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Noninvasive Neuromodulation: Modeling and Analysis of Transcranial Brain Stimulation with Applications to Electric and Magnetic Seizure Therapy
Bridging the fields of engineering and psychiatry, this dissertation proposes a novel framework for the rational dosing of electric and magnetic seizure therapy, including electroconvulsive therapy (ECT) and magnetic seizure therapy (MST), for the treatment of psychiatric disorders such as medication resistant major depression and schizophrenia. The objective of this dissertation is to develop computational modeling tools that allow ECT and MST stimulation paradigms to be biophysically optimized ex vivo, prior to testing safety and efficacy in preclinical and clinical trials. Despite therapeutic advances, treatment resistant depression (TRD) remains a largely unmet clinical need. ECT is highly effective for TRD, but its side effects limit its real-world clinical utility. Modifications of treatment technique (e.g., electrode placement, stimulus parameters, novel paradigms such as MST) significantly improve the tolerability of convulsive therapy. However, we know relatively little about the distribution of the electric field (E-field) induced in the brain to inform spatial targeting of ECT and MST. Lacking an understanding of biophysical and physiological mechanisms, refinements in ECT/MST technique rely exclusively on time-consuming and costly clinical trials. Consequently, key questions remain unanswered about how to position the ECT electrodes or MST coil for targeted brain stimulation. Addressing this knowledge gap, this dissertation proposes a new platform that will inform an improved spatial targeting of ECT and MST through state-of-the-art computer simulations of the E-field distribution in human and nonhuman primate (NHP) brain.
Part I of this dissertation aims to develop anatomically realistic finite element models of transcranial electric and magnetic stimulation in human and NHPs incorporating tissue heterogeneity and anisotropy derived from structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) data. The NHP models of ECT and MST are created alongside the human model since NHPs are used in preclinical studies on the mechanisms of seizure therapy.
Part II of this dissertation aims to apply the model developed in Part I to electric and magnetic seizure therapy. We compute the strength and spatial distributions of the E-field induced in the brain by various ECT and MST paradigms. The relative E-field strength among various regions of interest (ROIs) is examined to select electrode/coil configurations that produce most focal stimulation of target ROIs that are considered to mediate the therapeutic action of ECT and MST. Since E-field alone is insufficient to account for individual differences in neurophysiological response, we calibrate the E-field maps relative to the neural activation threshold via in vivo measurements of the corticospinal tract response to single pulses (motor threshold, MT). We derive an empirical estimate of the neural activation threshold by coupling simulated E-field strength with individually measured MT. The E-field strength relative to an empirical neural activation threshold and corresponding volume of suprathreshold stimulation (focality) is examined to inform the selection of ECT and MST stimulus pulse amplitude that will result in focal ROI stimulation. We contrast the ECT/MST stimulation strength and focality with conventional fixed and individually titrated pulse amplitude necessary to induce a seizure (seizure threshold, ST) to study pulse amplitude adjustment as a novel means of controlling stimulation strength and focality. This work provides a basis for rational dosing of seizure therapies that could help improve their risk/benefit ratio and guide the development of safer alternatives for patients with severe psychiatric disorders
Human head temperature and electric field investigations under ECT
Electroconvulsive therapy (ECT) is a non-invasive technique used to treat psychiatric conditions. A high strength low frequency electrical stimulation is delivered through two electrodes. The aim of this work is to develop an ECT finite element human head model to investigate the electric field and the increase in temperature due to the electrical stimulation.
The bio-heat transfer equation combined with Laplace equation and their initial and boundary conditions are used to define the physics of the models. Firstly, finite ele-ment spherical human head models are created in COMSOL Multiphysics and the behaviour of the thermal field due to ECT electrical stimulation is analysed. Hetero-geneity was considered and thermal anisotropy of the skull layer was applied to the finite element models.
Secondly, a realistic human head model is created using magnetic resonance images (MRI). Similar physics is applied to define the thermal and electrical problems, and the anisotropic conductivity of the skull is considered. The realistic models contain anatomical features and realistic tissue conductive properties. Through these models we investigate the role of stimulation parameters such as: electrode montages, strength of stimulation, temperature behaviour, etc. Later on, another realistic human head model with a brain tumor is created and a diffusion tensor image is included. Based on this model the white matter anisotropy is considered and the effect on the electric field is analysed.
