Matching Items (8)
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- All Subjects: Epilepsy
- Creators: Harrington Bioengineering Program
- Creators: Muthuswamy, Jitendran
- Member of: Theses and Dissertations
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Description
Development of post-traumatic epilepsy (PTE) after traumatic brain injury (TBI) is a major health concern (5% - 50% of TBI cases). A significant problem in TBI management is the inability to predict which patients will develop PTE. Such prediction, followed by timely treatment, could be highly beneficial to TBI patients. Six male Sprague-Dawley rats were subjected to a controlled cortical impact (CCI). A 6mm piston was pneumatically driven 3mm into the right parietal cortex with velocity of 5.5m/s. The rats were subsequently implanted with 6 intracranial electroencephalographic (EEG) electrodes. Long-term (14-week) continuous EEG recordings were conducted. Using linear (coherence) and non-linear (Lyapunov exponents) measures of EEG dynamics in conjunction with measures of network connectivity, we studied the evolution over time of the functional connectivity between brain sites in order to identify early precursors of development of epilepsy. Four of the six TBI rats developed PTE 6 to 10 weeks after the initial insult to the brain. Analysis of the continuous EEG from these rats showed a gradual increase of the connectivity between critical brain sites in terms of their EEG dynamics, starting at least 2 weeks prior to their first spontaneous seizure. In contrast, for the rats that did not develop epilepsy, connectivity levels did not change, or decreased during the whole course of the experiment across pairs of brain sites. Consistent behavior of functional connectivity changes between brain sites and the "focus" (site of impact) over time was demonstrated for coherence in three out of the four epileptic and in both non-epileptic rats, while for STLmax in all four epileptic and in both non-epileptic rats. This study provided us with the opportunity to quantitatively investigate several aspects of epileptogenesis following traumatic brain injury. Our results strongly support a network pathology that worsens with time. It is conceivable that the observed changes in spatiotemporal dynamics after an initial brain insult, and long before the development of epilepsy, could constitute a basis for predictors of epileptogenesis in TBI patients.
ContributorsTobin, Edward (Author) / Iasemidis, Leonidas (Thesis advisor) / Tsakalis, Konstantinos (Committee member) / Muthuswamy, Jitendran (Committee member) / Arizona State University (Publisher)
Created2012
Description
In epilepsy, malformations that cause seizures often require surgery. The purpose of this research is to join forces with the Multi-Center Epilepsy Lesion Detection (MELD) project at University College London (UCL) in order to improve the process of detecting lesions in patients with drug-resistant epilepsy. This, in turn, will improve surgical outcomes via more structured surgical planning. It is a global effort, with more than 20 sites across 5 continents. The targeted populations for this study include patients whose epilepsy stems from Focal Cortical Dysplasia. Focal Cortical Dysplasia is an abnormality of cortical development, and causes most of the drug-resistant epilepsy. Currently, the creators of MELD have developed a set of protocols which wrap various
commands designed to streamline post-processing of MRI images. Using this partnership, the Applied Neuroscience and Technology Lab at PCH has been able to complete production of a post-processing pipeline which integrates locally sourced smoothing techniques to help identify lesions in patients with evidence of Focal Cortical Dysplasia. The end result is a system in which a patient with epilepsy may experience more successful post-surgical results due to the
combination of a lesion detection mechanism and the radiologist using their trained eye in the presurgical stages. As one of the main points of this work is the global aspect of it, Barrett thesis funding was dedicated for a trip to London in order to network with other MELD project collaborators. This was a successful trip for the project as a whole in addition to this particular thesis. The ability to troubleshoot problems with one another in a room full of subject matter
experts allowed for a high level of discussion and learning. Future work includes implementing machine learning approaches which consider all morphometry parameters simultaneously.
commands designed to streamline post-processing of MRI images. Using this partnership, the Applied Neuroscience and Technology Lab at PCH has been able to complete production of a post-processing pipeline which integrates locally sourced smoothing techniques to help identify lesions in patients with evidence of Focal Cortical Dysplasia. The end result is a system in which a patient with epilepsy may experience more successful post-surgical results due to the
combination of a lesion detection mechanism and the radiologist using their trained eye in the presurgical stages. As one of the main points of this work is the global aspect of it, Barrett thesis funding was dedicated for a trip to London in order to network with other MELD project collaborators. This was a successful trip for the project as a whole in addition to this particular thesis. The ability to troubleshoot problems with one another in a room full of subject matter
experts allowed for a high level of discussion and learning. Future work includes implementing machine learning approaches which consider all morphometry parameters simultaneously.
