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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Associação entre alterações eletroencefalográficas interictais, ressonância magnética e resultado cirúrgico de pacientes com epilepsia de lobo temporal / Association of interictal epileptiform discharges, magnetic resonance and surgical outcome of patients with temporal lobe epilepsy

Barbosa, Patricia Horn, 1980- 26 August 2018 (has links)
Orientador: Fernando Cendes / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Ciências Médicas / Made available in DSpace on 2018-08-26T20:41:16Z (GMT). No. of bitstreams: 1 Barbosa_PatriciaHorn_D.pdf: 4694168 bytes, checksum: 4b2bdfa4847274a2d3a88005c77669d2 (MD5) Previous issue date: 2015 / Resumo: Epilepsia de lobo temporal resulta com freqüência em refratariedade ao tratamento medicamentoso. Alguns fatores prognósticos da epilepsia focal e seu tratamento já foram descritos, mas outros ainda estão por ser melhor conhecidos. Nosso objetivo foi investigar associação entre alterações no EEG pré e pós-operatório e na ressonância de crânio pré-operatória com o resultado cirúrgico de pacientes com epilepsia de lobo temporal. Pacientes com epilepsia focal refratária submetidos a cirurgia após investigação não invasiva foram reavaliados. Calculamos o período livre de crises até a recorrência. Realizamos análise visual da RM crânio pré-operatória buscando sinais de atrofia hipocampal e alterações sutis no hipocampo contralateral. Revisamos exames de EEG pré e pós-operatórios buscando inicialmente a presença ou ausência de descargas epileptiformes. Posteriormente, quantificamos atividade epileptiforme interictal e buscamos associação com recorrência de crises. Utilizamos os testes estatísticos qui-quadrado e Fisher, quando adequados, e construímos curvas de sobrevivência de Kaplan-Meier, considerando recorrência de crises como desfecho, com comparação pelo método de Mantel. Na primeira parte do estudo foram incluídos 86 pacientes com atrofia hipocampal. EEG pré-operatório unilateral não se associou a resultado cirúrgico favorável; EEG pós-operatório com presença de atividade epileptiforme interictal não se associou a resultado cirúrgico desfavorável; RM cranio com hipocampo contralateral alterado se associou tanto a resultado cirúrgico desfavorável, quanto com bilateralidade nos EEGs pré-operatórios. Na segunda parte do estudo, com 129 pacientes incluídos, não encontramos associação significativa entre presença de atividade epileptiforme interictal no EEG pós-operatório e resultado cirúrgico. As curvas de sobrevivência dos grupos com descargas epileptiformes presentes versus ausentes não foram estatisticamente diferentes (p=0,09), porem observamos uma tendência, o que motivou a terceira parte. Desta forma, demonstramos, através da quantificação da atividade epileptiforme, associação entre descargas pouco frequentes no EEG pós-operatório com resultado cirúrgico favorável. Finalmente, na tentativa de estabelecer o EEG pós-operatório como preditor de recorrência de crises, não encontramos, com a amostra disponível, associação entre EEG pós-operatório com atividade epileptiforme pouco frequente e resultado cirúrgico favorável. Estes resultados demonstram que é importante valorizar alterações sutis no volume, conformação, eixo e sinal do hipocampo menos afetado na indicação de cirurgia de pacientes com epilepsia de lobo temporal e atrofia hipocampal. O resultado cirúrgico dos pacientes com hipocampo contralateral normal é mais favorável. Alteração eletrográfica bitemporal no EEG pré-operatório, em geral, está associada a alteração estrutural sutil no hipocampo contralateral, que muitas vezes não é valorizada. Tal achado corrobora evidências previamente descritas de que pacientes com EEG pré-operatório bitemporal tem prognóstico cirúrgico menos favorável. Os dados relacionados à análise quantitativa de descargas epileptiformes no EEG pós-operatório mostraram associação entre atividade epileptiforme e resultado cirúrgico. Tal achado sugere que o EEG pode ser uma ferramenta útil no seguimento clínico pós-operatório. Em conclusão, nossos resultados indicaram dois fatores importantes no prognóstico de controle de crises após cirurgia em ELT: presença de alteração hipocampal contralateral mesmo que sutil, e espículas em uma frequência maior que 4 por um período de 15 minutos / Abstract: Temporal lobe epilepsy is frequently linked to medical refractoriness. Many clinical prognostic data on focal epilepsy have repeatedly been described, while surgical outcome factors are yet to be fully known. We presently look into an association between interictal epileptiform discharges in pre and postoperative EEG, as well as preoperative brain magnetic resonance imaging, and surgical outcome of temporal lobe epilepsy. Patients with medically refractory focal epilepsy submitted to surgery following non invasive investigation were reassessed. We calculated time until seizure recurrence. We visually analysed preoperative MRI searching for signs of hipoccampal atrophy, as well as subtle contralateral hipoccampal changes. We reviewed pre and postoperative EEGs concerning presence or absence of interictal epileptiform discharges. Later on, we quantified interictal discharges and tested association with seizure freedom. We used chi square or Fisher¿s exact test, when most adequate. We also built Kaplan-Meier¿s survival curves setting seizure recurrence as endpoint, and compared curves by Mantel method. We initially included 86 patients with hipoccampal atrophy. Preoperative unilateral EEG was not associated with favorable surgical outcome; presence of IED in postoperative EEG was not associated with unfavorable outcome; contralateral hipoccampal changes on preoperative MRI was strongly associated with unfavorable surgical outcome, as well as with bilateral preoperative EEGs. We then studied postoperative EEGs of 129 individuals. There was not a significant association between postoperative EEG and surgical outcome. Survival curves of group of patients with interictal discharges present and absent were not statistically different (p=0.09), but we observed a tendency in that direction. Therefore, we were able to demonstrate through manual quantification of epileptiform discharges that postoperative EEG direct association with surgical outcome. Our ultimate goal was to establish postoperative EEG as predictor of seizure recurrence. Unfortunately we were not able to demonstrate it with data available on our sample. These results highlight importance of assessing subtle changes in volume, form, axis and signal intensity on contralateral hipoccampus prior to indication of surgery in patients with temporal lobe epilepsy with hipoccampal atrophy. Surgical outcome is more favorable when contralateral hipoccampus is normal. Bilateral discharges over temporal electrodes in pre-operative EEG are associated with subtle structural changes on contralateral hipoccampus, which may be underestimated. Such findings is in agreement with previously described evidence of bitemporal preoperative EEG associated with less favorable surgical outcome. Quantification data on postoperative EEG sets forth direct association with epileptiform discharges and surgical outcome. Such finding suggests EEG may be a useful tool in postoperative followup. In conclusion, our results indicate two important prognostic factors for seizure control in surgically treated temporal lobe epilepsy patients: presence of contralateral signs of hipoccampal sclerosis, even if subtle, and interictal epileptiform discharges occuring in a frequency higher than 4 at 15 minutes period / Doutorado / Neurociencias / Fisiopatologia Médica
2