The results show that high temperatures only occur on external areas of the head, such as scalp and fat. The thermal conductivity anisotropy is insignificant from a heat-transferring point of view. However, the electrical anisotropy does need to be included in order to get more accurate outcomes. If ECT was applied to a patient
with a brain tumor, then factors such as tumor location, aggressiveness, electrode montage, etc would need to be considered. Further work can be undertaken through computational simulation to make personal ECT treatment feasible in clinical practice
Improving Tumor Treating Fields Treatment Efficacy in Patients With Glioblastoma Using Personalized Array Layouts
PurposeTo investigate tumors of different size, shape, and location and the effect of varying transducer layouts on Tumor Treating Fields (TTFields) distribution in an anisotropic model.Methods and MaterialsA realistic human head model was generated from MR images of 1 healthy subject. Four different virtual tumors were placed at separate locations. The transducer arrays were modeled to mimic the TTFields-delivering commercial device. For each tumor location, varying array layouts were tested. The finite element method was used to calculate the electric field distribution, taking into account tissue heterogeneity and anisotropy.ResultsIn all tumors, the average electric field induced by either of the 2 perpendicular array layouts exceeded the 1-V/cm therapeutic threshold value for TTFields effectiveness. Field strength within a tumor did not correlate with its size and shape but was higher in more superficial tumors. Additionally, it always increased when the array was adapted to the tumor's location. Compared with a default layout, the largest increase in field strength was 184%, and the highest average field strength induced in a tumor was 2.21 V/cm.ConclusionsThese results suggest that adapting array layouts to specific tumor locations can significantly increase field strength within the tumor. Our findings support the idea of personalized treatment planning to increase TTFields efficacy for patients with GBM
Brain and Human Body Modeling
This open access book describes modern applications of computational human modeling with specific emphasis in the areas of neurology and neuroelectromagnetics, depression and cancer treatments, radio-frequency studies and wireless communications. Special consideration is also given to the use of human modeling to the computational assessment of relevant regulatory and safety requirements. Readers working on applications that may expose human subjects to electromagnetic radiation will benefit from this book’s coverage of the latest developments in computational modelling and human phantom development to assess a given technology’s safety and efficacy in a timely manner. Describes construction and application of computational human models including anatomically detailed and subject specific models; Explains new practices in computational human modeling for neuroelectromagnetics, electromagnetic safety, and exposure evaluations; Includes a survey of modern applications for which computational human models are critical; Describes cellular-level interactions between the human body and electromagnetic fields
Brain and Human Body Modeling
This open access book describes modern applications of computational human modeling with specific emphasis in the areas of neurology and neuroelectromagnetics, depression and cancer treatments, radio-frequency studies and wireless communications. Special consideration is also given to the use of human modeling to the computational assessment of relevant regulatory and safety requirements. Readers working on applications that may expose human subjects to electromagnetic radiation will benefit from this book’s coverage of the latest developments in computational modelling and human phantom development to assess a given technology’s safety and efficacy in a timely manner. Describes construction and application of computational human models including anatomically detailed and subject specific models; Explains new practices in computational human modeling for neuroelectromagnetics, electromagnetic safety, and exposure evaluations; Includes a survey of modern applications for which computational human models are critical; Describes cellular-level interactions between the human body and electromagnetic fields
Volume Increase of the Hippocampus after Electroconvulsive Therapy - The Role of the Electric Field and the Individual Differences due to Body Mass Index, Sex and Age
Electroconvulsive therapy (ECT) involves passing an electrical current through the brain, intentionally causing a brief seizure. In Norway, it is common to calculate the dose according to an age-based method. Recent studies have shown that ECT induced volume changes in the grey matter areas, hippocampus and amygdala, strongly correlate with the strength of the electric field (EF). There is not yet a complete understanding of how EFs interact with the brain. This thesis aims to evaluate how well the age-based method accounts for individual differences and investigate the effect of ECT by estimating potential volume changes of the hippocampi resulting from the treatment combined with simulations of the EFs generated by the ECT stimulus. This project is a part of the ongoing research in the ECT-MRI group at Mohn Medical Imaging and Visualization Centre (MMIV). To examine the longitudinal volume changes, T1-weighted magnetic resonance imaging (MRI) scans from 29 patients scanned once before and once after a series of right unilateral ECT were analysed. Variations between individuals were further characterised in regard to body mass index (BMI), sex and age, to examine the extent to which the treatment strategies used today take into account individual differences. Statistically significant negative correlation values were found between the EF strength in the hippocampi and BMI and age. However, there were no significant relationships between volume change and the variables BMI and age. Furthermore, significantly higher EF strengths in the hippocampi were found in female patients compared to male patients. Corresponding significantly greater volume changes in the left hippocampus were found for female patients. Young women have also been reported to be at higher risk for side effects. Moreover, the relationship between volume change and EF strength reported in previous studies was confirmed. In summary, the results in this thesis show that the age-based method used in the clinic today does not correct for individual differences in a way that ensures equal effects of the ECT treatment.Masteroppgave i medisinsk teknologiMTEK39
Translational Modeling of Non-Invasive Electrical Stimulation
Seminal work in the early 2000’s demonstrated the effect of low amplitude non-invasive electrical stimulation in people using neurophysiological measures (motor evoked potentials, MEPs). Clinical applications of transcranial Direct Current Stimulation (tDCS) have since proliferated, though the mechanisms are not fully understood. Efforts to refine the technique to improve results are on-going as are mechanistic studies both in vivo and in vitro. Volume conduction models are being applied to these areas of research, especially in the design and analysis of clinical montages. However, additional research on the parameterization of models remains.
