Realistic Head Model Research Articles

Modeling implanted metals in electrical stimulation applications

Objective. Metal implants impact the dosimetry assessment in electrical stimulation techniques. Therefore, they need to be included in numerical models. While currents in the body are ionic, metals only allow electron transport. In fact, charge transfer between tissues and metals requires electric fields to drive electrochemical reactions at the interface. Thus, metal implants may act as insulators or as conductors depending on the scenario. The aim of this paper is to provide a theoretical argument that guides the choice of the correct representation of metal implants in electrical models while considering the electrochemical nature of the problem Approach. We built a simple model of a metal implant exposed to a homogeneous electric field of various magnitudes. The same geometry was solved using two different models: a purely electric one (with different conductivities for the implant), and an electrochemical one. As an example of application, we also modeled a transcranial electrical stimulation (tES) treatment in a realistic head model with a skull plate using a high and low conductivity value for the plate. Main results. Metal implants generally act as electric insulators when exposed to electric fields up to around 100 V m−1 and they only resemble a perfect conductor for fields in the order of 1000 V m−1 and above. The results are independent of the implant’s metal, but they depend on its geometry. tES modeling with implants incorrectly treated as conductors can lead to errors of 50% or more in the estimation of the induced fields Significance. Metal implants can be accurately represented by a simple electrical model of constant conductivity, but an incorrect model choice can lead to large errors in the dosimetry assessment. Our results can be used to guide the selection of the most appropriate model in each scenario.

Conservative Finite Element Modeling of EEG and MEG on Unstructured Grids.

For interpretation of electroencephalography (EEG) and magnetoencephalography (MEG) data, multiple solutions of the respective forward problems are needed. In this paper, we assess performance of the mixed-hybrid finite element method (MHFEM) applied to EEG and MEG modeling. The method provides an approximate potential and induced currents and results in a system with a positive semi-definite matrix. The system thus can be solved with a variety of standard methods (e.g. the preconditioned conjugate gradient method). The induced currents satisfy discrete charge conservation law making the method conservative. We studied its performance on unstructured tetrahedral grids for a layered spherical head model as well as a realistic head model. We also compared its accuracy versus the conventional nodal finite element method ( P1 FEM). To avoid modeling singular sources, we completed our computations with a subtraction approach; the derived expression for the MEG response different from earlier published and involves integration of finite quantities only. We conclude that although the MHFEM is more computationally demanding than the P1 FEM, its use is justified for EEG and MEG modeling on low-resolution head models where P1 FEM loses accuracy.

Cortical Source Analysis of Event-Related Potentials: A Developmental Approach

Cortical source analysis of electroencephalographic (EEG) signals has become an important tool in the analysis of brain activity. The aim of source analysis is to reconstruct the cortical generators (sources) of the EEG signal recorded on the scalp. The quality of the source reconstruction relies on the accuracy of the forward problem, and consequently the inverse problem. An accurate forward solution is obtained when an appropriate imaging modality (i.e., structural magnetic resonance imaging – MRI) is used to describe the head geometry, precise electrode locations are identified with 3D maps of the sensor positions on the scalp, and realistic conductivity values are determined for each tissue type of the head model. Together these parameters contribute to the definition of realistic head models. Here, we describe the steps necessary to reconstruct the cortical generators of the EEG signal recorded on the scalp. We provide an example of source reconstruction of event-related potentials (ERPs) during a face-processing task performed by a 6-month-old infant. We discuss the adjustments necessary to perform source analysis with measures different from the ERPs. The proposed pipeline can be applied to the investigation of different cognitive tasks in both younger and older participants.

