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局灶性癫痫患者发作间期头皮 EEG 分布式源模型的临床应用。

Clinical utility of distributed source modelling of interictal scalp EEG in focal epilepsy.

机构信息

Centre for Clinical Neurosciences and Neurological Research, St. Vincent's Hospital, 5th Floor Daly Wing, 35 Victoria Parade, Fitzroy, Victoria 3065, Australia.

出版信息

Clin Neurophysiol. 2010 Oct;121(10):1726-39. doi: 10.1016/j.clinph.2010.04.002. Epub 2010 May 8.

Abstract

OBJECTIVE

Assess the clinical utility of non-invasive distributed EEG source modelling in focal epilepsy.

METHODS

Interictal epileptiform discharges were recorded from eight patients - benign focal epilepsy of childhood (BFEC), four; mesial temporal lobe epilepsy (MTLE), four. EEG source localization (ESL) applied 48 forward-inverse-subspace set-ups: forward - standardized, leadfield-interpolated boundary element methods (BEMs, BEMi), finite element method (FEMi); inverse - minimum norm (MNLS), L1 norm (L1), low resolution electromagnetic tomography (LORETA), standardized LORETA (sLORETA); subspace- whole volume (3D), cortex with rotating sources (CxR), cortex with fixed sources (CxN), cortex with fixed extended sources (patch). Current density reconstruction (CDR) maxima defined 'best-fit'.

RESULTS

From 19,200 CDR parameter results and 2304 CDR maps, the dominant variables on best-fit were inverse model and subspace constraint. The most clinically meaningful and statistically robust results came with sLORETA-CxR/patch (lower Rolandic in BFEC, basal temporal lobe in MTLE). Computation time was inverse model dependent: sub-second (MNLS, sLORETA), seconds (L1), minutes (LORETA).

CONCLUSIONS

From the largest number of distributed ESL approaches compared in a clinical setting, an optimum modelling set-up for BFEC and MTLE incorporated sLORETA (inverse), CxR or patch (subspace), and either BEM or FEMi (forward). Computation is efficient and CDR results are reproducible.

SIGNIFICANCE

Distributed source modelling demonstrates clinical utility for the routine work-up of unilateral BFEC of the typical Rolandic variety, and unilateral MTLE secondary to hippocampal sclerosis.

摘要

目的

评估非侵入性分布式 EEG 源建模在局灶性癫痫中的临床实用性。

方法

从 8 名患者中记录发作间期癫痫样放电 - 良性儿童局灶性癫痫(BFEC),4 例;内侧颞叶癫痫(MTLE),4 例。脑电图源定位(ESL)应用 48 个正向-逆向子空间设置:正向 - 标准化,导联内插边界元方法(BEM,BEMi),有限元方法(FEMi);逆向 - 最小范数(MNLS),L1 范数(L1),低分辨率电磁层析成像(LORETA),标准化 LORETA(sLORETA);子空间 - 整个体积(3D),旋转源皮层(CxR),固定源皮层(CxN),固定扩展源皮层(补丁)。电流密度重建(CDR)最大值定义为“最佳拟合”。

结果

从 19200 个 CDR 参数结果和 2304 个 CDR 图谱中,最佳拟合的主要变量是逆向模型和子空间约束。最具临床意义和统计学稳健的结果来自 sLORETA-CxR/patch(BFEC 较低的 Rolandic,MTLE 基底颞叶)。计算时间取决于逆向模型:亚秒(MNLS,sLORETA),秒(L1),分钟(LORETA)。

结论

从临床环境中比较的最大数量的分布式 ESL 方法中,BFEC 和 MTLE 的最佳建模设置包括 sLORETA(逆向)、CxR 或补丁(子空间)以及 BEM 或 FEMi(正向)。计算高效,CDR 结果可重复。

意义

分布式源建模证明了在典型 Rolandic 类型的单侧 BFEC 和海马硬化引起的单侧 MTLE 的常规工作中具有临床实用性。

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