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Imaging structural and functional brain networks in temporal lobe epilepsy

机译:颞叶癫痫的结构和功能性大脑网络成像

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摘要

Early imaging studies in temporal lobe epilepsy (TLE) focused on the search for mesial temporal sclerosis, as its surgical removal results in clinically meaningful improvement in about 70% of patients. Nevertheless, a considerable subgroup of patients continues to suffer from post-operative seizures. Although the reasons for surgical failure are not fully understood, electrophysiological and imaging data suggest that anomalies extending beyond the temporal lobe may have negative impact on outcome. This hypothesis has revived the concept of human epilepsy as a disorder of distributed brain networks. Recent methodological advances in non-invasive neuroimaging have led to quantify structural and functional networks in vivo. While structural networks can be inferred from diffusion MRI tractography and inter-regional covariance patterns of structural measures such as cortical thickness, functional connectivity is generally computed based on statistical dependencies of neurophysiological time-series, measured through functional MRI or electroencephalographic techniques. This review considers the application of advanced analytical methods in structural and functional connectivity analyses in TLE. We will specifically highlight findings from graph-theoretical analysis that allow assessing the topological organization of brain networks. These studies have provided compelling evidence that TLE is a system disorder with profound alterations in local and distributed networks. In addition, there is emerging evidence for the utility of network properties as clinical diagnostic markers. Nowadays, a network perspective is considered to be essential to the understanding of the development, progression, and management of epilepsy.
机译:颞叶癫痫(TLE)的早期影像学研究侧重于寻找颞叶内侧硬化,因为其手术切除可在约70%的患者中产生具有临床意义的改善。尽管如此,仍有相当一部分患者继续遭受术后癫痫发作的折磨。尽管尚不能完全理解手术失败的原因,但电生理和影像学数据表明,超出颞叶的异常可能对预后产生负面影响。该假设使人癫痫病成为分布式脑网络疾病的概念得以复兴。非侵入性神经成像的最新方法学进展已导致量化体内的结构和功能网络。虽然可以从扩散MRI束层摄影术和结构性测量的区域间协方差模式(例如皮质厚度)推断出结构网络,但功能连通性通常是根据神经生理学时间序列的统计依赖性来计算的,并通过功能性MRI或脑电图技术进行测量。这篇评论考虑了高级分析方法在TLE的结构和功能连接分析中的应用。我们将特别强调来自图论分析的发现,这些发现可以评估大脑网络的拓扑结构。这些研究提供了令人信服的证据,表明TLE是一种系统疾病,在本地和分布式网络中发生了深刻的变化。另外,新兴的证据表明网络特性可作为临床诊断标记。如今,网络角度被认为对于理解癫痫的发生,发展和管理至关重要。

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