TMS intensity and focality correlation with coil orientation at three non-motor regions

Objective. The aim of this study is to define the best coil orientations for transcranial magnetic stimulation (TMS) for three clinically relevant brain areas: pre-supplementary motor area (pre-SMA), inferior frontal gyrus (IFG), and posterior parietal cortex (PPC), by means of simulations in 12 realistic head models of the electric field (E-field). Methods. We computed the E-field generated by TMS in our three volumes of interest (VOI) that were delineated based on published atlases. We then analysed the maximum intensity and spatial focality for the normal and absolute components of the E-field considering different percentile thresholds. Lastly, we correlated these results with the different anatomical properties of our VOIs. Results. Overall, the spatial focality of the E-field for the three VOIs varied depending on the orientation of the coil. Further analysis showed that differences in individual brain anatomy were related to the amount of focality achieved. In general, a larger percentage of sulcus resulted in better spatial focality. Additionally, a higher normal E-field intensity was achieved when the coil axis was placed perpendicular to the predominant orientations of the gyri of each VOI. A positive correlation between spatial focality and E-field intensity was found for PPC and IFG but not for pre-SMA. Conclusions. For a rough approximation, better coil orientations can be based on the individual’s specific brain morphology at the VOI. Moreover, TMS computational models should be employed to obtain better coil orientations in non-motor regions of interest. Significance. Finding better coil orientations in non-motor regions is a challenge in TMS and seeks to reduce interindividual variability. Our individualized TMS simulation pipeline leads to fewer inter-individual variability in the focality, likely enhancing the efficacy of the stimulation and reducing the risk of stimulating adjacent, non-targeted areas.

Key factors in the cortical response to transcranial electrical Stimulations—A multi-scale modeling study

Transcranial electrode stimulation (tES), one of the techniques used to apply non-invasive brain stimulation (NIBS), modulates cortical activities by delivering weak electric currents through scalp-attached electrodes. This emerging technique has gained increasing attention recently; however, the results of tES vary greatly depending upon subjects and the stimulation paradigm, and its cellular mechanism remains unclear. In particular, there is a controversy over the factors that determine the cortical response to tES. Some studies have reported that the electric field's (EF) orientation is the determining factor, while others have demonstrated that the EF magnitude itself is the crucial factor. In this work, we conducted an in-depth investigation of cortical activity in two types of electrode montages used widely—the conventional (C)-tES and high-definition (HD)-tES—as well as two stimulation waveforms—direct current (DC) and alternating current (AC). To do so, we constructed a multi-scale model by coupling an anatomically realistic human head model and morphologically realistic multi-compartmental models of three types of cortical neurons (layer 2/3 pyramidal neuron, layer 4 basket cell, layer 5 pyramidal neuron). Then, we quantified the neuronal response to the C-/HD-tDCS/tACS and explored the relation between the electric field (EF) and the radial field's (RF: radial component of EF) magnitude and the cortical neurons' threshold. The EF tES induced depended upon the electrode montage, and the neuronal responses were correlated with the EF rather than the RF's magnitude. The electrode montages and stimulation waveforms caused a small difference in threshold, but the higher correlation between the EF's magnitude and the threshold was consistent. Further, we observed that the neurons' morphological features affected the degree of the correlation highly. Thus, the EF magnitude was a key factor in the responses of neurons with arborized axons. Our results demonstrate that the crucial factor in neuronal excitability depends upon the neuron models' morphological and biophysical properties. Hence, to predict the cellular targets of NIBS precisely, it is necessary to adopt more advanced neuron models that mimic realistic morphological and biophysical features of actual human cells.

Comparison of Transcranial Focused Ultrasound and Transcranial Pulse Stimulation for Neuromodulation: A Computational Study

ObjectiveThe objective of the study was to investigate transcranial wave propagation through two low-intensity focused ultrasound (LIFU)–based brain stimulation techniques—transcranial focused ultrasound stimulation (tFUS) and transcranial pulse stimulation (TPS). Although tFUS involves delivering long trains of acoustic pulses, the newly introduced TPS delivers ultrashort (∼3 μs) pulses repeated at 4 Hz. Accordingly, only a single simulation study with limited geometry currently exists for TPS. We considered a high-resolution three-dimensional (3D) whole human head model in addition to water bath simulations. We anticipate that the results of this study will help researchers investigating LIFU have a better understanding of the effects of the two different techniques. ApproachWith an objective to first reproduce previous computational results, we considered two spherical tFUS transducers that were previously modeled. We assumed identical parameters (geometry, position, and imaging data set) to demonstrate differences, purely because of the waveform considered. For simulations with a 3D head data set, we also considered a parabolic transducer that has been used for TPS delivery. ResultsOur initial results successfully verified previous modeling workflow. The tFUS distribution was characterized by the typical elliptical profile, with its major axis perpendicular to the face of the transducer. The TPS distribution resembled two mirrored meniscus profiles, with its widest diameter oriented parallel to the face of the transducer. The observed intensity value differences were theoretical because the two waveforms differ in both intensity and time. The consideration of a realistic 3D human head model resulted in only a minor distortion of the two waveforms. SignificanceThis study simulated TPS administration using a 3D realistic image-derived data set. Although our comparison results are strictly limited to the model parameters and assumptions made, we were able to elucidate some clear differences between the two approaches. We hope this initial study will pave the way for systematic comparison between the two approaches in the future.