ContributorsHumphreys, Zachary William (Author) / Kodibagkar, Vikram (Thesis director) / Foldes, Stephen (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Epileptic encephalopathies (EE) are genetic or environmentally-caused conditions that cause “catastrophic” damage or degradation to the sensory, cognitive, and behavioral centers of the brain. Whole-exome sequencing identified de novo heterozygous missense mutations within the DNM1 gene of five pediatric patients with epileptic encephalopathies. DNM1 encodes for the dynamin-1 protein which is involved in endocytosis and synaptic recycling, and it is a member of dynamin GTPase. The zebrafish, an alternative model system for drug discovery, was utilized to develop a novel model for dynamin-1 epileptic encephalopathy through a small molecule inhibitor. The model system mimicked human epilepsy caused by DNM1 mutations and identified potential biochemical pathways involved in the production of this phenotype. The use of microinjections of mutated DNM1 verified phenotypes and was utilized to determine safe and effective antiepileptic drugs (AEDs) for treatment of this specific EE. This zebrafish dynamin-1 epileptic encephalopathy model has potential uses for drug discovery and investigation of this rare childhood disorder.
ContributorsMills, Gabrielle Corley (Author) / Kodibagkar, Vikram (Thesis director) / Rangasamy, Sampath (Committee member) / School of Human Evolution & Social Change (Contributor) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
From time immemorial, epilepsy has persisted to be one of the greatest impediments to human life for those stricken by it. As the fourth most common neurological disorder, epilepsy causes paroxysmal electrical discharges in the brain that manifest as seizures. Seizures have the effect of debilitating patients on a physical and psychological level. Although not lethal by themselves, they can bring about total disruption in consciousness which can, in hazardous conditions, lead to fatality. Roughly 1\% of the world population suffer from epilepsy and another 30 to 50 new cases per 100,000 increase the number of affected annually. Controlling seizures in epileptic patients has therefore become a great medical and, in recent years, engineering challenge.
In this study, the conditions of human seizures are recreated in an animal model of temporal lobe epilepsy. The rodents used in this study are chemically induced to become chronically epileptic. Their Electroencephalogram (EEG) data is then recorded and analyzed to detect and predict seizures; with the ultimate goal being the control and complete suppression of seizures.
Two methods, the maximum Lyapunov exponent and the Generalized Partial Directed Coherence (GPDC), are applied on EEG data to extract meaningful information. Their effectiveness have been reported in the literature for the purpose of prediction of seizures and seizure focus localization. This study integrates these measures, through some modifications, to robustly detect seizures and separately find precursors to them and in consequence provide stimulation to the epileptic brain of rats in order to suppress seizures. Additionally open-loop stimulation with biphasic currents of various pairs of sites in differing lengths of time have helped us create control efficacy maps. While GPDC tells us about the possible location of the focus, control efficacy maps tells us how effective stimulating a certain pair of sites will be.
The results from computations performed on the data are presented and the feasibility of the control problem is discussed. The results show a new reliable means of seizure detection even in the presence of artifacts in the data. The seizure precursors provide a means of prediction, in the order of tens of minutes, prior to seizures. Closed loop stimulation experiments based on these precursors and control efficacy maps on the epileptic animals show a maximum reduction of seizure frequency by 24.26\% in one animal and reduction of length of seizures by 51.77\% in another. Thus, through this study it was shown that the implementation of the methods can ameliorate seizures in an epileptic patient. It is expected that the new knowledge and experimental techniques will provide a guide for future research in an effort to ultimately eliminate seizures in epileptic patients.
