Simulation of the Electrical Field in Equine Larynx to Optimize Functional Electrical Stimulation in Denervated Musculus Cricoarythenoideus Dorsalis.

This study is developing a simulation model to optimize the effects of functional electrical stimulation therapy for treating Recurrent Laryngeal Neuropathy (a horse muscle disorder). The model, built from CT scans and using a finite difference method, can simulate various electrode and conductivity configurations, providing a visualization of voltage distributions and a guide for improving therapy.

Introduction

• The research focuses on how to optimize Functional Electrical Stimulation (FES) – a therapy used to treat Recurrent Laryngeal Neuropathy (RLN) – a neuropathic disorder in horses.
• The optimization is accomplished by effectively distributing the electrical field to stimulate muscle and nerve cells correctly.
• The current method of optimization involves implanting quadripolar electrodes in the musculus cricoarythenoideus dorsalis (CAD) muscle of the horse and testing different configurations until an optimal result is obtained.

Building the Simulation Model

• The study aims to improve on the current optimization techniques by developing a simulation model that can predict the best way to activate the CAD muscle.
• This model is built using data from CT scans allowing its internal structure to correspond to actual laryngeal anatomy.
• The model uses a method known as the finite difference method, creating a 3D network of voxels (3D pixels), each of which has an electrical conductivity value representative of the type of tissue it represents in the real world.

Model Validation

• To verify the model, the 3D electrical potential distribution of an actual larynx is measured while being positioned in an electrolytic tray, a device that stimulates electrical conductivity.
• The measured results are then compared to the calculated results from the simulation model, ensuring accuracy and reliability of the model.

Preliminary Results and Further Investigation

• Initial outcomes reveal that changing the electrode configuration and conductivity can lead to significantly different voltage distributions.
• These voltage distributions can be clearly presented through equipotential lines superimposed on CT slices, which are visualized using a Matlab graphical user interface.
• The model also enables the visualization and calculation of potential voltage distribution along estimated muscle fiber paths.
• For further research and to improve the optimization process, the paths of actual nerve or denervated muscle fibers need to be properly defined and mapped in relation to the potential distribution and the CT-data.