Assessing spino-cortical proprioceptive processing in childhood unilateral cerebral palsy with corticokinematic coherence

ObjectiveTo develop an electrophysiological marker of proprioceptive spino-cortical tracts integrity based on corticokinematic coherence (CKC) in young children with unilateral cerebral palsy (UCP), in whom behavioral measures are not applicable. MethodsElectroencephalography (EEG) signals from 12 children with UCP aged 19 to 57 months were recorded using 128-channel EEG caps while their fingers were moved at 2 Hz by an experimenter, in separate sessions for the affected and non-affected hands. The coherence between movement kinematics and EEG signals (i.e., CKC) was computed at the sensor and source (using a realistic head model) levels. Peaks of CKC obtained for the affected and non-affected hands were compared for location and strength. The relation between CKC strength on the lesion-side, the lesion-type (cortico-subcortical vs. subcortical) and the level of manual ability were studied with 2-way repeated-measures ANOVA. ResultsAt the individual level, a significant CKC peak at the central area contralateral to the moved hand was found in all young children with their non-affected hand and in 8 out of 12 children with their affected hand. At the group level, CKC to the affected hand movements was weaker than CKC to the non-affected hand movements. This difference was influenced by the type of lesion, the effect being predominant in the subgroup (n = 5) with cortico-subcortical lesions. ConclusionCKC is measurable with EEG in young children with UCP and provides electrophysiological evidence for altered proprioceptive spino-cortical tracts on the lesioned brain hemisphere, particularly in children with cortico-subcortical lesions.

Numerical Analysis of RF-Induced Heating While Wearing Face Mask at Magnetic Resonance Imaging

In response to the unprecedented COVID-19 pandemic, wearing face masks in public places and common facilities has been strongly recommended to help prevent the further spread of the virus. However, conductive components of the face mask carry the potential risk of radio-frequency (RF)-induced heating when exposed to an RF electromagnetic field, particularly during magnetic resonance imaging (MRI). In this study, a realistic human head model wearing a face mask exposed to a strong RF electromagnetic field in 1.5 T, 3 T, and 7 T MRI was simulated. A nose wire in contact with the skin and a mask sheet with relatively high electrical conductivity, emulating a silver nanoparticle-coated face mask, was modeled to investigate the worst case of RF-induced heating that could occur during the MRI scan. 24 scenarios were simulated by using finite-difference time-domain (FDTD)-based electromagnetic solver and thermal-transient solver from Sim4Life commercial simulation software. According to the results, a notable enhancement in the specific absorption rate (SAR) and temperature rise was observed in the local region of the skin where the wire contacted the skin around the edge of the high-conductive mask sheet. In particular, a maximum of a 12-fold increase in mass-averaged SAR and a temperature increase of more than 8.0°C occurred because of the conductive face mask at 3 T, compared to the normal polymer-based face mask with low conductivity. Our results confirmed that the degree of RF-induced heating due to the face mask could be completely different depending on the RF frequency of the MRI, location where the nose wire contacted the skin, and conductivity of the mask sheet. To the best of our knowledge, this is the first study to assess the face mask as a factor for RF-induced heating during MRI. These findings are important for providing a safety guide that allows patients to safely undergo MRI while wearing a face mask during the COVID-19 pandemic.

