Objective-To determine which mechanisms lead to activation of neurons in the motor cortex during transcranial magnetic stimulation (TMS) with different current directions and pulse waveforms.Methods-The total electric field induced in a simplified model of a cortical sulcus by a figureeight coil was calculated using the finite element method (FEM). This electric field was then used as the input to determine the response of compartmental models of several types of neurons.Results-The modeled neurons were stimulated at different sites: fiber bends for pyramidal tract neurons, axonal terminations for cortical interneurons and axon collaterals, and a combination of both for pyramidal association fibers. All neurons were more easily stimulated by a PA directed electric field, except association fibers. Additionally, the second phase of a biphasic pulse was found to be more efficient than the first phase of either monophasic or biphasic pulses. Conclusion-The stimulation threshold for different types of neurons depends on the pulse waveform and current direction. The reported results might account for the range of responses obtained in TMS of the motor cortex when using different stimulation parameters.Significance-Modeling studies combining electric field calculations and neuronal models may lead to a deeper understanding of the effect of the TMS-induced electric field on cortical tissue, and may be used to evaluate improvements in TMS coil and waveform design.

Objective-The present work aims to elucidate by what physical mechanisms and where stimulation occurs in the brain during transcranial magnetic stimulation (TMS), taking into account cortical geometry and tissue heterogeneity.Methods-An idealized computer model of TMS was developed, comprising a stimulation coil, a cortical sulcus, and surrounding tissues. The distribution of the induced electric field was computed and estimates of the relevant parameters were generated to predict the locus and type of neurons stimulated during TMS, assuming three different stimulation mechanisms.Results-Tissue heterogeneity strongly affects the spatial distribution of the induced electric field and hence which stimulation mechanism is dominant and where it acts. Stimulation of neurons may occur in the gyrus, in the lip of the gyrus, and in the walls of the sulcus. The stimulated cells can be either pyramidal cells having medium to large caliber axons, or intracortical fibers of medium caliber. Conclusions-The results highlight the importance of cortical folding in shaping locally the action of TMS.Significance-Tissue geometry and heterogeneity in electrical conductivity both must be taken into account to predict accurately stimulation loci and mechanism in TMS.

BackgroundIMRT provides higher dose conformation to the target and dose sparing to surrounding tissues than 3DCRT. Monte Carlo method in Medical Physics is not a novelty to approach dosimetric problems. A new PENELOPE based code named PRIMO recently was published. The most intriguing features of PRIMO are the user-friendly approach, the stand-alone property and the built-in definition of different linear accelerators models. Nevertheless, IMRT simulations are not yet implemented.MethodsA Varian Trilogy with a Millennium120 MLC and a Varian Novalis with 120HD MLC were studied. A RW3 multi-slab phantom was irradiated with Gafchromic films inserted between slabs. An Expression 10000XL scanner (Seiko Epson Corp., Nagano, Japan) was used to digitalize the films. PTW-Verisoft software using the global Gamma Function (2%, 2 mm) was used to compare simulated and experimental results.The primary beam parameters were adjusted to best match reference data previously obtained in a water phantom. Static MLC simulations were performed to validate the MLC models in use. Two Dynamic IMRT preliminary tests were performed with leaves moving with constant and variable speed. A further test of an in phantom delivery of a real IMRT field allowed simulating a clinical-like MLC modulation.ResultsSimulated PDD, X- and Y-profiles in reference conditions showed respectively 100.0%, 100.0% and 99.4% of Gamma points < 1 (2%, 2 mm). Static MLC simulations showed 100.0% of Gamma points < 1 with the 120HD MLC and 99.1% with the Millennium compared with the scanned images.The fixed speed test showed 99.5 and 98.9% of Gamma points < 1 respectively with two different MLC configuration-sampling algorithms when the 120HD MLC was used. The higher modulation MLC motion simulation showed 99.1% of Gamma points < 1 with respect to the experimental. This result depends on the number of the fields to reproduce the MLC motion, as well as calculation time. The clinical-like simulation showed 96.2% of Gamma points < 1 using the same analysis conditions.ConclusionsThe numerical model of the Varian Trilogy and Novalis in the PRIMO software was validated. The algorithms to simulate MLC motion were considered reliable. A clinical-like procedure was successfully simulated.

PurposeTo improve motion robustness of functional fetal MRI scans by developing an intrinsic real‐time motion correction method. MRI provides an ideal tool to characterize fetal brain development and growth. It is, however, a relatively slow imaging technique and therefore extremely susceptible to subject motion, particularly in functional MRI experiments acquiring multiple Echo‐Planar‐Imaging‐based repetitions, for example, diffusion MRI or blood‐oxygen‐level‐dependency MRI.MethodsA 3D UNet was trained on 125 fetal datasets to track the fetal brain position in each repetition of the scan in real time. This tracking, inserted into a Gadgetron pipeline on a clinical scanner, allows updating the position of the field of view in a modified echo‐planar imaging sequence. The method was evaluated in real‐time in controlled‐motion phantom experiments and ten fetal MR studies (17 + 4‐34 + 3 gestational weeks) at 3T. The localization network was additionally tested retrospectively on 29 low‐field (0.55T) datasets.ResultsOur method achieved real‐time fetal head tracking and prospective correction of the acquisition geometry. Localization performance achieved Dice scores of 84.4% and 82.3%, respectively for both the unseen 1.5T/3T and 0.55T fetal data, with values higher for cephalic fetuses and increasing with gestational age.ConclusionsOur technique was able to follow the fetal brain even for fetuses under 18 weeks GA in real‐time at 3T and was successfully applied “offline” to new cohorts on 0.55T. Next, it will be deployed to other modalities such as fetal diffusion MRI and to cohorts of pregnant participants diagnosed with pregnancy complications, for example, pre‐eclampsia and congenital heart disease.

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Fetal MRI is an excellent tool for estimating the fetal gestational age using the head circumference measurements. This study measures the biometry information using fast 30 sec survey scans for the measurement of fetal head circumference using 3D UNet, Bi-parietal diameter, Frontal-occipital diameter for the estimation of the fetal gestational age in the second half of gestation. The results show high accuracy in gestational age measurements which correlates well with the clinical data.

Fetal MRI and MRS are often compromised due to unpredictable fetal motion and commonly require multiple repetitions for diagnostic studies. To overcome these limitations, we are working towards developing a deep-learning based automatic MRI fetal motion tracking method. Our method uses, as input, rapid dynamic multi-echo 2D-EPI acquisitions and is based on a 3D U-Net for brain localisation and translational motion parameters estimation for brain tracking. The results show rapid low-resolution acquisitions contain sufficient information to allow automated fetal brain localisation. Our technique can be used to assess fetal movements and to build navigation systems for fetal MRI/MRS.

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