Toward Safety Protocols for Peripheral Nerve Stimulation (PNS): A Computational and Experimental Approach

Area of Science:

• Bioelectromagnetics
• Computational Neuroscience
• Biomedical Engineering

Background:

• Clinical applications of peripheral nerve stimulation (PNS) are expanding.
• There is a growing need for specific safety criteria for PNS.
• Current safety standards do not fully capture the effects of induced fields and currents on axons.

Purpose of the Study:

• To establish a novel safety criterion for PNS that accounts for induced electrical fields and currents on axons.
• To develop a predictive model for axonal damage in response to PNS.
• To create a safety threshold curve correlating stimulation parameters with potential nerve damage.

Main Methods:

• Utilized a machine learning and computational bio-electromagnetics modeling platform.
• Collected and segmented high-resolution images of rat sciatic nerves under varying stimulation intensities.
• Employed the Admittance Method-NEURON (AM-NEURON) platform to model nerves and calculate induced currents and charges.
• Correlated cellular-level morphological changes with electrical stimulation parameters.

Main Results:

• Developed machine learning tools for automatic classification of nerve morphology.
• Established a cellular-level correlation between nerve morphology changes and electrical stimulation.
• Determined thresholds of electrical parameters associated with axonal damage, such as maximum cell charge density.
• Generated a safety threshold curve for PNS based on experimental and computational data.

Conclusions:

• The proposed methodology successfully combines experimental data and computational modeling to create PNS safety criteria.
• The developed safety threshold curve provides a valuable tool for assessing the risk of axonal damage during PNS.
• This approach represents a significant step towards context-specific safety criteria for neurostimulation.