Computational modeling of dorsal root ganglion stimulation using an Injectrode.

Area of Science:

• Neuromodulation
• Biomedical Engineering
• Computational Neuroscience

Background:

• Minimally invasive neuromodulation offers a low-risk approach for electrical stimulation.
• The Injectrode, a flexible microcoil electrode, is designed for dorsal root ganglion (DRG) stimulation.
• Transcutaneous electrical stimulation (TES) effectiveness depends on system geometry.

Purpose of the Study:

• To investigate how Injectrode system design parameters influence charge delivery and neural activation.
• To analyze the impact of Injectrode size and orientation on neural activation thresholds.
• To determine optimal configurations for effective DRG stimulation.

Main Methods:

• Hybrid computational modeling using finite element method (FEM) for DRG stimulation.
• Multi-compartment models of DRG neurons to simulate neural responses.
• Analysis of potential distribution and neural activation thresholds under various stimulation parameters.

Main Results:

• Injectrode system predominantly activates large-diameter afferents (Aβ-fibers).
• Activation thresholds are dependent on Injectrode surface area.
• Increased surface area expands the therapeutic margin by reducing charge density and delaying Aδ-fiber activation.

Conclusions:

• The Injectrode is a viable technology for minimally invasive DRG neuromodulation.
• Larger Injectrode surface areas enhance the therapeutic window for selective Aβ-fiber activation.
• Design optimization is crucial for maximizing therapeutic benefit and minimizing off-target effects.