FastField

FastField approximates electric fields and volumes of tissue activated (VTA) in deep brain stimulation (DBS) to enable rapid prediction of stimulation effects.

Key Features:

• Electric-field and VTA approximation: Approximates electric fields and volumes of tissue activated (VTA) in DBS.
• Superposition-based scaling: Implements scalable electric field approximations based on the principle of superposition.
• Activation models: Uses VTA activation models that explicitly consider pulse width and axon diameter.
• Computation speed: Performs individual simulations in approximately 0.2 seconds.
• Speed versus FEM: Achieves roughly 1000× speedup compared to finite element method (FEM)-based simulations.
• Accuracy benchmark: Delivers an average Dice overlap of 92% in benchmark tests, comparable to typical clinical data noise levels.
• Complex geometries and configurations: Handles complex geometries and diverse electrode configurations and stimulation settings.
• Rapid parameter tuning: Facilitates rapid parameter tuning and optimization studies through fast computation.

Scientific Applications:

• Optimization studies: Enables efficient optimization of stimulation parameters and electrode configurations via rapid simulations.
• Patient-specific DBS planning: Supports tailoring DBS therapies to individual patients by predicting outcomes for different electrode placements and settings.
• Network analyses: Provides electric field and VTA estimates usable for network analyses of DBS effects.
• Benchmarking and validation: Serves for benchmarking and validation of DBS models against FEM and clinical data.

Methodology:

Computational approach uses superposition-based electric field approximations coupled with VTA activation models that incorporate pulse width and axon diameter.