Electric Field Comparison for TMS Using Different Neuroimaging Segmentation Methods

Computational electromagnetic modeling is a powerful technique to evaluate the effects of electrical stimulation of the human brain. The results of these simulations can vary depending on the specific segmentation of the head and brain generated from the patient images. Using an existing boundary element fast multipole method (BEM-FMM) electromagnetic solver, this work evaluates the electric field differences modeled using two neuroimaging segmentation methods. A transcranial magnetic stimulation (TMS) coil targeting both the primary motor cortex and the dorsolateral prefrontal cortex (DLPFC) was simulated. Average field differences along a 100 mm line from the coil were small (2% for motor cortex, 3% for DLPFC) and the average field differences in the regions directly surrounding the target stimulation point were 5% for the motor cortex and 2% for DLPFC. More studies evaluating different coils and other segmentation options may further improve the computational modeling for robust TMS treatment.Clinical relevance- Patient-specific computational modeling will provide more information to clinicians for improved localization and targeting of neuromodulation therapies.