Virtual Neurostimulation: Computer-aided transcranial magnetic stimulation (TMS) guidance and dosimetry
Publication date
2023-02-07
Authors
Petrov, Petar Ivanov
Editors
Advisors
Dijkhuizen, R.M.
Neggers, S.F.W.
Berg, C.A.T. van den
Supervisors
Document Type
Dissertation
Metadata
Show full item recordCollections
License
Abstract
Transcranial magnetic stimulation (TMS) is a noninvasive treatment that
uses electromagnetic pulses to stimulate nerve cells. For decades, it is attempted to
use high frequency trains of TMS pulses (repetitive or rTMS) to improve
symptoms of neurological or mental health disorders.
Nowadays TMS is mainly used to treat depression. It has proven to be
successful in helping patients who don’t respond to antidepressant medication. In
2008 the Food and Drug Administration (FDA) approved TMS for this purpose in
the US, and many other countries followed, including the Netherlands where health
insurances now reimburse rTMS treatment. Furthermore, TMS is used increasingly
to diagnose diseases of and damage to the central and peripheral nervous system.
TMS therapies, diagnostic use and research applications are plagued by
poor reproducibility and suffer from the large variability in responses and
outcomes. We propose that computer models of induced electric fields and initial
implementations of models describing the interaction between induced currents and
neuronal signaling in the stimulated tissue could help improve the efficacy of TMS
treatment and aid many other applications of TMS.
The work presented in thesis involves a multimodal approach validating the
models that we developed for TMS-induced currents using in-vivo experiments.
The focus is on comparing the predicted TMS-induced electrical field intensity and
spatial distribution from numerical computer models, combined with models of
electric currents and their interaction with neurons in the cortical layers, with
measurable physiological responses. For this purpose, we developed a sophisticated
framework capable of producing subject-specific 3D models of TMS effects.
This thesis not only develops such models but also validates them
empirically in several experiments mainly on human volunteers (and one on
rodents), which is an effort seldom made by other groups, who mainly report
modeling results without much empirical validation. The technical advances that
were needed for this empirical work are also presented (chapter 6).
Finally, we also present a first application of my modeling work, in the
form of a miniature cooled rodent TMS coil, which was constructed based on my
initial models and is useful in translational TMS research involving the treatment of
stroke and is now brought to market by a company that was involved in the work
presented here.
Keywords
TMS; MRI; BOLD; FEM; EMG; NIBS; Meshing; Modeling; Brain; Electromagnetic