In this study, the conditions of human seizures are recreated in an animal model of temporal lobe epilepsy. The rodents used in this study are chemically induced to become chronically epileptic. Their Electroencephalogram (EEG) data is then recorded and analyzed to detect and predict seizures; with the ultimate goal being the control and complete suppression of seizures.
Two methods, the maximum Lyapunov exponent and the Generalized Partial Directed Coherence (GPDC), are applied on EEG data to extract meaningful information. Their effectiveness have been reported in the literature for the purpose of prediction of seizures and seizure focus localization. This study integrates these measures, through some modifications, to robustly detect seizures and separately find precursors to them and in consequence provide stimulation to the epileptic brain of rats in order to suppress seizures. Additionally open-loop stimulation with biphasic currents of various pairs of sites in differing lengths of time have helped us create control efficacy maps. While GPDC tells us about the possible location of the focus, control efficacy maps tells us how effective stimulating a certain pair of sites will be.
The results from computations performed on the data are presented and the feasibility of the control problem is discussed. The results show a new reliable means of seizure detection even in the presence of artifacts in the data. The seizure precursors provide a means of prediction, in the order of tens of minutes, prior to seizures. Closed loop stimulation experiments based on these precursors and control efficacy maps on the epileptic animals show a maximum reduction of seizure frequency by 24.26\% in one animal and reduction of length of seizures by 51.77\% in another. Thus, through this study it was shown that the implementation of the methods can ameliorate seizures in an epileptic patient. It is expected that the new knowledge and experimental techniques will provide a guide for future research in an effort to ultimately eliminate seizures in epileptic patients.
ContributorsShafique, Md Ashfaque Bin (Author) / Tsakalis, Konstantinos (Thesis advisor) / Rodriguez, Armando (Committee member) / Muthuswamy, Jitendran (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2016
Description
In this study, the entrainment of brain dynamics in epilepsy was investigated in a thorough, systematic way. In the first part of the study, diagnosis of epilepsy, elements from the theory of chaos were used to measure the brain dynamics over time from EEGs (electroencephalograms) recorded in humans with either epileptic or non-epileptic seizures. In the second part of the study, treatment of epilepsy, data from rats undergoing VNS (vagus nerve stimulation) treatment were analyzed in the same way. The results suggest that a) the differential diagnosis in humans with epileptic and non-epileptic seizures can be significantly improved by analysis of brain dynamics, and b) the Vagus Nerve Stimulation may be working by controlling the entrainment level of brain dynamics.
ContributorsRoth, Austin Edward (Author) / Iasemidis, Leonidas (Thesis director) / Tsakalis, Kostas (Committee member) / Spano, Mark (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2013-05
Description
For patients with focal drug-resistant epilepsy, surgical remediation can be a hopeful last resort treatment option, but only if enough clinical signs can point to an epileptogenic tissue region. Subdural grids offer ample cortical surface area coverage to evaluate multiple regions of interest, yet they lack the spatial resolution typical of penetrating electrodes. Additionally, subthreshold stimulation through subdural grids is a stable source for detecting eloquent cortex surrounding potential epileptic tissue. Researchers have each tried introducing microelectrodes to increase the spatial resolution but ran into connectivity challenges as the desired surface area increased. Meanwhile, clinical hybrid options have shown promise by combining multiple electrode sizes, maintaining surface area coverage with an increased spatial resolution where necessary. However, a benchtop method to quantify spatial resolution or test signal summation, without the complexity of an in vivo study, has not been found in the literature; a subdural grid in gel solution has functioned previously but without a published method. Thus, a novel hybrid electrode array with a telescopic configuration including three electrode geometries, called the M$^3$ array, is proposed to maintain cortical surface area coverage and provide spatial clarity in regions of interest using precision microfabrication techniques. Electrophysiological recording with this array should enhance the clinical signal portfolio without changing how clinicians interface with the broad surface data from macros. Additionally, this would provide a source for simultaneous recording and stimulation from the same location due to the telescopic nature of the design. A novel benchtop test method should remove complexity from in vivo tests while allowing direct comparison of recording capabilities of different cortical surface electrodes. Implementing the proposed M$^3$ electrode array in intracranial monitoring improves the current technology without much compromise, enhancing patient outcomes, reducing risks, and encouraging swift clinical translation.