In this dissertation, Finite Element Method (FEM) models of current flow were developed for clinical applications. The first image-derived models of obese subjects were developed to assess the relative impact of fat delineation from skin. Body mass index and more broadly inter-individual differences were considered. The effect of incorporating the meninges was predicted from CAD-based (Computer Aided Design) models before being translated into image-derived head models as an “emulated” CSF conductivity. These predictions were tested in a recently validated database of head models. Multi-scale models of transcutaneous vagus nerve stimulation (tVNS) were developed by coupling image-derived volume conduction models with physiological compartment modeling. The impact of local tissue inhomogeneities on fiber activation were considered
Gender Differences in Current Received during Transcranial Electrical Stimulation.
Low current transcranial electrical stimulation (tCS) is an effective but somewhat inconsistent tool for augmenting neuromodulation. In this study, we used 3D MRI guided electrical transcranial stimulation modeling to estimate the range of current intensities received at cortical brain tissues. Combined T1, T2, and proton density MRIs from 24 adult subjects (12 male and 12 female) were modeled with virtual electrodes placed at F3, F4, C3, and C4. Two sizes of electrodes 20 mm round and 50 mm × 45 mm were examined at 0.5, 1, and 2 mA input currents. The intensity of current received was sampled in a 1-cm sphere placed at the cortex directly under each scalp electrode. There was a 10-fold difference in the amount of current received by individuals. A large gender difference was observed with female subjects receiving significantly less current at targeted parietal cortex than male subjects when stimulated at identical current levels (P < 0.05). Larger electrodes delivered somewhat larger amounts of current than the smaller ones (P < 0.01). Electrodes in the frontal regions delivered less current than those in the parietal region (P < 0.05). There were large individual differences in current levels that the subjects received. Analysis of the cranial bone showed that the gender difference and the frontal parietal differences are due to differences in cranial bone. Males have more cancelous parietal bone and females more dense parietal bone (P < 0.01). These differences should be considered when planning tCS studies and call into question earlier reports of gender differences due to hormonal influences
Computational Model of Electroconvulsive Therapy Considering Electric Field Dependent Skin Conductivity
Improvements in electroconvulsive therapy (ECT) outcomes have followed refinement in device electrical output and electrode montage. The physical properties of the ECT stimulus, together with those of the patient’s head, determine the impedances measured by the device and govern current delivery to the brain and ECT outcomes. However, the precise relations among physical properties of the stimulus, patient head anatomy, and patient-specific impedance to the passage of current are long-standing questions in ECT research and practice. In this thesis, we develop a computational framework based on diverse clinical data sets. We developed anatomical MRI-derived models of transcranial electrical stimulation (tES) that included changes in tissue conductivity due to local electrical current flow. These “adaptive” models simulate ECT both during therapeutic stimulation using high current and when dynamic impedance is measured, as well as prior to stimulation when low current is used to measure static impedance. We modeled two scalp layers: a superficial scalp layer with adaptive conductivity that increases with electric field up to a subject-specific maximum, and a deep scalp layer with a subject-specific fixed conductivity. We demonstrated that variation in these scalp parameters may explain clinical data on subject-specific static impedance and dynamic impedance, their imperfect correlation across subjects, their relationships to seizure threshold, and the role of head anatomy. Adaptive tES models demonstrated that current flow changes local tissue conductivity which in turn shapes current delivery to the brain in a manner not accounted for in fixed tissue conductivity models. Our predictions that variation in individual skin properties, rather than other aspects of anatomy, largely govern the relationship between static impedance, dynamic impedance, and ECT current delivery to the brain, themselves depend on assumptions about tissue properties. Broadly, our novel modeling pipeline opens the door to explore how adaptive-scalp conductivity may impact transcutaneous electrical stimulation (tES). Lastly, we incorporate the (device specific) role of frequency with a single overall assumption allowing quasi-static stimulations of ECT: appropriately parametrizing effective resistivity at single representative frequency (e.g., at 1 kHz), including subject-specific and adaptive skin resistivities. We only stipulate that our functions for (adaptive) resistivity at 1 kHz explain local tissue resistivity as they impact the static and dynamic impedance measures by specific ECT devices (e.g., Thymatron)
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