Medicine (St Vincent's) - Theses

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    Virtual intracranial electroencephalography for epilepsy surgery: an ictal magnetoencephalographic study
    Cao, Miao ( 2020)
    Pharmaco-refractory focal epilepsy is a serious clinical problem. Epilepsy surgery is an effective approach to treat pharmaco-refractory focal epilepsy, particularly for complex cases with no clear lesion or an extensive lesion. However, surgical treatment is currently under-used and does not always render favourable outcomes. Invasive intracranial electroencephalography (iEEG) is the pre-surgical gold-standard to localise and circumscribe the epileptogenic zone (EZ). However, iEEG has several important limitations, such as constrained spatial sampling and invasiveness. More importantly, it is not always guaranteed that iEEG electrodes cover the entire EZ, which is believed to be one of the main reasons for unsuccessful surgeries. Non-invasive neuroimaging techniques mitigate the risks and limitations of iEEG by imaging brain structure and neural activity in a whole-brain fashion. Recent advances in electroencephalography (EEG), magnetoencephalography (MEG) and magnetic resonance imaging (MRI) combined with source imaging techniques allow to investigate neural dynamics at comparable temporal and spatial resolutions to iEEG but non-invasively. Solving forward and inverse problems are the two major missions of EEG and MEG source imaging. In this thesis, a study using realistic head model derived from individual MRI of a healthy subject and an epilepsy patient is conducted to understand the operating regime and limitations of constructing EEG and MEG forward models with compromise from brain lesion. Simulations using forward and inverse modelled ictal iEEG time-series and ictal MEG signals also offer crucial insights into reliably reconstructing ictal source signals that preserve important clinical characteristics, such as morphology and spatial patterns. Attempts have also been made to construct functional networks using ictal source signals reconstructed from MEG. There is a pressing need for non-invasive approaches that objectively characterise the EZ in presurgical evaluation. Dynamical network models using iEEG have demonstrated multiple successes in predicting the EZ and surgical outcomes. Combining non-invasive neuroimaging techniques with sophisticated dynamical network modelling approaches may offer valuable information to the current clinical localisation of the EZ such as iEEG. A novel approach, virtual iEEG (ViEEG), is proposed to non-invasively investigate ictal dynamics like iEEG without its limitations. The proof-of-concept study using 36 seizures captured MEG from 12 patients suggest dynamical network models applied to ictal ViEEG provide the valid characterisation of the EZ and non-ictogenic brain areas that are less likely to overlap the EZ. Moreover, solutions from ViEEG and dynamical network models using MEG alone predicts the iEEG seizure onset zone and the optimal source localisation solution that can only be offered using simultaneous EEG and MEG. The proposed approach and its findings demonstrate the feasibility of non-invasively and objectively characterising the EZ and motivate future work to optimise the current methods. The successful implementation of the proposed approach in the clinical setting would lead to significant benefit to people with refractory focal seizures: making surgery more available, minimising invasive recordings and therefore mitigation of risks, as well as improved surgical outcomes.
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    Epileptic seizures: mechanisms and forecasting
    Karoly, Philippa Jane ( 2018)
    Seizure forecasting, like weather forecasting, was once considered the domain of charlatans and purveyors of science fiction. However, neuroscience has now advanced to the point of translating seizure forecasting research into widely available clinical applications. Just like weather apps that report the probability of rain on a given day, it is now conceivable that devices will inform people with epilepsy about their current likelihood of having a seizure. This information could be life-changing: restoring a sense of control and the ability to participate in everyday activities. Over 65 million people around the world have epilepsy; one third cannot control their seizures with medication. The unpredictability of seizures can be devastating, leading to persistent anxiety, exclusion from day-to-day life, serious injury or death. The aim of this thesis is to develop a clinically useful framework for forecasting seizures. The presented research addresses several key questions towards this goal: What drives seizure transitions? Are there underlying rhythms governing seizure onset? If underlying rhythms exist, how can they be integrated into a single determination of an individual's seizure likelihood? By presenting answers to these questions this thesis aims to form the basis for an innovative approach to seizure forecasting.
