Rapid computation of TMS-induced E-fields using a dipole-based magnetic stimulation profile approach
Mohammad Daneshzand,
Sergey N. Makarov,
Lucia I. Navarro de Lara,
Bastien Guerin,
Jennifer McNab,
Bruce R. Rosen,
Matti S. Hämäläinen,
Tommi Raij,
Aapo Nummenmaa
Affiliations
Mohammad Daneshzand
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA; Corresponding authors.
Sergey N. Makarov
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA; Department of Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA, USA
Lucia I. Navarro de Lara
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
Bastien Guerin
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
Jennifer McNab
Department of Radiology, Stanford University, Stanford, CA, USA
Bruce R. Rosen
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
Matti S. Hämäläinen
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
Tommi Raij
Department of Physical Medicine and Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago IL, USA; Center for Brain Stimulation, Shirley Ryan Ability Lab, Chicago IL, USA
Aapo Nummenmaa
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA; Corresponding authors.
Background: TMS neuronavigation with on-line display of the induced electric field (E-field) has the potential to improve quantitative targeting and dosing of stimulation, but present commercially available solutions are limited by simplified approximations. Objective: Developing a near real-time method for accurate approximation of TMS induced E-fields with subject-specific high-resolution surface-based head models that can be utilized for TMS navigation. Methods: Magnetic dipoles are placed on a closed surface enclosing an MRI-based head model of the subject to define a set of basis functions for the incident and total E-fields that define the subject's Magnetic Stimulation Profile (MSP). The near real-time speed is achieved by recognizing that the total E-field of the coil only depends on the incident E-field and the conductivity boundary geometry. The total E-field for any coil position can be obtained by matching the incident field of the stationary dipole basis set with the incident E-field of the moving coil and applying the same basis coefficients to the total E-field basis functions. Results: Comparison of the MSP-based approximation with an established TMS solver shows great agreement in the E-field amplitude (relative maximum error around 5%) and the spatial distribution patterns (correlation >98%). Computation of the E-field took ~100 ms on a cortical surface mesh with 120k facets. Conclusion: The numerical accuracy and speed of the MSP approximation method make it well suited for a wide range of computational tasks including interactive planning, targeting, dosing, and visualization of the intracranial E-fields for near real-time guidance of coil positioning.