Unsupervised Detection of Interictal Epileptiform Discharges in Routine Scalp EEG : Machine Learning Assisted Epilepsy Diagnosis

Shao, Shuai January 2023 (has links)
Epilepsy affects more than 50 million people and is one of the most prevalent neurological disorders and has a high impact on the quality of life of those suffering from it. However, 70% of epilepsy patients can live seizure free with proper diagnosis and treatment. Patients are evaluated using scalp EEG recordings which is cheap and non-invasive. Diagnostic yield is however low and qualified personnel need to process large amounts of data in order to accurately assess patients. MindReader is an unsupervised classifier which detects spectral anomalies and generates a hypothesis of the underlying patient state over time. The aim is to highlight abnormal, potentially epileptiform states, which could expedite analysis of patients and let qualified personnel attest the results. It was used to evaluate 95 scalp EEG recordings from healthy adults and adult patients with epilepsy. Interictal Epileptiform discharges (IED) occurring in the samples had been retroactively annotated, along with the patient state and maneuvers performed by personnel, to enable characterization of the classifier’s detection performance. The performance was slightly worse than previous benchmarks on pediatric scalp EEG recordings, with a 7% and 33% drop in specificity and sensitivity, respectively. Electrode positioning and partial spatial extent of events saw notable impact on performance. However, no correlation between annotated disturbances and reduction in performance could be found. Additional explorative analysis was performed on serialized intermediate data to evaluate the analysis design. Hyperparameters and electrode montage options were exposed to optimize for the average Mathew’s correlation coefficient (MCC) per electrode per patient, on a subset of the patients with epilepsy. An increased window length and lowered amount of training along with an common average montage proved most successful. The Euclidean distance of cumulative spectra (ECS), a metric suitable for spectral analysis, and homologous L2 and L1 loss function were implemented, of which the ECS further improved the average performance for all samples. Four additional analyses, featuring new time-frequency transforms and multichannel convolutional autoencoders were evaluated and an analysis using the continuous wavelet transform (CWT) and a convolutional autoencoder (CNN) performed the best, with an average MCC score of 0.19 and 56.9% sensitivity with approximately 13.9 false positives per minute.

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