Effects of Different Head Models in Wearable OPM-MEG

Optically pumped magnetometer (OPM)-based magnetoencephalography (MEG) has attracted significant attention due to its flexible sensor configuration and closer proximity to the scalp. The source localization technique of MEG is used in neuroscience and clinical research. Different head models have been developed to provide a forward solution for MEG source localization. However, the effects of different head models have not yet been studied under the new OPM-MEG measurement scenario. In this simulation study, we investigated the effects of eight head models (a local sphere, a corrected-sphere, a boundary element method-based, and five finite element method (FEM)-based models, including isotropic three-, four-, and five-compartment and two anisotropic five-compartment head models) for forward and inverse solutions. In addition, we studied the effects of these eight head models in a more realistic environment, such as under sensor co-registration error and measurement noise. The results showed that the source localization error between the simplified head model and isotropic five-compartment FEM model can reach 4–5 mm, emphasizing the necessity of using an elaborate head model. Additionally, in the comparison of forward and inverse problems, the distinction of cerebrospinal fluid (CSF) showed the most obvious improvement. Thus, a FEM head model with a CSF compartment is recommended. Further, a high level of measurement noise (>80%, the ratio of the root-mean-square of the noise matrix to the data matrix) and high co-registration errors (rotation error>2°) significantly reduced the contributions of realistic head models.

The Impact of Tumor Treating Fields on Glioblastoma Progression Patterns

Tumor-treating fields (TTFields) are an antimitotic treatment modality that interfere with glioblastoma (GBM) cell division and organelle assembly by delivering low-intensity, alternating electric fields to the tumor. A previous analysis from the pivotal EF-14 trial demonstrated a clear correlation between TTFields dose density at the tumor bed and survival in patients treated with TTFields. This study tests the hypothesis that the antimitotic effects of TTFields result in measurable changes in the location and patterns of progression of newly diagnosed GBM. Magnetic resonance images of 428 newly diagnosed GBM patients who participated in the pivotal EF-14 trial were reviewed, and the rates at which distant progression occurred in the TTFields treatment and control arm were compared. Realistic head models of 252 TTFields-treated patients were created, and TTFields intensity distributions were calculated using a finite element method. The TTFields dose was calculated within regions of the tumor bed and normal brain, and its relationship with progression was determined. Distant progression was frequently observed in the TTFields-treated arm, and distant lesions in the TTFields-treated arm appeared at greater distances from the primary lesion than in the control arm. Distant progression correlated with improved clinical outcome in the TTFields patients, with no such correlation observed in the controls. Areas of normal brain that remained normal were exposed to higher TTFields doses compared with normal brain that subsequently exhibited neoplastic progression. Additionally, the average dose to areas of the enhancing tumor that returned to normal was significantly higher than in the areas of the normal brain that progressed to enhancing tumor. There was a direct correlation between TTFields dose distribution and tumor response, confirming the therapeutic activity of TTFields and the rationale for optimizing array placement to maximize the TTFields dose in areas at highest risk of progression, as well as array layout adaptation after progression.

DevfOLD: a toolbox for designing age-specific fNIRS channel placement.

.Significance: Near-infrared spectroscopy (NIRS) is a noninvasive technique that uses scalp-placed sensors to measure cerebral hemoglobin concentration. Commercial NIRS instruments do not allow for whole-head coverage and do not intrinsically indicate which brain areas generate the NIRS signal. Hence, the challenge is to design source–detector channel arrangement that maximizes sensitivity to a given brain region of interest (ROI). Existing methods for optimizing channel placement design have been developed using adult head models. Thus, they have limited utility for developmental research.Aim: We aim to build an application from an existing toolbox (fOLD) that guides NIRS channel configuration based on age group, stereotaxic atlas, and ROI (devfOLD).Approach: The devfOLD provides NIRS channel-to-ROI specificity computed using photon propagation simulation with realistic head models from infant, child, and adult age groups.Results: Cortical locations and user-specified specificity cut-off values influence the between-age consistency and differences in the ROI-to-channel correspondence among the example infant and adult age groups.Conclusions: The study highlights the importance of incorporating age-specific head models for optimizing NIRS channel configurations. The devfOLD toolbox is publicly shared and compatible with multiple operating systems.

