Simple Head Model Research Articles

A Method for Determining the Envelope of Induced Electric Field on a Simple Human Head Model by Peaks Detection

A Method for Determining the Envelope of Induced Electric Field on a Simple Human Head Model by Peaks Detection

Tensor-conductance model for reducing the computational artifact in target tissue for low-frequency dosimetry

Objective. In protecting human from low-frequency (<100 kHz) exposure, an induced electric field strength is used as a physical quantity for assessment. However, the computational assessment suffers from a staircasing error because of the approximation of curved boundary discretized with cubic voxels. The international guidelines consider an additional reduction factor of 3 when setting the limit of external field strength computed from the permissible induced electric field. Here, a new method was proposed to reduce the staircasing error considering the tensor conductance in human modeling for low-frequency dosimetry. Approach. We proposed a tensor-based conductance model, which was developed on the basis of the filling ratio and the direction of the tissue interface to satisfy the electric field boundary condition and reduce staircasing errors in the target tissue of a voxel human model. Main results. The proposed model was validated using two-layer nonconcentric cylindrical and spherical models with different conductivity contrasts. A comparison of induced electric field strengths with solutions obtained using an analytical formula and finite element method simulation indicated that for a wide range of conductivity ratios, staircasing errors were reduced compared with a conventional scalar-potential finite-difference method. The induced electric field in a simple anatomical head model using our approach was in good agreement with finite element method for exposure to uniform magnetic field exposure and that from coil, simulating transcranial magnetic stimulation. Significance. The proposed tensor-conductance model demonstrated that the staircasing error in an inner target tissue of a voxel human body can be reduced. This finding can be used for the electromagnetic compliance assessment and dose evaluation in electric or magnetic stimulation at low frequencies.

Quantitative Comparison of Analytical Solution and Finite Element Method for Investigation of Near-infrared Light Propagation in Brain Tissue Model.

Functional near-infrared spectroscopy (fNIRS) is an imaging method in which a light source and detector are installed on the head; consequently, the re-emission of light from human skin contains information about cerebral hemodynamic alteration. The spatial probability distribution profile of photons penetrating tissue at a source spot, scattering into the tissue, and being released at an appropriate detector position, represents the spatial sensitivity. Modeling light propagation in a human head is essential for quantitative near-infrared spectroscopy and optical imaging. The specific form of the distribution of light is obtained using the theory of perturbation. An analytical solution of the perturbative diffusion equation (DE) and finite element method (FEM) in a Slab media (similar to the human head) makes it possible to study light propagation due to absorption and scattering of brain tissue. The simulation result indicates that sensitivity is slowly decreasing in the deep area, and the sensitivity below the source and detector is the highest. The depth sensitivity and computation time of both analytical and FEM methods are compared. The simulation time of the analytical approach is four times larger than the FEM. In this paper, an analytical solution and the performance of FEM methods when applied to the diffusion equation for heterogeneous media with a single spherical defect are compared. The depth sensitivity along with the computation time of simulation has been investigated for both methods. For simple and Slab modes of the human brain, the analytical solution is the right candidate. Whenever the brain model is sophisticated, it is possible to use FEM methods, but it costs a higher computation time. Analytical and finite element method (FEM) depth sensitivity are almost the same.FEM requires more computation time, but can handle complicated head models.The analytical method is proposed for the first step and simple head models. The functional near-infrared spectroscopy (fNIRS) is a type of neuromonitoring that uses near-infrared light to measure brain activity indirectly and is similar to electroencephalography (EEG). A single-channel fNIRS system contains a near-infrared light source, which emits near-infrared light (NIR), and a detector is placed near the source. A light intensity change received by detectors indicates brain activity when NIR light penetrates into the gray matter. It is necessary to have a prior understanding of light penetration depth in order to measure brain activity more accurately. fNIRS can be better understood, optimized, and investigated through modeling light propagation in brain tissue. In order to study light in tissues, analytical and numerical methods can be used. In this work, we compared these two approaches quantitatively in a simple slab medium. We concluded that the numerical method takes too much time to calculate the results, but it can be applied to complicated head models. The results of these studies provide researchers with new insights into the modeling and simulation of fNIRS and diffuse optical tomography.

Comparison of EEG Source Localization Using Simplified and Anatomically Accurate Head Models in Younger and Older Adults.