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    Initial development of an implantable drug delivery device for the treatment of epilepsy
    Bauquier, Sébastien Hyacinthe ( 2018)
    Epilepsy is a chronic neurological condition, characterized by recurrent seizures. Treatment with conventional anti-epileptic drugs (AED) results in only 33% of patients having no seizure recurrence after a prolonged period. Some evidence suggests that the lack of effectiveness of AED penetration into the brain parenchyma could be one of the mechanisms for resistance to treatment. Furthermore, AED side effects often prevent large increases in their dose. It was for these reasons that a new alternative approach to therapy, intracranial implantation of polymer-based drug delivery systems aimed at improving the bioavailability of AED, was investigated in this PhD research project. Genetic Absent Epilepsy Rats from Strasbourg (GAERS) is a strain of rat that has 100% of the animals with recurrent generalised non-convulsive seizures. This animal model has become the gold standard to study the mechanisms underlying absence epilepsy. After validating an automated spike and wave discharges (SWDs) detection algorithm applied to GAERS’ electroencephalograms (EEG) and demonstrating some effects of enrofloxacin on the GAERS’ epileptic activity, in vitro characterisation and in vivo testing of the antiepileptic efficacy of Poly(D,L-lactide-co-glycolide) (PLGA) polymers loaded with anticonvulsants, either phenytoin or lacosamide, were performed. PLGA is a biodegradable copolymer that it is very well tolerated by the brain and can be used as a passive release substrate. In prospective randomized masked experiments, GAERS underwent surgery for implantation of skull electrodes, skull electrodes and blank polymers, or skull electrodes and AED loaded polymers. The polymers were implanted bilaterally and subdurally on the surface of the cortex. Electroencephalogram recordings were started at day 7 post-surgery and continued for eight weeks. The number of SWDs and mean duration of one SWD were compared week-by-week between the groups. Although temporary changes were seen, phenytoin loaded PLGA polymer sheets did not decrease seizure activity in GAERS. However lacosamide loaded PLGA polymer sheets affected seizure activity in GAERS by decreasing the mean duration of SWDs for a sustained period of up to 7 weeks. This provided proof of concept that intracranial implantation of polymer-based drug delivery systems could be used in the treatment of epilepsy. The last chapter of this thesis evaluated the in vivo biocompatibility of Polypyrrole (PPy) implanted subdurally and unilaterally on the surface of the motor cortex in GAERS. Polypyrrole offers the advantage of being electrically conductive which could allow a controlled release of the anti-epileptic medications. Due to the absence of evidence of toxic injury or immune mediated inflammation, it was concluded that PPy offers good histocompatibility with central nervous system cells. Furthermore, the comparison of immunohistochemical scores reveals that the amount of neuronal death and gliosis was significantly less in the PPy side than in the sham surgery side of the cortices (p values of 0.005 and 0.002 respectively) implying that the application of PPy could protect the CNS tissue after surgery. With improvements in polymer technologies and episodic release offering potentially much longer lasting release durations, intracranial polymer-based drug delivery systems may provide an effective therapeutic strategy for chronic epilepsy. While the development of such an antiepileptic device is worthwhile but still years away, the development of an implantable device combining the potential neuroprotective effect of PPy and an anti-inflammatory drug like dexamethasone would certainly be quicker to develop.
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    Cognitive and psychosocial functioning in genetic generalised epilepsy
    LOUGHMAN, AMY ( 2017)
    Genetic generalised epilepsies (GGE) are a common, but under-studied cluster of epileptic syndromes of predominantly child and adolescent onset. The primary syndromes of GGE are childhood absence epilepsy (CAE), juvenile absence epilepsy(JAE), juvenile myoclonic epilepsy (JME), and genetic generalised epilepsy with generalised tonic-clonic seizures only (GTSCO). Important questions remain regarding: the degree of cognitive and psychopathological comorbidity, particularly in adults and in syndromes other than JME; effects of the disease on cognitive function; and psychopathology and psychosocial wellbeing in these patient groups. This thesis aimed to provide a detailed and quantitative description of cognitive function and psychopathology in GGE, assess the impact of contributing factors including subclinical epileptiform discharges on cognitive and psychopathology outcomes, and to evaluate the relationship between psychopathology and cognition. Methods employed include narrative systematic review, quantitative meta-analysis, and prospective assessment of cognitive and psychosocial functioning of a relatively large sample of people with GGE. Results indicated mild to moderately large reductions across most cognitive factors relative to that of healthy control participants and age-based normative data, with a relative weakness in long-term retrieval and memory function. Short-term memory function was not reduced relative to age-based normative data. Overall cognitive ability and memory function was negatively associated with total duration of epileptiform discharges during a 24-hour period. Approximately 50% of the sample reported elevated symptoms on a measure of psychopathology spanning six symptom types, with depression and anxiety the most common amongst these. Collectively, these findings highlight the need for increased awareness, screening and the provision of services for psychological comorbidities for people with GGE.
