Fast computational E-field dosimetry for transcranial magnetic stimulation using adaptive cross approximation and...

Area of Science:

• Biophysics
• Computational Neuroscience
• Medical Imaging

Background:

• Transcranial Magnetic Stimulation (TMS) is a non-invasive brain stimulation technique.
• Accurate electric field (E-field) modeling is crucial for TMS applications.
• Current E-field solvers are computationally intensive, limiting their use in real-time applications.

Purpose of the Study:

• To develop a computationally efficient E-field solver for TMS.
• To enable rapid evaluation of E-field distributions for various coil placements.
• To improve the practicality of TMS computational dosimetry.

Main Methods:

• Developed a two-stage fast E-field solver utilizing adaptive cross approximation (ACA).
• Pre-processing stage approximates the mapping between coil placement and ROI E-field distribution.
• Second stage rapidly determines ROI E-field distribution from the approximated mapping.

Main Results:

• The ACA-based solver achieves high accuracy with less than 2% error compared to standard solvers.
• The solver can determine ROI E-field distribution in approximately 40 ms for a 100 mm diameter ROI.
• Pre-processing stage takes approximately 4 hours, enabling rapid subsequent calculations.

Conclusions:

• The developed fast E-field solver significantly enhances the efficiency of TMS computational dosimetry.
• The method's speed and accuracy make it suitable for real-time applications like neuro-navigation.
• This advancement facilitates wider adoption and optimization of TMS therapies.