Accuracy of electroencephalography (EEG) source localization relies on the volume conduction head model. A previous analysis of young adults has shown that simplified head models have larger source localization errors when compared with head models based on magnetic resonance images (MRIs). As obtaining individual MRIs may not always be feasible, researchers often use generic head models based on template MRIs. It is unclear how much error would be introduced using template MRI head models in older adults that likely have differences in brain structure compared to young adults. The primary goal of this study was to determine the error caused by using simplified head models without individual-specific MRIs in both younger and older adults. We collected high-density EEG during uneven terrain walking and motor imagery for 15 younger (22±3 years) and 21 older adults (74±5 years) and obtained [Formula: see text]-weighted MRI for each individual. We performed equivalent dipole fitting after independent component analysis to obtain brain source locations using four forward modeling pipelines with increasing complexity. These pipelines included: 1) a generic head model with template electrode positions or 2) digitized electrode positions, 3) individual-specific head models with digitized electrode positions using simplified tissue segmentation, or 4) anatomically accurate segmentation. We found that when compared to the anatomically accurate individual-specific head models, performing dipole fitting with generic head models led to similar source localization discrepancies (up to 2 cm) for younger and older adults. Co-registering digitized electrode locations to the generic head models reduced source localization discrepancies by ∼ 6 mm. Additionally, we found that source depths generally increased with skull conductivity for the representative young adult but not as much for the older adult. Our results can help inform a more accurate interpretation of brain areas in EEG studies when individual MRIs are unavailable.

MODL-13. Sensitivity of Tumor Treating Fields (TTFields) treatment planning to healthy tissue segmentation inaccuracies

Abstract TTFields are FDA approved for treating patients with GBM. TTFields utilize low intensity electric fields with intermediate frequency (100-500 kHz) that disrupt cellular processes critical for cancer cell viability and tumor progression. TTFields have been shown to disrupt multiple phases of the cell cycle including metaphase, anaphase, and telophase, resulting in cellular apoptosis. TTFields are administered through two pairs of capacitive arrays placed on the patient’s scalp. As TTFields are a dose dependent therapy, optimization of array layout for maximizing field intensity may improve survival rates of patients. Thus, Novocure is developing a treatment planning system, in which MR images are used to create a patient-specific model, which in turn is used for simulating electric fields distribution. However, the segmentation process of the MRIs is prone to errors that may influence the choice of array layout, and consequently provide lower TTFields dose than possible. To test the sensitivity of layout chosen to such inaccuracies, we placed different array layouts on the highly detailed MIDA head model and simulated the resulting LMiPD from each configuration. We then simplified the model in several phases and compared the resulting array layout ranking between the full model and each simplified model. Our results show that though the calculated LMiPD is very sensitive to the quality of the model, the ranking pattern between the detailed and simplified models is similar. Some alterations do occur, but this mostly happens when the LMiPD values between switched layouts are very close, rendering these alterations clinically insignificant. Based on these results, we conclude that the ranking order of array layouts by LMiPD dose does not significantly change between detailed and simplified head models even though the LMiPD dose itself is sensitive to the quality of the head model.

Computational Modeling and Investigation of the Vibro-Acoustic Effects Induced by Intracranial Stenosis in a Simplified Head Model

Computational Modeling and Investigation of the Vibro-Acoustic Effects Induced by Intracranial Stenosis in a Simplified Head Model

Evaluation of Blast Simulation Methods for Modeling Blast Wave Interaction With Human Head.

Blast-induced traumatic brain injury (bTBI) research is crucial in asymmetric warfare. The finite element analysis is an attractive option to simulate the blast wave interaction with the head. The popular blast simulation methods are ConWep-based pure Lagrangian, Arbitrary-Lagrangian-Eulerian, and coupling method. This study examines the accuracy and efficiency of ConWep and coupling methods in predicting the biomechanical response of the head. The simplified cylindrical, spherical surrogates and biofidelic human head models are subjected to field-relevant blast loads using these methods. The reflected overpressures at the surface and pressures inside the brain from the head models are qualitatively and quantitatively evaluated against the available experiments. Both methods capture the overall trends of experiments. Our results suggest that the accuracy of the ConWep method is mainly governed by the radius of curvature of the surrogate head. For the relatively smaller radius of curvature, such as cylindrical or spherical head surrogate, ConWep does not accurately capture decay of reflected blast overpressures and brain pressures. For the larger radius of curvature, such as the biofidelic human head, the predictions from ConWep match reasonably well with the experiment. For all the head surrogates considered, the reflected overpressure-time histories predicted by the coupling method match reasonably well with the experiment. Coupling method uniquely captures the shadowing and union of shock waves governed by the geometry-driven flow dynamics around the head. Overall, these findings will assist the bTBI modeling community to judiciously select an objective-driven modeling methodology.