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    Validating MEG and EEG finite element head models using a controlled rabbit experiment of skull defects
    Lau, Stephan ( 2015)
    Epilepsy affects 20 million people world-wide. When treatment of focal epilepsy with anti-epileptic drugs is ineffective, resective surgery may be considered. It is then essential to accurately determine the location of the seizure focus. Magnetoencephalography (MEG) and electroencephalography (EEG) allow us to reconstruct the location of event-related brain activity using a volume conductor model of the head. The objective of this thesis is to validate MEG and EEG finite element head models using a rabbit experiment of skull defects. An in vivo rabbit experiment was developed that allowed recording high-resolution MEG and EEG above two conducting skull defects. An implantable, coaxial current source was constructed and placed at a series of positions in the cortex under the skull defects. An agarose gel was developed that provided a time-stable conductivity that mimicked different tissue types in the skull defects. A node-shifted, cubic finite element mesh of the head was generated, which differentiated nine tissue types. For the first time, in vivo, experimental evidence was provided of the substantial influence of skull defects on MEG signals. The MEG signal amplitude reduced by as much as 20%, while the EEG signal amplitude increased 2-10 times. The MEG signal amplitude deviated more from the intact skull condition when the source was central under a skull defect. Using the exact finite element head model, forward simulation of the MEG and EEG signals replicated the experimentally observed characteristic magnitude and topography changes due to skull defects. When skull defects, with their physical conductivity, were incorporated in the head model, location and orientation errors during reconstruction were mostly eliminated. The conductivity of the skull defect material non-uniformly modulated its influence on MEG and EEG signals and source reconstruction. The concordance of experimental measurements of the influence of skull defects on MEG and EEG signals and finite element simulations of exactly that experiment validated the finite element head modelling technique. Detailed finite element head models can improve non-invasive MEG- and EEG-based diagnostic localisation of brain activity, such as epileptic discharges.
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    The prolonged ambulatory electroencephalography in genetic generalised epilepsies: characteristics and predictors of prognosis
    SENEVIRATNE, UDAYA ( 2015)
    INTRODUCTION: Epilepsy is a common and serious neurological disorder affecting 65 million people worldwide. Idiopathic (genetic) generalised epilepsy (GGE) constitutes 15-20% of patients with epilepsy. The electroencephalogram (EEG) plays a crucial role in the diagnosis and classification of epilepsy. Bilateral, symmetrical and synchronous generalised spike-wave activity is considered to be the electrographic hallmark of GGE. However, atypical EEG and clinical features as well as the value of EEG in predicting long-term prognosis of IGE have not been well studied in the past. This thesis presents the first detailed and systematic study on typical and atypical EEG findings, atypical focal seizure symptoms and prognosis of GGE based on quantified, 24-hour, ambulatory EEG data. AIMS AND METHODS: (a) To quantify the typical EEG abnormalities in GGE, describe the circadian variations of epileptiform discharges and explore the differences among syndromes: I prospectively recruited and studied a cohort of patients diagnosed with GGE and classified into syndromes based on International League against Epilepsy criteria. All patients had 24-hour ambulatory EEG recordings according to a standard protocol. I quantified EEG abnormalities and used analysis of variance test to explore the differences among syndromes. (b) To quantify the atypical EEG abnormalities in GGE and to explore the relationship between atypical EEG findings and clinical variables: I used generalised linear mixed models to explore the influence of clinical variables (syndrome, age, state of arousal, number of antiepileptic drugs, seizure-free duration, epilepsy duration) on the outcome of atypical EEG characteristics. (c) To explore the association between seizure-free duration and EEG parameters: I analysed the EEG predictors of seizure recurrence with stepwise Cox proportional hazards regression model. (d) To evaluate focal seizure symptoms among patients diagnosed with GGE and to explore the association between focal seizure symptoms and focal epileptiform discharges as well as seizure-free duration: I elicited focal seizure symptoms (FSS) using a standardised, validated questionnaire. Chi-square test for independence was used to explore the relationship between focal epielptiform discharges and FSS. Regression analysis was conducted to examine the relationship between the duration of seizure freedom and FSS. RESULTS: A total of 120 patients were recruited, of which 13 had normal