Individually optimized multi-channel tDCS for targeting somatosensory cortex

ObjectiveTranscranial direct current stimulation (tDCS) is a non-invasive neuro-modulation technique that delivers current through the scalp by a pair of patch electrodes (2-Patch). This study proposes a new multi-channel tDCS (mc-tDCS) optimization method, the distributed constrained maximum intensity (D-CMI) approach. For targeting the P20/N20 somatosensory source at Brodmann area 3b, an integrated combined magnetoencephalography (MEG) and electroencephalography (EEG) source analysis is used with individualized skull conductivity calibrated realistic head modeling. MethodsSimulated electric fields (EF) for our new D-CMI method and the already known maximum intensity (MI), alternating direction method of multipliers (ADMM) and 2-Patch methods were produced and compared for the individualized P20/N20 somatosensory target for 10 subjects. ResultsD-CMI and MI showed highest intensities parallel to the P20/N20 target compared to ADMM and 2-Patch, with ADMM achieving highest focality. D-CMI showed a slight reduction in intensity compared to MI while reducing side effects and skin level sensations by current distribution over multiple stimulation electrodes. ConclusionIndividualized D-CMI montages are preferred for our follow up somatosensory experiment to provide a good balance between high current intensities at the target and reduced side effects and skin sensations. SignificanceAn integrated combined MEG and EEG source analysis with D-CMI montages for mc-tDCS stimulation potentially can improve control, reproducibility and reduce sensitivity differences between sham and real stimulations.

Uncertainty quantification and sensitivity analysis of transcranial electric stimulation for 9-subdomain human head model

This paper deals with uncertainty quantification of transcranial electric stimulation (TES) of realistic human head model. The head model taken from Visible Human Project consists of 9 subdomains: scalp, skull, CSF, grey matter, white matter, cerebellum, ventricles, jaw and tongue. The deterministic computation of quasi-static induced electric scalar potential features boundary element method (BEM). Conductivities of each subdomain are modelled as uniformly distributed random variables and stochastic analysis features a non-intrusive stochastic collocation method (SCM). The input uncertainties impact only the magnitude of the electric scalar potential and not the position of the potential extrema. Skin and brain conductivities play the most important role, while CSF conductivity has negligible impact on the output potential variance. The significance of the skull conductivity is not high for the chosen input parameter setup. In the previous work authors considered 3-compartment head model which consisted of scalp, skull and brain compartments. The presented model is a step forward in SCM+BEM TES analysis, primarily in terms of model complexity. Comparing the results of the two analyses it can be concluded that the uncertainty in the added tissues’ conductivities do not impact the variation of the output electric potential.

Wavelength and pulse energy optimization for detecting hypoxia in photoacoustic imaging of the neonatal brain: a simulation study.

Cerebral hypoxia is a severe injury caused by oxygen deprivation to the brain. Hypoxia in the neonatal period increases the risk for the development of neurological disorders, including hypoxic-ischemic encephalopathy, cerebral palsy, periventricular leukomalacia, and hydrocephalus. It is crucial to recognize hypoxia as soon as possible because early intervention improves outcomes. Photoacoustic imaging, using at least two wavelengths, through a spectroscopic analysis, can measure brain oxygen saturation. Due to the spectral coloring effect arising from the dependency of optical properties of biological tissues to the wavelength of light, choosing the right wavelength-pair for efficient and most accurate oxygen saturation measurement and consequently quantifying hypoxia at a specific depth is critical. Using a realistic neonate head model and Monte Carlo simulations, we found practical wavelength-pairs that quantified regions with hypoxia most accurately at different depths down to 22 mm into the cortex neighboring the lateral ventricle. We also demonstrated, for the first time, that the accuracy of the sO2 measurement can be increased by adjusting the level of light energy for each wavelength-pair. Considering the growing interest in photoacoustic imaging of the brain, this work will assist in a more accurate use of photoacoustic spectroscopy and help in the clinical translation of this promising imaging modality. Please note that explaining the effect of acoustic aberration of the skull is not in the scope of this study.

Brain-Wide Diffuse Optical Tomography Based on Cap-Based, Whole-Head fNIRS Recording.