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&#x2013;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 (&#x003E;80%, the ratio of the root-mean-square of the noise matrix to the data matrix) and high co-registration errors (rotation error&#x003E;2&#x00B0;) significantly reduced the contributions of realistic head models.

Human in-vivo magnetic resonance current density imaging of the brain by optimizing head tissue conductivities

Abstract Introduction: Magnetic resonance current density imaging (MRCDI) aims to reconstruct the current flow of transcranial electrical stimulation (TES) in the brain from MR-measurements of the current-induced magnetic field Bz. Aim: We test the performance of a standard reconstruction algorithm (“projected current density algorithm”, PCD, Jeong et al. 2014) for human brain data. We compare it with current flow simulations using personalized head models. Methods:1. We generated ground-truth data for the TES current flow and Bz-field using a detailed head model and SimNIBS (www.simnibs.org). We applied the PCD algorithm to the Bz -field and quantified the reconstruction performance by comparison with the ground-truth current flow. We additionally compared the PCD results with simulations using a simple head model (“3c” with scalp, bone and a homogeneous intracranial compartment). 2. We reconstructed the current flow from in-vivo MRCDI data (Göksu et al, 2018) with the PCD algorithm. We also used head models of different complexities (“3c” and “4c”: scalp, skull, CSF & brain) and optimized their conductivities to minimize the root-mean-square difference between the measured and simulated Bz. Results: 1. For simulated Bz data, the PCD algorithm only coarsely reconstructed the true current flow. Even the simple head model performed better. 2. For measured Bz data, current flows obtained with personalized head models and fitted conductivities explained the measurements better than the current flow reconstructed with the PCD algorithm. This was already the case for the simple head model (3c). The more detailed model (4c) resulted in further statistically significant improvements. However, for all models, the unexplained variance stayed above the noise floor, indicating remaining differences to unknown true current flow. Conclusions: The PCD algorithm has low accuracy for MRCDI data of the brain. However, MRCDI is useful for evaluations and improvements of current flow simulations with anatomically detailed personalized head models. Keywords: magnetic resonance current density imaging, personalized electric field calculation, dose control, transcranial electrical stimulation

Nonlinear ultrasound simulation in an axisymmetric coordinate system using a k-space pseudospectral method.

A full-wave model for nonlinear ultrasound propagation through a heterogeneous and absorbing medium in an axisymmetric coordinate system is developed. The model equations are solved using a nonstandard or k-space pseudospectral time domain method. Spatial gradients in the axial direction are calculated using the Fourier collocation spectral method, and spatial gradients in the radial direction are calculated using discrete trigonometric transforms. Time integration is performed using a k-space corrected finite difference scheme. This scheme is exact for plane waves propagating linearly in the axial direction in a homogeneous and lossless medium and significantly reduces numerical dispersion in the more general case. The implementation of the model is described, and performance benchmarks are given for a range of grid sizes. The model is validated by comparison with several analytical solutions. This includes one-dimensional absorption and nonlinearity, the pressure field generated by plane-piston and bowl transducers, and the scattering of a plane wave by a sphere. The general utility of the model is then demonstrated by simulating nonlinear transcranial ultrasound using a simplified head model.

Variations in Constitutive Properties of the Fluid Elicit Divergent Vibrational and Pressure Response Under Shock Wave Loading.

We performed a characterization of the shock wave loading on the response of the specimen representing a simplified head model. A polycarbonate cylinder (2-in. outer diameter, wall thickness: 0.06 or 0.12 in.) was filled with two fluids: pure de-ionized water and 40% glycerol in water, which differ only slightly in their constitutive material properties. These two fluids were selected to represent the cerebrospinal fluid and cerebral blood, using their high strain rate viscosity as a primary selection criterion. The model specimen was exposed to a single shock wave with two nominal intensities: 70 and 130 kPa overpressure. The response of the model was measured using three strain gauges and three pressure sensors, one mounted on the front face of the cylinder and two embedded in the cylinder to measure the pressure inside of the fluid. We noted several discriminant characteristics in the collected data, which indicate that the type of fluid is strongly influencing the response. The vibrations of the cylinder walls are strongly correlated with the fluid kind. The similarity analysis via the Pearson coefficient indicated that the pressure waveforms in the fluid are only moderately correlated, and these results were further corroborated by Euclidean distance analysis. Continuous wavelet transform of pressure waveforms revealed that the frequency response is strongly correlated with the properties of the fluid. The observed differences in strain and pressure modalities stem from relatively small differences in the properties of the fluids used in this study.

