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Funkční a strukturální konektivita lidského neokortexu v epileptochirurgii / Functional and structural connectivity of human neocortex in epileptosurgeryŠulc, Vlastimil January 2020 (has links)
1 ABSTRACT The presented dissertation deals with prognostic factors influencing a favorable postoperative outcome in patients undergoing surgical treatment of epilepsy and the possibilities of improving the methods used in the localization of epileptogenic lesions. This work is based on the results of four published studies. The first study evaluated the factors influencing the long-term outcomes of epilepsy surgery in MRI-negative (nonlesional) extratemporal lobe epilepsy (nETLE). The aim of the study was to evaluate the benefit of non-invasive diagnostic tests and their relationship with a favorable surgical outcome in a group nETLE patients. Univariate analysis showed that localized interictal epileptiform discharges (IEDs) on the scalp EEG were associated with a favorable surgical outcome. Diagnostic difficulty in this group of patients is highlighted by the fact that, although 9 of 24 patients undergoing surgery had a favorable outcome, and only nine of 85 patients with nETLE achieved such a favorable outcome. The second work evaluated the benefit of SPECT (Single Photon Emission Tomography) statistical processing over traditional subtraction methods in patients with MRI-negative temporal lobe epilepsy (nTLE) and MRI-negative extratemporal epilepsy (nETLE). 49 consecutive patients who underwent...
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[en] IMPROVING EPILEPSY LESION DETECTION USING ADVANCED TECHNIQUES OF ACQUISITION AND ANALYSIS OF MRI: A SYSTEMATIC REVIEW / [pt] MELHORANDO A DETECÇÃO DE LESÕES EPILÉPTICAS UTILIZANDO TÉCNICAS AVANÇADAS DE OBTENÇÃO E ANÁLISE DE MRI: UMA REVISÃO SISTEMÁTICALUCAS MACHADO LOUREIRO 05 May 2022 (has links)
[pt] Em aproximadamente um terço dos pacientes com epilepsia, a cirurgia é
única forma de intervenção para diminuição dos impactos ou término das crises.
Em pacientes sem um foco lesional na imagem por ressonância magnética, essa
intervenção depende de outros métodos investigativos, que nem sempre estão
prontamente disponíveis. Nesses casos, métodos avançados de pós-processamento
e de sequências de imagens podem ajudar a detectar lesões. O objetivo dessa revisão
sistemática foi resumir a disponibilidade e taxas de sucesso dessas técnicas. De
acordo com as diretrizes PRISMA, usando as bases de dados PubMED, Web of
Science, PsycNET e CENTRAL, uma busca por artigos foi conduzida até o dia 12
de janeiro de 2021. No total, a busca retornou 4.024 artigos, com 49 permanecendo
após a revisão. Vinte e cinco artigos usaram alguma forma de voxel-based
morphometry, 14 usaram machine learning e 10 usaram técnicas avançadas de
MRI. Apenas um artigo descreveu um estudo prospectivo. A taxa de detecção de
lesões variou bastante entre estudos, com técnicas de machine learning
demonstrando taxas mais consistentes, todas acima de 50 por cento em grupos de pacientes
com imagem negativa. Isso pode ser útil em centros onde outros métodos
investigativos, como PET, SPECT, MEG ou sEEG não estão prontamente
acessíveis. / [en] In approximately one third of patients with epilepsy, surgery is the only form
of intervention to diminish seizure burden or achieve seizure freedom. In patients
without a lesional focus on MRI, surgical intervention depends on other
investigative methods, not always readily accessible. Advanced MRI
postprocessing and acquisition methods may help with lesion localization in those
cases. The aim of this systematic review was to summarize the availability and
success rate of such MRI techniques. In accordance with the PRISMA guidelines,
using PubMED, Web of Science, PsycNET, and CENTRAL, a search for papers
was performed until the 12th of January of 2021. In total, the search returned 4,024
papers, of which 49 remained after revision. Twenty-five used a form of voxelbased morphometry, 14 used machine learning techniques, and 10 used advanced
MRI sequences not commonly part of the standard MRI-protocol. Only one paper
described a prospective study. The lesion detection rate greatly varied between
studies, with machine learning techniques showing a more consistent rate, all above
50 percent in MRI-negative groups. This could be particularly helpful in center where
other investigative methods, including PET, SPECT, MEG and stereo EEG are not
readily available.
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