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首页> 外文期刊>Epilepsia: Journal of the International League against Epilepsy >A conceptual framework for the use of neuroimaging to study and predict pharmacoresistance in epilepsy.
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A conceptual framework for the use of neuroimaging to study and predict pharmacoresistance in epilepsy.

机译:使用神经影像学研究和预测癫痫药物抗药性的概念框架。

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Twenty percent to 49% of newly treated patients with epilepsy will develop pharmacoresistance (PR). The mechanisms leading to PR are unclear. There is currently no unifying theory to explain the variety of presentations of PR and the diversity of potential contributing factors. Etiology of seizures seems to play a critical role in at least a subset of PR. Many magnetic resonance imaging (MRI) studies in the advanced stages of epilepsy suggest a strong association between lesions such as hippocampal sclerosis and focal cortical dysplasia and PR. Unfortunately, almost all of these studies are cross-sectional and retrospective. There is a need for a new perspective on the role of preexisting lesions in the evolution of epilepsy and PR. We propose in this article to study a unique population of drug-naive patients with either first seizure or new-onset epilepsy longitudinally with advanced MRI imaging techniques, including magnetic resonance spectroscopy and diffusion tensor imaging. We hope to be able to monitor imaging findings and the development of PR early in the course of the disease in a subset of these patients with temporal lobe epilepsy (TLE). Our goal is to understand the pathogenesis of PR, to dissect changes associated with the development of PR from changes associated with chronic seizures and medication, and ultimately to predict PR at the onset of disease.
机译:在新治疗的癫痫患者中,有20%至49%会发展成药物抗药性(PR)。导致PR的机制尚不清楚。当前没有统一的理论来解释PR的表现形式和潜在影响因素的多样性。癫痫的病因似乎在至少一部分PR中起关键作用。癫痫晚期的许多磁共振成像(MRI)研究表明,诸如海马硬化和局灶性皮质发育不良和PR之类的病变之间有很强的联系。不幸的是,几乎所有这些研究都是横断面的和回顾性的。对于先前存在的病变在癫痫和PR演变中的作用,需要一个新的观点。我们在本文中建议使用先进的MRI成像技术(包括磁共振波谱和弥散张量成像)纵向研究首次吸毒或初发癫痫的独特药物人群。我们希望能够在这些疾病的一部分颞叶癫痫(TLE)患者的病程中早期监测影像学发现和PR的发展。我们的目标是了解PR的发病机理,从与慢性癫痫发作和药物治疗相关的变化中剖析与PR的发展相关的变化,并最终在疾病发作时预测PR。

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