Electric field calculations in brain stimulation based on finite elements: an optimized processing pipeline for the generation and usage of accurate individual head models.

ABSTRACT: The need for realistic electric field calculations in human noninvasive brain stimulation is undisputed to more accurately determine the affected brain areas. However, using numerical techniques such as the finite element method (FEM) is methodologically complex, starting with the creation of accurate head models to the integration of the models in the numerical calculations. These problems substantially limit a more widespread application of numerical methods in brain stimulation up to now. We introduce an optimized processing pipeline allowing for the automatic generation of individualized high-quality head models from magnetic resonance images and their usage in subsequent field calculations based on the FEM. The pipeline starts by extracting the borders between skin, skull, cerebrospinal fluid, gray and white matter. The quality of the resulting surfaces is subsequently improved, allowing for the creation of tetrahedral volume head meshes that can finally be used in the numerical calculations. The pipeline integrates and extends established (and mainly free) software for neuroimaging, computer graphics, and FEM calculations into one easy-to-use solution. We demonstrate the successful usage of the pipeline in six subjects, including field calculations for transcranial magnetic stimulation and transcranial direct current stimulation. The quality of the head volume meshes is validated both in terms of capturing the underlying anatomy and of the well-shapedness of the mesh elements. The latter is crucial to guarantee the numerical robustness of the FEM calculations. The pipeline will be released as open-source, allowing for the first time to perform realistic field calculations at an acceptable methodological complexity and moderate costs.

SUBMITTER: Windhoff M 

PROVIDER: S-EPMC6870291 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature