Model Of Human Brain Research Articles

Simulation of Blast Induced Traumatic Brain Injury using Finite Element Method

Because of increase in threat from militant groups and during war exposure to blast wave from improvised explosive devices, Traumatic Brain Injury (TBI), a signature injury is on rise worldwide. During blast, the biological system is exposed to a sudden blast over pressure which is several times higher than the ambient pressure causing the damage in the brain. The severity of TBI due to air blast may vary from brief change in mental status or consciousness (termed as mild) to extended period of unconsciousness or memory loss after injuries (termed as severe). The blast wave induced impact on head propagates as shock wave with the broad spectrum of frequencies and stress concentrations in the brain. The primary blast TBI is directly induced by pressure differentials across the skull/fluid/soft tissue interfaces and is further reinforced by the reflected stress waves within the cranial cavity, leading to stress concentrations in certain regions of the brain. In this paper, an attempt has been made to study the behaviour of a human brain model subjected to blast wave based on finite element model using LSDYNA code. The parts of a typical human head such as skull, scalp, CSF, brain are modelled using finite element with properties assumed based on available literature. The model is subjected to blast from frontal lobe, occipital lobe, temporal lobe of the brain. The interaction of the blast wave with the head and subsequent transformation of various forms of shock energy internally have been demonstrated in the human head model. The brain internal pressure levels and the shear stress distribution in the various lobes of the brain such as frontal, parietal, temporal and occipital are determined and presented.

TurboBFS: GPU Based Breadth-First Search (BFS) Algorithms in the Language of Linear Algebra.

Graphs that are used for modeling of human brain, omics data, or social networks are huge, and manual inspection of these graph is impossible. A popular, and fundamental, method used for making sense of these large graphs is the well-known Breadth-First Search (BFS) algorithm. However, BFS suffers from large computational cost especially for big graphs of interest. More recently, the use of Graphics processing units (GPU) has been promising, but challenging because of limited global memory of GPU's, and irregular structures of real-world graphs. In this paper, we present a GPU based linear-algebraic formulation and implementation of BFS, called TurboBFS, that exhibits excellent scalability on unweighted, undirected or directed sparse graphs of arbitrary structure. We demonstrate that our algorithms obtain up to 40 GTEPs, and are on average 15.7x, 5.8x, and 1.8x faster than the other state-of-the-art algorithms implemented on the SuiteSparse:GraphBLAS, GraphBLAST, and gunrock libraries respectively. The codes to implement the algorithms proposed in this paper are available at https://github.com/pcdslab.

Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach.

Central to the investigation of the biomechanics of traumatic brain injury (TBI) and the assessment of injury risk from head impact are finite element (FE) models of the human brain. However, many existing FE human brain models have been developed with simplified representations of the parenchyma, which may limit their applicability as an injury prediction tool. Recent advances in neuroimaging techniques and brain biomechanics provide new and necessary experimental data that can improve the biofidelity of FE brain models. In this study, the CAB-20MSym template model was developed, calibrated, and extensively verified. To implement material heterogeneity, a magnetic resonance elastography (MRE) template image was leveraged to define the relative stiffness gradient of the brain model. A multi-stage inverse FE (iFE) approach was used to calibrate the material parameters that defined the underlying non-linear deviatoric response by minimizing the error between model-predicted brain displacements and experimental displacement data. This process involved calibrating the infinitesimal shear modulus of the material using low-severity, low-deformation impact cases and the material non-linearity using high-severity, high-deformation cases from a dataset of in situ brain displacements obtained from cadaveric specimens. To minimize the geometric discrepancy between the FE models used in the iFE calibration and the cadaveric specimens from which the experimental data were obtained, subject-specific models of these cadaveric brain specimens were developed and used in the calibration process. Finally, the calibrated material parameters were extensively verified using independent brain displacement data from 33 rotational head impacts, spanning multiple loading directions (sagittal, coronal, axial), magnitudes (20–40 rad/s), durations (30–60 ms), and severity. Overall, the heterogeneous CAB-20MSym template model demonstrated good biofidelity with a mean overall CORA score of 0.63 ± 0.06 when compared to in situ brain displacement data. Strains predicted by the calibrated model under non-injurious rotational impacts in human volunteers (N = 6) also demonstrated similar biofidelity compared to in vivo measurements obtained from tagged magnetic resonance imaging studies. In addition to serving as an anatomically accurate model for further investigations of TBI biomechanics, the MRE-based framework for implementing material heterogeneity could serve as a foundation for incorporating subject-specific material properties in future models.

Research on 3D Modeling Software Maya Digital Media Animation Assisted Brain Surgery Technology

Abstract This article uses the three-dimensional (3D) modeling software Maya and the 3D interactive software Unity3D to develop an interactive teaching system that integrates the display of the human brain, the display of the principle pathology of cerebral thrombosis, and the simulation of stent surgery in the brain. The use of this system can result in unlimited learning by multiple people, avoiding shortcomings such as insufficient resources, and strengthening the characteristics of interaction. For human brain models, functions such as zoom-in, rotation, and observation of a single part can be implemented, and text descriptions are provided. For the demonstration of cerebral thrombosis, animation is provided for simulation. For intra-brain stent surgery, the system can automatically demonstrate the surgical process, and it can be actually operated by the user, thereby enhancing the convenience and fun of student learning. This system uses Unity3D software as the main development tool. It uses the software’s advanced lighting system, particle system, and algorithms such as edge detection and screen post effects to establish the main frame of the system. It utilizes C # language for programming, thus enriching the functions of the system. On testing, the virtual interactive teaching system realized by the above method exhibits high interactivity, fun, and practicability.

Abstract P507: Clot Ingestion Leads to the Highest First Pass Complete Recanalization Rates in a Human Brain Model of Large Vessel Occlusion Stroke

Introduction: Suction catheters and stent retrievers are based on the classical paradigm of “en bloc” removal of emboli by generation of tensile forces by vacuum or device withdrawal. However, in this process emboli elongate and fracture leading to fragmentation. Fragments can migrate downstream or remain impacted in the arterial wall resulting in a residual occlusion. Hypothesis: Clot ingestion is biomechanically superior to “en bloc” removal and leads to higher recanalization rates with less complications. Methods: To test this hypothesis, we present a hybrid test bed consisting of pressurized human brains which was developed and validated for large vessel occlusion (LVO) and revascularization. We fabricated 3 types of representative embolus analogs (EAs) (elastic, fragment-prone and stiff) and recreated 105 LVO in twenty-four fresh human brains with the vasculature connected to an hydraulic system to mimic physiological flow and pressures. Recanalization was attempted in 61 LVO cases by Direct Aspiration (DA) using an 068 catheter and in 44 LVO cases combining Stent Retriever with Aspiration (SR+A). Rates of successful recanalization (SR, Grade 2b or higher) and complete recanalization (CR, Grade 2c or higher) were measured. Up to 4 attempts were done before declaring a failure (Grade 2a or lower). Results: DA resulted in 90% of SR, 79% of CR, 61% of first pass SR and 49% of first pass CR. SR+A resulted in 34% of SR, 34% of CR, 23% of first pass SR and 14% of first pass CR. Elastic EA were associated with 88% of SR, 85% of CR, 61% of first pass SR and 52% of first pass CR. Stiff EAs were associated with 64% of SR, 64% of CR, 36% of first pass SR and 36% of first pass CR. Fragment-prone EAs were associated with 64% of SR, 40% of CR, 38% of first pass SR and 21% of first pass CR. Conclusion: Clot ingestion is biomechanically superior to “en bloc” removal and leads to the highest rates of SR, CR and first pass recanalization. DA achieves higher recanalization rates than SR+A. Elastic clots are associated with the highest rates or recanalization, followed by stiff clots and finally by fragment-prone clots.

Stiff-to-Soft Transition from Glass to 3D Hydrogel Substrates in Neuronal Cell Culture.

Over the past decade, hydrogels have shown great potential for mimicking three- dimensional (3D) brain architectures in vitro due to their biocompatibility, biodegradability, and wide range of tunable mechanical properties. To better comprehend in vitro human brain models and the mechanotransduction processes, we generated a 3D hydrogel model by casting photo-polymerized gelatin methacryloyl (GelMA) in comparison to poly (ethylene glycol) diacrylate (PEGDA) atop of SH-SY5Y neuroblastoma cells seeded with 150,000 cells/cm2 according to our previous experience in a microliter-sized polydimethylsiloxane (PDMS) ring serving for confinement. 3D SH-SY5Y neuroblastoma cells in GelMA demonstrated an elongated, branched, and spreading morphology resembling neurons, while the cell survival in cast PEGDA was not supported. Confocal z-stack microscopy confirmed our hypothesis that stiff-to-soft material transitions promoted neuronal migration into the third dimension. Unfortunately, large cell aggregates were also observed. A subsequent cell seeding density study revealed a seeding cell density above 10,000 cells/cm2 started the formation of cell aggregates, and below 1500 cells/cm2 cells still appeared as single cells on day 6. These results allowed us to conclude that the optimum cell seeding density might be between 1500 and 5000 cells/cm2. This type of hydrogel construct is suitable to design a more advanced layered mechanotransduction model toward 3D microfluidic brain-on-a-chip applications.

A porous circulation model of the human brain for in silico clinical trials in ischaemic stroke: A human brain model for ischaemic stroke

The advancement of ischaemic stroke treatment relies on resource-intensive experiments and clinical trials. In order to improve ischaemic stroke treatments, such as thrombolysis and thrombectomy, we target the development of computational tools for in silico trials which can partially replace these animal and human experiments with fast simulations. This study proposes a model that will serve as part of a predictive unit within an in silico clinical trial estimating patient outcome as a function of treatment. In particular, the present work aims at the development and evaluation of an organ-scale microcirculation model of the human brain for perfusion prediction. The model relies on a three-compartment porous continuum approach. Firstly, a fast and robust method is established to compute the anisotropic permeability tensors representing arterioles and venules. Secondly, vessel encoded arterial spin labelling magnetic resonance imaging and clustering are employed to create an anatomically accurate mapping between the microcirculation and large arteries by identifying superficial perfusion territories. Thirdly, the parameter space of the problem is reduced by analysing the governing equations and experimental data. Fourthly, a parameter optimization is conducted. Finally, simulations are performed with the tuned model to obtain perfusion maps corresponding to an open and an occluded (ischaemic stroke) scenario. The perfusion map in the occluded vessel scenario shows promising qualitative agreement with computed tomography images of a patient with ischaemic stroke caused by large vessel occlusion. The results highlight that in the case of vessel occlusion (i) identifying perfusion territories is essential to capture the location and extent of underperfused regions and (ii) anisotropic permeability tensors are required to give quantitatively realistic estimation of perfusion change. In the future, the model will be thoroughly validated against experiments.

Levenberg–Marquardt Algorithm for Acousto-Electric Tomography based on the Complete Electrode Model

The inverse problem in acousto-electric tomography concerns the reconstruction of the electric conductivity in a body from knowledge of the power density function in the interior of the body. This interior power density results from currents prescribed at boundary electrodes, and it can be obtained through electro-static boundary measurements together with auxiliary acoustic probing. Previous works on acousto-electric tomography used the continuum model for the electrostatic boundary conditions; however, from Electrical Impedance Tomography, it is known that the complete electrode model is much more realistic and accurate. In this paper, the inverse problem of acousto-electric tomography is posed using the (smoothened) complete electrode model, and a reconstruction method based on the Levenberg–Marquardt iteration is formulated in appropriate function spaces. This results in a system of partial differential equations to be solved in each step. To increase the computational efficiency and stability, a strategy based on both the complete electrode model and the continuum model is proposed. The method is implemented numerically for a two-dimensional scenario, and the algorithm is tested on two different numerical phantoms, a heart and lung model and a human brain model. Several numerical experiments are carried out confirming the feasibility, accuracy and stability of the developed method.

Next generation human brain models: engineered flat brain organoids featuring gyrification

Brain organoids are considered to be a highly promising in vitro model for the study of the human brain and, despite their various shortcomings, have already been used widely in neurobiological studies. Especially for drug screening applications, a highly reproducible protocol with simple tissue culture steps and consistent output, is required. Here we present an engineering approach that addresses several existing shortcomings of brain organoids. By culturing brain organoids with a polycaprolactone scaffold, we were able to modify their shape into a flat morphology. Engineered flat brain organoids (efBOs) possess advantageous diffusion conditions and thus their tissue is better supplied with oxygen and nutrients, preventing the formation of a necrotic tissue core. Moreover, the efBO protocol is highly simplified and allows to customize the organoid size directly from the start. By seeding cells onto 12 by 12 mm scaffolds, the brain organoid size can be significantly increased. In addition, we were able to observe folding reminiscent of gyrification around day 20, which was self-generated by the tissue. To our knowledge, this is the first study that reports intrinsically caused gyrification of neuronal tissue in vitro. We consider our efBO protocol as a next step towards the generation of a stable and reliable human brain model for drug screening applications and spatial patterning experiments.

Tubular human brain organoids to model microglia-mediated neuroinflammation.

Human brain organoids, 3D brain tissue cultures derived from human pluripotent stem cells, hold promising potential in modeling neuroinflammation for a variety of neurological diseases. However, challenges remain in generating standardized human brain organoids that can recapitulate key physiological features of a human brain. Here, we present tubular organoid-on-a-chip devices to generate better organoids and model neuroinflammation. By employing 3D printed hollow mesh scaffolds, our device can be easily incorporated into multiwell-plates for reliable, scalable, and reproducible generation of tubular organoids. By introducing rocking flows through the tubular device channel, our device can perfuse nutrients and oxygen to minimize organoid necrosis and hypoxia, and incorporate immune cells into organoids to model neuro-immune interactions. Compared with conventional protocols, our method increased neural progenitor proliferation and reduced heterogeneity of human brain organoids. As a proof-of-concept application, we applied this method to model the microglia-mediated neuroinflammation after exposure to an opioid receptor agonist. We found isogenic microglia were activated after exposure to an opioid receptor agonist (DAMGO) and transformed back to the homeostatic status with further treatment by a cannabinoid receptor 2 (CB2) agonist (LY2828360). Importantly, the activated microglia in tubular organoids had stronger cytokine responses compared to those in 2D microglial cultures. Our tubular organoid device is simple, versatile, inexpensive, easy-to-use, and compatible with multiwell-plates, so it can be widely used in common research and clinical laboratory settings. This technology can be broadly used for basic and translational applications in inflammatory diseases including substance use disorders, neural diseases, autoimmune disorders, and infectious diseases.

Identification of dysregulated lipid metabolic pathways in mouse embryonic derived neurons and in a mouse model of Alzheimer's disease

AbstractBackgroundLipidomic data from autopsy brain, human plasma and animal models highlights severe lipid dyshomeostasis in Alzheimer’s disease (AD). The importance of lipid metabolism in AD is supported by GWAS studies which have identified multiple lipid modifying enzymes and interacting proteins. Further, mouse genetic studies have shown benefit of genetic disruption of synaptojanin1 (Synj1), phospholipase A2 (PLA2), and phospholipase D2 (PLD2).MethodWe used high‐content screening for Aß‐triggered synapse loss in mouse embryonic stem cell derived neurons to identify phospholipid modifying enzymes which contributed to synapse loss. In an orthogonal approach we used DESI Imaging Mass Spectrometry to identify lipid metabolic pathways which are dysregulated in brain of a mouse model of AD.ResultWe showed that haploinsufficiency of Synj1, a phosphoinositide phosphatase, and concurrent maintenance of phosphoinositide levels, ameliorated behavioral deficits in a mouse model of AD in spite of pathological amyloid accumulation. Similarly, disruption of phospholipid modifying enzymes PLD2 and PLA2 resulted in rescue of behavioral deficits despite the pathological accumulation of amyloid. It is likely then that specific pathways in lipid metabolism underlie AD disease mechanisms leading to behavioral impairment. Specifically, the loss of polyunsaturated fatty acids among multiple phospholipid classes is common in AD affected human brain and mouse models. Our lipidomic studies show that lipid species are dramatically altered in mouse brain in a regionally specific manner determined by imaging mass spectrometry.ConclusionSynthesis of these findings and the fact that disruption of phospholipid modifying enzymes Synj1, PLA2 and PLD2 rescue behavioral deficits in spite of pathological accumulation of amyloid, implicate acyl chain remodeling as a candidate therapeutic target in AD.

Human cerebral organoids establish subcortical projections in the mouse brain after transplantation

Numerous studies have used human pluripotent stem cell-derived cerebral organoids to elucidate the mystery of human brain development and model neurological diseases in vitro, but the potential for grafted organoid-based therapy in vivo remains unknown. Here, we optimized a culturing protocol capable of efficiently generating small human cerebral organoids. After transplantation into the mouse medial prefrontal cortex, the grafted human cerebral organoids survived and extended projections over 4.5 mm in length to basal brain regions within 1 month. The transplanted cerebral organoids generated human glutamatergic neurons that acquired electrophysiological maturity in the mouse brain. Importantly, the grafted human cerebral organoids functionally integrated into pre-existing neural circuits by forming bidirectional synaptic connections with the mouse host neurons. Furthermore, compared to control mice, the mice transplanted with cerebral organoids showed an increase in freezing time in response to auditory conditioned stimuli, suggesting the potentiation of the startle fear response. Our study showed that subcortical projections can be established by microtransplantation and may provide crucial insights into the therapeutic potential of human cerebral organoids for neurological diseases.

Haptic-based virtual reality simulator for lateral ventricle puncture operation.

The implementation of lateral ventricle puncture (LVP) operation is challenging due to the complex anatomy structure of human brains. Surgical simulator has been proved to be effective in surgical training. However, few works consider the integration of visual and haptic feedback. Aim at achieving a realistic haptic interaction, this paper proposes a haptic-based virtual reality (VR) simulator for the LVP operation. In this simulator, we first reconstruct the three-dimension (3D) model of human brains for tissue/instrument interaction. Then a preoperative planning method based on geometry analysis is introduced to find the feasible entry point of LVP operation. A hierarchical bounding-box collision detection approach is proposed to render haptic feedback that is transferred to humans. Finally, a set of experiments on the proposed simulator and 3D printed models of human brains is carried out. Two sets of experiments are conducted to evaluate the effectiveness of the proposed haptic-based simulator: experiments in the simulator and experiments on a 3D printed brain model. The proposed simulator allows neurosurgeons to train the LVP operation by visualizing the 3D virtual human brain and feeling realistic haptic feedback. We demonstrated that the proposed haptic-based VR simulator can improve the performance of the LVP operation effectively and reduce the operation time.

Potential of Microfluidics and Lab-on-Chip Platforms to Improve Understanding of “prion-like” Protein Assembly and Behavior

Human aging is accompanied by a relevant increase in age-associated chronic pathologies, including neurodegenerative and metabolic diseases. The appearance and evolution of numerous neurodegenerative diseases is paralleled by the appearance of intracellular and extracellular accumulation of misfolded proteins in affected brains. In addition, recent evidence suggests that most of these amyloid proteins can behave and propagate among neural cells similarly to infective prions. In order to improve understanding of the seeding and spreading processes of these “prion-like” amyloids, microfluidics and 3D lab-on-chip approaches have been developed as highly valuable tools. These techniques allow us to monitor changes in cellular and molecular processes responsible for amyloid seeding and cell spreading and their parallel effects in neural physiology. Their compatibility with new optical and biochemical techniques and their relative availability have increased interest in them and in their use in numerous laboratories. In addition, recent advances in stem cell research in combination with microfluidic platforms have opened new humanized in vitro models for myriad neurodegenerative diseases affecting different cellular targets of the vascular, muscular, and nervous systems, and glial cells. These new platforms help reduce the use of animal experimentation. They are more reproducible and represent a potential alternative to classical approaches to understanding neurodegeneration. In this review, we summarize recent progress in neurobiological research in “prion-like” protein using microfluidic and 3D lab-on-chip approaches. These approaches are driven by various fields, including chemistry, biochemistry, and cell biology, and they serve to facilitate the development of more precise human brain models for basic mechanistic studies of cell-to-cell interactions and drug discovery.

Scalable surrogate deconvolution for identification of partially-observable systems and brain modeling

Objective. For many biophysical systems, direct measurement of all state-variables, in − vivo is not feasible. Thus, a key challenge in biological modeling and signal processing is to reconstruct the activity and structure of interesting biological systems from indirect measurements. These measurements are often generated by approximately linear time-invariant dynamical interactions with the hidden system and may therefore be described as a convolution of hidden state-variables with an unknown kernel. Approach. In the current work, we present an approach termed surrogate deconvolution, to directly identify such coupled systems (i.e. parameterize models). Surrogate deconvolution reframes certain non linear partially-observable identification problems, which are common in neuroscience/biology, as analytical objectives that are compatible with almost any user-chosen optimization procedure. Main results. We show that the proposed technique is highly scalable, low in computational complexity, and performs competitively with the current gold-standard in partially-observable system estimation: the joint Kalman Filters (Unscented and Extended). We show the benefits of surrogate deconvolution for model identification when applied to simulations of the Local Field Potential and blood oxygen level dependent (BOLD) signal. Lastly, we demonstrate the empirical stability of Hemodynamic Response Function (HRF) kernel estimates for Mesoscale Individualized NeuroDynamic (MINDy) models of individual human brains. The recovered HRF parameters demonstrate reliable individual variation as well as a stereotyped spatial distribution, on average. Significance. These results demonstrate that surrogate deconvolution promises to enhance brain-modeling approaches by simultaneously and rapidly fitting large-scale models of brain networks and the physiological processes which generate neuroscientific measurements (e.g. hemodynamics for BOLD fMRI).

Flexible, Conformable Organic Semiconductor Proximity Sensor Array for Electronic Skin

AbstractA flexible and conformal thin film proximity sensor array based on organic semiconductor dinaphtho[2,3‐b:2′,3′‐f]thieno[3,2‐b]thiophene (DNTT) is demonstrated, which can be perfectly affixed onto the curved objects such as glass ball, human brain model, and even the deforming human skin. Both spatial position and shape can be registered with fast response when human finger or insulator plastic to be recognized is approaching and removing. This flexible, conformal organic semiconductor sensor array bears merits of low operation voltage (1 V) and ultralow power consumption (0.36 nW), which is ideal for applications of the electronic skin in future wearable electronics.

High-Resolution In Vivo Identification of miRNA Targets by Halo-Enhanced Ago2 Pull-Down

The identification of microRNA (miRNA) targets by Ago2 crosslinking-immunoprecipitation (CLIP) methods has provided major insights into the biology of this important class of non-coding RNAs. However, these methods are technically challenging and not easily applicable to an invivo setting. To overcome these limitations and facilitate the investigation of miRNA functions invivo, we have developed a method based on a genetically engineered mouse harboring a conditional Halo-Ago2 allele expressed from the endogenous Ago2 locus. By using a resin conjugated to the HaloTag ligand, Ago2-miRNA-mRNA complexes can be purified from cells and tissues expressing the endogenous Halo-Ago2 allele. We demonstrate the reproducibility and sensitivity of this method in mouse embryonic stem cells, developing embryos, adult tissues, and autochthonous mouse models of human brain and lung cancers. This method and the datasets we have generated will facilitate the characterization of miRNA-mRNA networks invivo under physiological and pathological conditions.

Realistic modeling of mesoscopic ephaptic coupling in the human brain.

Several decades of research suggest that weak electric fields may influence neural processing, including those induced by neuronal activity and proposed as a substrate for a potential new cellular communication system, i.e., ephaptic transmission. Here we aim to model mesoscopic ephaptic activity in the human brain and explore its trajectory during aging by characterizing the electric field generated by cortical dipoles using realistic finite element modeling. Extrapolating from electrophysiological measurements, we first observe that modeled endogenous field magnitudes are comparable to those in measurements of weak but functionally relevant self-generated fields and to those produced by noninvasive transcranial brain stimulation, and therefore possibly able to modulate neuronal activity. Then, to evaluate the role of these fields in the human cortex in large MRI databases, we adapt an interaction approximation that considers the relative orientation of neuron and field to estimate the membrane potential perturbation in pyramidal cells. We use this approximation to define a simplified metric (EMOD1) that weights dipole coupling as a function of distance and relative orientation between emitter and receiver and evaluate it in a sample of 401 realistic human brain models from healthy subjects aged 16–83. Results reveal that ephaptic coupling, in the simplified mesoscopic modeling approach used here, significantly decreases with age, with higher involvement of sensorimotor regions and medial brain structures. This study suggests that by providing the means for fast and direct interaction between neurons, ephaptic modulation may contribute to the complexity of human function for cognition and behavior, and its modification across the lifespan and in response to pathology.

Computational evaluation for improving the |B1+ field in deep brain and cerebellum using a combination of a birdcage coil and a dipole antenna array

ABSTRACTThe use of strong magnetic fields for brain imaging has shown that increased SNR and resolution can be obtained. Such MRI systems are prone to field non-uniformities that are more likely to appear in deep brain structures making high-quality imaging of deep brain regions a challenge. We investigate the combination of a dipole antenna and Birdcage coil to generate a uniform magnetic field with high intensity in the deep brain. Magnetic fields |B1|, were computed from a human brain model and statistical analysis was done specifically on the tissues of interest. The geometry of the Birdcage coil and eight Dipole antenna array was selected after performing simulations by varying its dimensions, and evaluating the |B1| field intensity and uniformity on the deep brain area. The proposed combination of birdcage coil and dipole array shows to have an improvement on the field intensity and uniformity on the deep brain and cerebellum area in comparison to only using the birdcage coil.

Solving the Time- and Frequency-Multiplexed Problem of Constrained Radiofrequency Induced Hyperthermia.

Targeted radiofrequency (RF) heating induced hyperthermia has a wide range of applications, ranging from adjunct anti-cancer treatment to localized release of drugs. Focal RF heating is usually approached using time-consuming nonconvex optimization procedures or approximations, which significantly hampers its application. To address this limitation, this work presents an algorithm that recasts the problem as a semidefinite program and quickly solves it to global optimality, even for very large (human voxel) models. The target region and a desired RF power deposition pattern as well as constraints can be freely defined on a voxel level, and the optimum application RF frequencies and time-multiplexed RF excitations are automatically determined. 2D and 3D example applications conducted for test objects containing pure water (rtarget = 19 mm, frequency range: 500–2000 MHz) and for human brain models including brain tumors of various size (r1 = 20 mm, r2 = 30 mm, frequency range 100–1000 MHz) and locations (center, off-center, disjoint) demonstrate the applicability and capabilities of the proposed approach. Due to its high performance, the algorithm can solve typical clinical problems in a few seconds, making the presented approach ideally suited for interactive hyperthermia treatment planning, thermal dose and safety management, and the design, rapid evaluation, and comparison of RF applicator configurations.