Diffuse optical tomography (DOT), based on functional near-infrared spectroscopy, is a portable, low-cost, noninvasive functional neuroimaging technology for studying the human brain in normal and diseased conditions. The goal of the present study was to evaluate the performance of a cap-based brain-wide DOT (BW-DOT) framework in mapping brain-wide networked activities. We first analyzed point-spread-function (PSF)-based metrics on a realistic head geometry. Our simulation results indicated that these metrics of the optode cap varied across the brain and were of lower quality in brain areas deep or away from the optodes. We further reconstructed brain-wide resting-state networks using experimental data from healthy participants, which resembled the template networks established in the fMRI literature. The preliminary results of the present study highlight the importance of evaluating PSF-based metrics on realistic head geometries for DOT and suggest that BW-DOT technology is a promising functional neuroimaging tool for studying brain-wide neural activities and large-scale neural networks, which was not available by patch-based DOT. A full-scope evaluation and validation in more realistic head models and more participants are needed in the future to establish the findings of the present study further.Clinical relevance- Via simulations and experimental evaluation, this work establishes a novel framework to image large-scale brain networks, which benefits the patient population, such as bedridden patients, infants, etc., who otherwise cannot undergo conventional brain monitoring modalities like fMRI and PET.

An individualized Neural Mass Model of ictal activity based on GABA-A pathology for personalization of brain stimulation protocols in epilepsy

Abstract The creation of personalized brain network models for therapeutic intervention with brain stimulation is a promising direction of research in epilepsy. Early work in the last decades has shown that neural mass models can be used to represent realistic epileptic seizure transitions. We provide here a novel semi-autonomous neural mass model that includes the dynamics of chloride accumulation and is capable of realistically reproducing the electrical activity recorded by an SEEG electrode in the epileptogenic zone during a seizure. The neural mass model includes a physiologically inspired algorithm that relates activity-dependent GABA-A depolarization to the pathological accumulation of chloride in pyramidal cells. Due to fluctuating input, chloride overload into pyramidal cells induced seizure-like activity—including pre-ictal, fast onset, and ictal transitions. The fact that the model is capable of generating spontaneous realistic seizures constitutes a novelty in the field of computational modeling with neural masses in epilepsy. With the aim of generating SEEG data to compare with intracranial recordings from epileptic patients, the neural mass model is first embedded in a layered model of the cortex, and then in a realistic head model. The model also accounts for the effects of electric fields on the membrane of cell populations. We provide some examples of model personalization for clinical cases demonstrating that the patients’ SEEG-recorded seizures can be successfully reproduced by the personalized model embedded in the subject-specific realistic head model and that they can be controlled with a DC field. By including key physio-pathological and physical mechanisms, our model simulates realistic ictal SEEG electrical activity and reflects the effects of brain stimulation. This provides a robust framework for the creation of personalized brain network models for the design of therapeutic interventions such as transcranial electrical stimulation (tES) in epilepsy. Keywords: epilepsy, neural mass model, GABA depolarization, personalized models

Is electric field strength deterministic in cortical neurons' response to transcranial electrical stimulation?

Transcranial electrical stimulation (tES), which modulates cortical excitability via electric currents, has attracted increasing attention because of its application in treating neurologic and psychiatric disorders. To obtain a better understanding of the brain areas affected and stimulation's cellular effects, a multi-scale model was proposed that combines multi-compartmental neuronal models and a head model. While one multi-scale model of tES that used straight axons reported that the direction of electric field (EF) is a determining factor in a neuronal response, another model of transcranial magnetic stimulation (TMS) that used arborized axons reported that EF magnitude is more crucial than EF direction because of arborized axons' reduced sensitivity to the latter. Our goal was to investigate whether EF magnitude remains a crucial factor in the neuronal response in a multi-scale model of tES into which an arborized axon is integrated. To achieve this goal, we constructed a multi-scale model that integrated three types of neurons and a realistic head model, and then simulated the neuronal response to realistic EF. We found that EF magnitude was correlated with excitation threshold, and thus, it may be one of the determining factors in cortical neurons' response to tES.Clinical Relevance-This multi-scale model based on biophysical and morphological properties and realistic brain geometry may help elucidate tES's neural mechanisms. Moreover, given its clinical applications, this model may help predict a patient's neuronal response to brain stimulation effectively.

