been developed. An open-source model with state-of-the-art precision would serve as a standard for SCS simulation. Approach. We developed a sophisticated SCS modeling platform, named Realistic Anatomically Detailed Open-Source Spinal Cord Stimulation (RADO-SCS) model. This platform consists of realistic and detailed spinal cord and ancillary tissues anatomy derived based on prior imaging and cadaveric studies. In our finite element model of the T9-T11 spine levels, we represented the following tissues: vertebrae, intervertebral disc, epidural space, epidural space vasculature, dura mater, dural sac, intraforaminal tissue, cerebrospinal fluid (CSF), whitematter, spinal cord vasculature, Lissauer’s tract, gray matter, dorsal and ventral roots and rootlets, dorsal root ganglion (DRG), sympathetic chain (trunk and ganglion), thoracic aorta and its branching, peripheral vasculature, and soft tissues (thorax). As an exemplary application to illustrate the model workflow, we simulated a bipolar SCS montage and calculated the corresponding activation thresholds for individual axons populating the spinal cord. Main results. RADO-SCS provides state-of-the-art precision across 19 tissue compartments. The resulting model calculations of the electric fields generated in the white-matter and gray matter, and the axonal activation thresholds are broadly consistent with prior simulations. Significance. The RADO-SCS can be used to simulate any SCS approach with both unprecedented resolution (precision) and transparency (reproducibility). Freely-available online, the RADO-SCS will be updated continuously with version control.

A Call to Action Toward Optimizing the Electrical Dose Received by Neural Targets in Spinal Cord Stimulation Therapy for Neuropathic Pain

“…In addition, the stimulation-on vs -off ratio, CSF thickness and other complex spinal anatomy, circulation of CSF, lead encapsulation, lead positioning, and electrode configurations affect how much stimulus is delivered to the spinal target. 21,[59][60][61][62][63][64] Changes in any one variable may affect overall dosing. An anatomically realistic computational model of SCS has been developed and can help researchers understand the interactions of complex tissue compartments in terms of impedance.…”

“…An anatomically realistic computational model of SCS has been developed and can help researchers understand the interactions of complex tissue compartments in terms of impedance. 62 It has also been noted that actual stimulation output may be lower than the as-programmed stimulation: 37 a “governor” function established by regulatory requirements to maintain safe levels of electrical stimulation. If unaware of this, clinicians could dramatically misinterpret the implications of their programming choices.…”

Non-invasive brain-spine interface: Continuous control of trans-spinal magnetic stimulation using EEG

“…on the excitability of spinal neural networks should also be disclosed. Computational modelling might be a key tool to understand the ongoing mechanisms involved in spinal neuromodulation due to ts-MS and to optimize interventions based on spinal stimulation for functional recovery ( Formento et al, 2018 ; Khadka et al, 2020 ; Greiner et al, 2021 ). Recent approaches for EEG decoding, based on advanced machine learning algorithms, have received substantial attention and could also be implemented for designing and training classifiers that could considerably boost the performance of closed-loop systems ( Schirrmeister et al, 2017 ; Saeidi et al, 2021 ).…”

Non-invasive brain-spine interface: continuous brain control of trans-spinal magnetic stimulation using EEG

“…on the excitability of spinal neural networks should also be disclosed in future investigations. Computational modelling might be a key tool to understand the ongoing mechanisms involved in spinal neuromodulation due to ts-MS in order to optimize interventions based on spinal cord stimulation that enhance functional recovery (Formento et al, 2018;Greiner et al, 2020;Khadka et al, 2020).…”