A Dual-ID RFID Tag for Headgear Based on Quasi-Yagi and Dipole Antennas

In this article, we present a dual-ID radio frequency identification (RFID) headgear based on quasi-Yagi antenna where we reuse the reflector element as the second dipole antenna that provides radiation pattern upward from the user's head. Thus, we achieve simultaneously the broadside and endfire patterns without increasing the size of the antenna platform. For avoiding the unpredictable impact of the surface of the human body to the electromagnetic properties of the antenna platform, we inserted a periodic surface made up of a 2-by-2 grid of square loops beneath it. It facilitates launching of surface waves thereby enhancing the endfire radiation for the quasi-Yagi antenna and its back metal plate isolates the antenna platform from the human body. We have fitted the whole structure on the headgear by folding the quasi-Yagi antenna elements and created the antenna on a low-permittivity textile substrate. Moreover, we have modeled the antenna in both simple and anatomical head models, both including curvature, and measured the attainable read ranges of 6.8 m and 5 m, for the quasi-Yagi and dipole tags, respectively, in head-worn configuration.

Evaluation of neutron fluence in the treatment room and along the maze of an 18 MV linear accelerator

Neutron fluence and dose equivalent rate in the treatment room and along the maze of an 18 MV medical linear accelerator was evaluated using Monte Carlo code MCNP5. Scope of the study was to test the hypothesis that a simple accelerator head model can adequately estimate the neutron fluence in the treatment room and along the maze without the requirement of a detailed modeling of the complex accelerator head configuration. The accelerator head was modeled either as a spherical cell source of 10 cm in radius or as a point source in the centre of a spherical cell of 10 cm internal and 20 cm external radious, both made of tungsten. The calculations were compared against measurements performed using gold and indium activation foils. A good agreement between calculated and experimental results was observed in the treatment room. However, the calculations at the maze entrance overestimated the neutron fluence by a factor of 3. The results of the study contribute towards the development of a simple and computationally cost effective methodology for the calculation of neutron dose in the treatment room and the maze of high energy medical accelerators providing a representative simulation of the complex accelerator, bunker and maze configurations that cannot be described by presently used analytical expressions.

Capacitively Coupled Electrical Impedance Tomography for Brain Imaging.

Electrical impedance tomography (EIT) is considered as a potential candidate for brain stroke imaging due to its compactness and potential use in bedside and emergency settings. The electrode-skin contact impedance and low conductivity of skull pose some practical challenges to the EIT head imaging. This paper studies the application of capacitively coupled electrical impedance tomography (CCEIT) in brain imaging for the first time. CCEIT is a new contactless EIT technique which uses voltage excitation without direct contact with the skin, as oppose to directly injecting the current to the skin in EIT. Because the safety issue of a new technique should be strictly treated, simulation work based on a simplified head model was carried out to investigate the safety aspects of CCEIT. By comparing with the standard EIT excited by a typical safe current level used in brain imaging, the safe excitation reference of CCEIT is obtained. This is done by comparing the maximum level of internal electrical field (internal current density) of EIT and that of CCEIT. Simulation results provide useful knowledge of excitation signal level of CCEIT and also show a critical comparison with traditional EIT. Practical experiments were carried out with a 12-electrode CCEIT phantom, saline, and carrot samples. Experimental results show the feasibility and potential of CCEIT for stroke imaging. In this paper, the anomaly diameter resolution is 10 mm (1/18 of the phantom diameter), which indicates that small-volume stroke could be detected. This is achieved by a low excitation voltage of 1 V, showing the possibility of even better performance when higher but yet safe level of excitation voltages is used.

Wound ballistic simulation of a headshot with .223 Rem

ABSTRACTIn the context of a crime scene, it became necessary to examine whether a direct shot to the head with calibre .223 Rem. could happen without creating an exit wound. A simplified head model consisting of a bone-sphere filled with gelatine was compared with a more realistic model considering the inner bone structure of the human skull. It turned out that both models show significantly different behaviour. While the bullet normally penetrates the simplified model and causes an exit defect, it was found that bullet fragmentation can happen in the more realistic model due to grazing along inner bones. The fragments might not perforate the skin and remain inside the skull without creating an exit defect.

