Quantifying the effect of repetitive transcranial magnetic stimulation in the rat brain by µSPECT CBF scans.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is used to treat neurological and psychiatric disorders such as depression and addiction amongst others. Neuro-imaging by means of SPECT is a non-invasive manner of evaluating regional cerebral blood flow (rCBF) changes, which are assumed to reflect changes in neural activity. OBJECTIVE: rCBF changes induced by rTMS are evaluated by comparing stimulation on/off in different stimulation paradigms using microSPECT of the rat brain. METHODS: Rats (n = 6) were injected with 10 mCi of (99m)Tc-HMPAO during application of two rTMS paradigms (1 Hz and 10 Hz, 1430 A at each wing of a 20 mm figure-of-eight coil) and sham. SPM- and VOI-based analysis was performed. RESULTS: rTMS caused widespread significant hypoperfusion throughout the entire rat brain. Differences in spatial extent and intensity of hypoperfusion were observed between both stimulation paradigms: 1 Hz caused significant hypoperfusion (P < 0.05) in 11.9% of rat brain volume while 10 Hz caused this in 23.5%; the minimal t-value induced by 1 Hz was -24.77 while this was -17.98 due to 10 Hz. Maximal percentage of hypoperfused volume due to 1 Hz and 10 Hz was reached at tissue experiencing 0.03-0.15 V/m. CONCLUSION: High-frequency (10 Hz) stimulation causes more widespread hypoperfusion, while 1 Hz induces more pronounced hypoperfusion. The effect of rTMS is highly dependent on the electric field strength in the brain tissue induced by the TMS coil. This innovative imaging approach can be used as a fast screening tool in quantifying and evaluating the effect of various stimulation paradigms and coil designs for TMS and offers a means for research and development.

An efficient 3-D eddy-current solver using an independent impedance method for transcranial magnetic stimulation.

In many important bioelectromagnetic problem settings, eddy-current simulations are required. Examples are the reduction of eddy-current artifacts in magnetic resonance imaging and techniques, whereby the eddy currents interact with the biological system, like the alteration of the neurophysiology due to transcranial magnetic stimulation (TMS). TMS has become an important tool for the diagnosis and treatment of neurological diseases and psychiatric disorders. A widely applied method for simulating the eddy currents is the impedance method (IM). However, this method has to contend with an ill conditioned problem and consequently a long convergence time. When dealing with optimal design problems and sensitivity control, the convergence rate becomes even more crucial since the eddy-current solver needs to be evaluated in an iterative loop. Therefore, we introduce an independent IM (IIM), which improves the conditionality and speeds up the numerical convergence. This paper shows how IIM is based on IM and what are the advantages. Moreover, the method is applied to the efficient simulation of TMS. The proposed IIM achieves superior convergence properties with high time efficiency, compared to the traditional IM and is therefore a useful tool for accurate and fast TMS simulations.

Low-parametric induced current - magnetic resonance electrical impedance tomography for quantitative conductivity estimation of brain tissues using a priori information: a simulation study.

Accurate estimation of the human head conductivity is important for the diagnosis and therapy of brain diseases. Induced Current - Magnetic Resonance Electrical Impedance Tomography (IC-MREIT) is a recently developed non-invasive technique for conductivity estimation. This paper presents a formulation where a low number of material parameters need to be estimated, starting from MR eddy-current field maps. We use a parameterized frequency dependent 4-Cole-Cole material model, an efficient independent impedance method for eddy-current calculations and a priori information through the use of voxel models. The proposed procedure circumvents the ill-posedness of traditional IC-MREIT and computational efficiency is obtained by using an efficient forward eddy-current solver.

A mechanical model of soft biological tissue--an application to lung parenchyma.

This paper presents a fractal mechanical model for branching systems, with application to the respiratory system. Assuming a dichotomously branching tree, each airway tube is modeled by a Kelvin-Voigt model (a spring in parallel with a dashpot) using morphological values. The model allows investigations on the viscoelastic properties within the context of inter-connections between levels of the respiratory tree. The results are in agreement with physiological expectancy. The model presented in this paper can also serve to derive a mechanical model for other branching systems, i.e. the circulatory system.