A computational study of the relation between the power density in the tumor and the maximum temperature in the scalp during Tumor Treating Fields (TTFields) therapy.

In this work we investigated the relation between the power density in the tumor and the maximum temperature reached in the scalp during TTFields treatment for glioblastoma. We used a realistic head model to perform the simulations in COMSOL Multiphysics and we solved Pennes' equation to obtain the temperature distribution. Our results indicate that there might be a linear relation between these two quantities and that TTFields are safe from a thermal point of view.

Comprehensive Approaches to Enhancing Tumor Treating Fields Dose at the Tumor

<h3>Purpose/Objective(s)</h3> Tumor Treating Fields (TTFields) are alternating electric fields that inhibit mitosis of cancer cells. In the clinic, TTFields are delivered via transducer arrays placed on the skin of the patient in close proximity to the tumor. A recent study has shown a connection between survival of newly diagnosed Glioblastoma (ndGBM) patients and dose delivered to the tumor bed [1]. In this case, TTFields dose was defined as the product of the power density delivered by the field and device usage (% of time patient was on active treatment). Thus, a key to enhancing the efficacy of TTFields dose is to maximize dose delivery to the tumor by controlling three factors. (a) Designing the transducer arrays to maximize the field intensity delivered by the arrays, (b) Planning the placement of the arrays on the skin to maximize field delivery to the tumor (c) designing the device to increase usage (% of time patient is on active treatment). Here we present ongoing research developing new methods for improving dose delivered to the tumor utilizing the three factors mentioned above. <h3>Materials/Methods</h3> Realistic computational head models of Glioblastoma patients were created using a previously described method [1]. Virtual transducer arrays of different shapes and sizes were placed on the models, and the delivery of TTFields were numerically simulated. The average power density within the brain and tumor bed delivered by each type of transducer array were calculated. An optimization algorithm designed to place the transducer arrays on the scalp in a manner that maximizes power density delivered to the tumor bed was devised. The algorithm utilized numerical simulation of TTFields delivery in an iterative manner. <h3>Results</h3> Generally speaking, transducer arrays with larger surface area delivered higher average power density to the entire brain and tumor bed. However, in some cases, the size of the arrays positioning the arrays on the head in a manner that maximized power density delivery to the tumor. For some type of arrays, the optimization algorithm yielded layouts that increased power delivered to the tumor bed by over 30% relative to a "standard" central layout. <h3>Conclusion</h3> We have demonstrated how array design and optimization algorithms can be used to enhance TTFields dose at the tumor. Optimizing array shape and using light-weight thin materials for the construction of the arrays could yield arrays that not only deliver higher doses to the tumor bed, but also enhance patient comfort during treatment, thereby leading to an increase in usage.

The Influence of the Head Model Conductor on the Source Localization of Auditory Evoked Potentials.

The accuracy of EEG source analysis reconstruction improves when a realistic head volume conductor is modeled. In this study we investigated how the progressively more complex head representations influence the spatial localization of auditory-evoked potentials (AEPs). Fourteen young-adult participants with normal hearing performed the AEP task. Individualized head models were obtained from structural MRI and diffusion-weighted imaging scans collected in a separate session. AEPs were elicited by 1kHz and 4kHz tone bursts during a passive-listening tetanizing paradigm. We compared the amplitude of the N1 and P2 components before and after 4min of tetanic-stimulation with 1kHz sounds. Current density reconstruction values of both components were investigated in the primary auditory cortex and adjacent areas. Furthermore, we compared the signal topography and magnitude obtained with 10 different head models on the EEG forward solution. Starting from the simplest model (scalp, skull, brain), we investigated the influence of modeling the CSF, distinguishing between GM and WM conductors, and including anisotropic WM values. We localized the activity of AEPs within the primary auditory cortex, but not in adjacent areas. The inclusion of the CSF compartment had the strongest influence on the source reconstruction, whereas white matter anisotropy led to a smaller improvement. We conclude that individualized realistic head models provide the best solution for the forward solution when modeling the CSF conductor.