ContributorsGarich, Jonathan Von (Author) / Blain Christen, Jennifer M (Thesis advisor) / Abbas, James J (Committee member) / Helms Tillery, Stephen I (Committee member) / Muthuswamy, Jitendran (Committee member) / Raupp, Gregory B (Committee member) / Arizona State University (Publisher)
Created2022
Description
Neurological disorders are the leading cause of physical and cognitive declineglobally and affect nearly 15% of the current worldwide population. These disorders
include, but are not limited to, epilepsy, Alzheimer’s disease, Parkinson’s disease,
and multiple sclerosis. With the aging population, an increase in the prevalence of
neurodegenerative disorders is expected. Electrophysiological monitoring of neural
signals has been the gold standard for clinicians in diagnosing and treating neurological
disorders. However, advances in detection and stimulation techniques have paved the
way for relevant information not seen by standard procedures to be captured and
used in patient treatment. Amongst these advances have been improved analysis of
higher frequency activity and the increased concentration of alternative biomarkers,
specifically pH change, during states of increased neural activity. The design and
fabrication of devices with the ability to reliably interface with the brain on multiple
scales and modalities has been a significant challenge.
This dissertation introduces a novel, concentric, multi-scale micro-ECoG array
for neural applications specifically designed for seizure detection in epileptic patients.
This work investigates simultaneous detection and recording of adjacent neural tissue
using electrodes of different sizes during neural events. Signal fidelity from electrodes
of different sizes during in vivo experimentation are explored and analyzed to highlight
the advantages and disadvantages of using varying electrode sizes. Furthermore, the
novel multi-scale array was modified to perform multi-analyte detection experiments
of pH change and electrophysiological activity on the cortical surface during epileptic
events. This device highlights the ability to accurately monitor relevant information
from multiple electrode sizes and concurrently monitor multiple biomarkers during
clinical periods in one procedure that typically requires multiple surgeries.
ContributorsAkamine, Ian (Author) / Blain Christen, Jennifer (Thesis advisor) / Abbas, Jimmy (Committee member) / Muthuswamy, Jitendran (Committee member) / Goryll, Michael (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2024
Description
Epilepsy is a medical disorder that is difficult to diagnose given the current available protocols and procedures. This project looks at the potential economic impact of a new digital screening technology developed by EpiFinder, Inc. Utilizing a thorough literature review, this thesis generated a concept based clinical utility function comprised of the essential functional aspects of a seizure assessment. EpiFinder’s digital screening tool was then inserted into the clinical utility objective function based on its capabilities. In order to evaluate the potential impact of this model, hospital discharge data from Phoenix Children’s Hospital was assessed for costs relating to procedures performed. This was estimated using average charges for Medicare Part B in 2018. Patients were categorized based on the severity of their seizure presentation into groups of well-controlled, intermediate-controlled, and uncontrolled seizures. Due to a limited data set for well-controlled seizure patients, only intermediate-controlled and uncontrolled groups were compared through the clinical utility model. There was an average cost savings of $227.92 for the uncontrolled group with digital screening and $131.94 for the intermediate-controlled group. The findings of this feasibility study for the economic impact of digital screening suggest further work to refine the model and improve the quality of cost estimates. Clinical utility of seizure assessment procedures and protocols should be quantified through claims data and field specialists opinions to broaden the scope of digital screening’s impact across the continuum of care for epilepsy patients. Comparisons of clinical utility and the creation of an objective function to assess new medical technologies is becoming a common practice for analyzing new medical technologies entering the market. This is the first such attempt in regards to adding a digital screening tool into the current seizure assessment protocols.
ContributorsSilverman, Bernard (Author) / Baldwin, Marjorie (Thesis director) / Mehta, Neel (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05