Brain Tissue Constitutive Material Models and the Finite Element Analysis of Blast-Induced Traumatic Brain Injury

Traumatic brain injury (TBI) often happens due to assaulting loads such as blast on the human head. Finite elements (FEs) can approximately simulate the blast interactions with the human head. An important parameter in the FE modelling procedures is the accuracy of constitutive formulation of the brain tissue. This paper is focusing on implementation of three brain tissue constitutive relations to measure and compare the dynamic behaviour of the brain under identical blast loads. For the geometry, we employ a simple spherical head model to monitor the brain tissue response and examine the uncertainties in FE brain tissue constitutive modelling. The brain tissue is constitutively modelled as hyperelastic, viscoelastic, and hyperviscoelastic type material. Intracranial pressures (ICP), strains, and shear stresses as the dynamic parameters are measured with time. These biomechanical parameters can be compared against the injury thresholds. Our analyses show that although the results for ICPs and strains are close for the three models, however, shear stresses are considerably different. The study will further provide new insight into selecting a proper constitutive model of the brain tissue under dynamic conditions.

Research and application of personalized human body simplification and fusion method

In crowd simulation, 3D (three-dimensional) character modeling is an important topic since the appropriate character models are helpful to improve the efficiency and realism of crowd simulation. The reconstructed 3D character model based on Kinect has a strong sense of reality and low cost. However, these models are all complex and cannot be applied to large-scale crowd simulation directly. In this paper, we propose a novel personalized human body modeling method for mass crowd simulation based on Kinect. The human modeling process is divided into head modeling and torso modeling, and then they are fused into each other to build a personalized human body model. This method can be divided into two parts: In the first part, a simplified method is presented based on edge curvature and area of error. In addition, to preserve the detail characteristics of model, the way of interactive operation is introduced. In the second part, the automatic fusion for the simplified head model and body model is made by using the improved FCF (fusion control function) fusion method. Finally, a hierarchical database for the personalized human body models is built. The experiment results show that the method proposed in this paper has high efficiency and good robustness in practical applications.

Performance Evaluation of Hyperthermia Applicators to Heat Deep-Seated Brain Tumors

Addition of hyperthermia to modern cancer therapies is highly effective in improving the treatment outcome of deep-seated head and neck tumors. Brain tumors, on the other hand, are more difficult for heating due to high perfusion and thermal conduction. However, late side effects of conventional therapies in children with brain cancer make it important to combine hyperthermia with these therapies. For this purpose, a hyperthermia applicator capable of efficient heat delivery to large and deep-seated brain tumors is required. In this paper, we evaluate preliminary design of hyperthermia applicators for treatment of deep-seated brain tumors in children. We present three applicators with a different numbers of antennas. The performance of the applicators is compared and evaluated in terms of hyperthermia quality indicators. Although the analysis results in terms of power loss density show that all the applicators are capable of heating sufficiently large deep-seated spherical tumors in our simple head model, more antennas resulted in higher power absorption in the tumors and higher values of tumor coverage.

A Low-Frequency Panning Method With Compensation for Head Rotation

Amplitude panning produces interaural time difference (ITD) cues that help localize images in directions between loudspeakers. However, if the panning gains are static, then the ITD cues produced in this way vary inconsistently as the listener's head rotates, compared with a real source, and so the dynamic ITD cues are inaccurate. This effect destabilizes the perception of the image and overall scene, and is worse for loudspeakers that are more widely spaced relative to the listener. Based on a simple head model that is accurate in the low-frequency ITD regime, the ITD is calculated for a general field, including those produced by panning. A simple formula is derived relating head orientation, image direction, and a field description vector. Panning functions are then found that compensate for head orientation and are valid for any image direction. For the special case when the listener is facing the image, the functions are equivalent to vector base amplitude panning. The performance is first assessed objectively using measured binaural responses, rather than the simple head model. Subjective comparison is then made with pre-existing listening tests and new listening tests in which the listener's head is tracked to control the panning gains in real-time. These show that images can be stabilized as predicted, and, furthermore, that with the same panning functions, images can be produced in all directions using two loudspeakers placed in front.

Performance Evaluation of Novel Microwave Imaging Algorithms for Stroke Detection using an Accurate 3D Head Model

This paper addresses the feasibility of transportable stroke detection devices based on Ultra-Wideband radar imaging. Advanced artefact removal and processing algorithms have been recently proposed for the specific application of stroke detection. However, their performance have been assessed using a simplified head model. This paper assess the performance of these algorithms using a more accurate 3D head model. Comparisons with other state-of-the-art algorithms confirm the effectiveness of these novel algorithms both in terms of accuracy of stroke localization and amount of artefacts not completely removed.