ambulatory EEGs. The final cohort consisted of 33.3% males and 66.7% females with mean age of 28.5±10.7 years (range, 13-58). The mean age of seizure onset was 13.3±5.1. (a) The vast majority (96%) of epileptiform discharges are symmetric in amplitude with fronto-central maximum in topography. Two-thirds of discharges occur in sleep. Epileptiform discharges demonstrate circadian patterns with four peaks; before midnight, after midnight, early morning and afternoon. There are significant differences in spike densities among syndromes. In general quantified epileptiform activity is higher in JAE and JME than CAE and GTCSO. (b) 66% of 24-hour EEG recordings show atypical abnormalities, significantly influenced by the state of arousal. (c) Longer generalised paroxysms are associated with shorter duration of seizure freedom in GGE. (d) 52% of patients report focal seizure symptoms. There is no association between focal seizure symptoms and focal epileptiform discharges. However, focal seizure symptoms are associated with shorter seizure-free duration. CONCLUSION: The results demonstrate the value of prolonged EEG as a biomarker of diagnosis and potentially prognosis. Prolonged EEG recordings have demonstrated: 1) There are circadian patterns in the occurrence of epileptifom discharges. 2) Atypical EEG features and FSS are common in GGE. 3) Recognition of these variations is important to avoid misdiagnosis and inappropriate choice of antiepileptic drugs.
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    Risk factors for depression in community treated epilepsy
    Lacey, Cameron J. ( 2013)
    Risk factors for depression in people with epilepsy remain elusive despite longstanding research into this prevalent, serious comorbidity. In part, this stems from the dominance of samples from tertiary care settings, subjects unrepresentative of the general population of people with epilepsy. This has changed recently with the advent of community-based studies, of which the present study is an example. This thesis investigated the association between depression and epilepsy, applying findings from general depression research to the aetiology of depression in people with epilepsy. The research question was addressed in several ways. A systematic review of risk factors for depression in community epilepsy studies found that the most consistent factors were socio-demographic, despite most studies focusing on epilepsy-related factors. Psychological factors implicated in depression were rarely studied although, in the few studies that did, associations with depression were consistently observed. Second, using data from an existing sample of community-treated people with epilepsy (the Tasmania Epilepsy Register, TER), a first study investigated the prevalence of and risk factors for ‘psychological distress’ (principally anxiety and depression) and its associations with health service use. Psychological distress was common but available variables explained little variance, reflecting that TER was not designed specifically to investigate psychiatric comorbidity. However, ‘psychological distress’ was associated with greater use of primary health care, a useful reminder for clinicians that more frequent attendance for medical care by people with epilepsy may indicate psychiatric comorbidity more than seizure activity. Third, a second study, designed to more comprehensively investigate risk factors for depression, utilised the best-established psychosocial and neurological factors from the literature, as well as a specific, important polymorphism affecting the serotonin transporter gene (SLC6A4). The TER Mood Study recruited subjects from the Register, employing a mailed questionnaire, and saliva collection for genetic study. A large sample (n=554) was recruited and was representative of community treated epilepsy subjects. Depression was associated with increased seizure frequency, stressful life events, a past history of depression, neuroticism, lower social support and use of gabapentin. The model explained 64% of the variance of depression, the best available model to date. While most risk factors for depression identified in this sample of people with epilepsy were similar to those seen in other samples, negative findings for gender and socioeconomic status suggest that there may be several pathways to depression in patients with epilepsy. This is the first study to test in epilepsy subjects the hypothesis of an interaction of life stress and the SLC6A4 polymorphism as a moderator of depression risk. The data did not support the hypothesis. However, strong associations were observed between depression and stressful life events and a lack of associations with indices of disease severity. This has implications for chronic disease depression research generally, not only epilepsy, as many studies have not measured general life stress, only stress narrowly attributable to chronic disease itself. This work has epidemiological, clinical and health services implications and gives guidance to future research into risk factors for depression in epilepsy and other chronic illnesses.