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定量多腔室 SPECT 图像分析在颞叶癫痫侧化中的应用。

Quantitative multi-compartmental SPECT image analysis for lateralization of temporal lobe epilepsy.

机构信息

Department of Diagnostic Radiology, Henry Ford Hospital, One Ford Place, Detroit, MI 48202, USA.

出版信息

Epilepsy Res. 2011 Jun;95(1-2):35-50. doi: 10.1016/j.eplepsyres.2011.02.011. Epub 2011 Mar 30.

Abstract

This study assesses the utility of compartmental analysis of SPECT data in lateralizing ictal onset in cases of a putative mesial temporal lobe epilepsy (mTLE). An institutional archival review provided 46 patients (18M, 28F) operated for a putative mTLE who achieved an Engel class Ia postoperative outcome. This established the standard to assure a true ictal origin. Ictal and interictal SPECT images were separately coregistered to T1-weighted (T1W) magnetic resonance (MR) image using a rigid transformation and the intensities matched with an l(1) norm minimization technique. The T1W MR image was segmented into separate structures using an atlas-based automatic segmentation technique with the hippocampi manually segmented to improve accuracy. Mean ictal-interictal intensity difference values were calculated for select subcortical structures and the accuracy of lateralization evaluated using a linear classifier. Hippocampal SPECT analysis yielded the highest lateralization accuracy (91%) followed by the amygdala (87%), putamen (67%) and thalamus (61%). Comparative FLAIR and volumetric analyses yielded 89% and 78% accuracies, respectively. A multi-modality analysis did not generate a higher accuracy (89%). A quantitative anatomically compartmented approach to SPECT analysis yields a particularly high lateralization accuracy in the case of mTLE comparable to that of quantitative FLAIR MR imaging. Hippocampal segmentation in this regard correlates well with ictal origin and shows good reliability in the preoperative analysis.

摘要

本研究评估了 SPECT 数据的房室分析在假定颞叶内侧癫痫(mTLE)病例中偏侧化发作起始的效用。机构档案回顾提供了 46 例(18 名男性,28 名女性)接受假定 mTLE 手术且术后获得 Engel 分类 Ia 结果的患者。这确立了确保真正发作起源的标准。使用刚性变换将发作期和发作间期 SPECT 图像分别与 T1 加权(T1W)磁共振(MR)图像配准,并使用 l(1)范数最小化技术匹配强度。使用基于图谱的自动分割技术将 T1W MR 图像分割成单独的结构,并手动分割海马以提高准确性。为选定的皮质下结构计算发作期-发作间期强度差值的平均值,并使用线性分类器评估偏侧化的准确性。海马 SPECT 分析的偏侧化准确性最高(91%),其次是杏仁核(87%)、壳核(67%)和丘脑(61%)。比较 FLAIR 和容积分析分别产生 89%和 78%的准确性。多模态分析未产生更高的准确性(89%)。SPECT 分析的定量解剖分区方法在 mTLE 病例中产生了特别高的偏侧化准确性,与定量 FLAIR MR 成像相当。在这方面,海马分割与发作起源密切相关,并在术前分析中具有良好的可靠性。

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