使用Z-score参数F-18 FDG PET图像的计算机辅助侧化单侧颞叶癫痫。

Ching-Yee Oliver Wong, James Gannon, Jeffrey Bong, Christiana O Wong, Gopal B Saha
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引用次数: 1

摘要

背景:评价利用z-score参数化PET成像(ZPET)对颞叶癫痫(TLE)进行无偏计算机辅助侧化的应用。方法:38例组织学证实的单纯海马硬化单侧TLE患者,在5年期间接受术前PET评估顽固性癫痫发作。F-18 FDG图像沿时间长轴定向,逐体素转换成ZPET图像。在38例完全无癫痫发作(I类)结果的患者中,28例患者的皮质、皮质下和小脑结构上放置了多个感兴趣的区域(共21个)。使用配对t检验和Bonferroni校正来确定最不对称区域的位置,作为随后对整个患者组进行判别分析的变量。结果:计算机程序识别出I类TLE患者颞叶前半部分(p < 0.0005)和丘脑(p = 0.021)是最不对称的区域。使用来自这些结构的总共8个roi(4对)的z分数进行判别分析,正确地侧向化了38名患者中的37名(97%)(敏感性= 94%;特异性= 100%)。唯一的错误定位来自一个颞叶z分数不明确的病人,这个病人的结果很差。结论:利用ZPET进行计算机辅助TLE侧化是一种准确、快速、客观的癫痫发作评价方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Computer-assisted lateralization of unilateral temporal lobe epilepsy using Z-score parametric F-18 FDG PET images.

Computer-assisted lateralization of unilateral temporal lobe epilepsy using Z-score parametric F-18 FDG PET images.

Computer-assisted lateralization of unilateral temporal lobe epilepsy using Z-score parametric F-18 FDG PET images.

Computer-assisted lateralization of unilateral temporal lobe epilepsy using Z-score parametric F-18 FDG PET images.

Background: To evaluate the use of unbiased computer-assisted lateralization of temporal lobe epilepsy (TLE) by z-score parametric PET imaging (ZPET).

Methods: 38 patients with histologically proven unilateral TLE due to pure hippocampal sclerosis, referred for pre-surgical PET evaluation of intractable seizure over a 5-year period, were included. The F-18 FDG images were oriented along temporal long axis and then transformed into ZPET images on a voxel by voxel basis. Multiple regions of interests (21 in total) were placed on cortical, subcortical and cerebellar structures on twenty-eight out of 38 patients with totally seizure-free (class I) outcome. Paired t-tests with Bonferroni correction were used to determine the location of the most asymmetric regions as variables for subsequent discriminant analysis of the entire group of the patients.

Results: The computer program identified the anterior half of the temporal lobe (p < 0.0005) and thalami (p = 0.021) as the most asymmetric regions in TLE patients with Class I outcome. Discriminant analysis using z-scores from a total of 8 ROIs (in 4 pairs) on these structures correctly lateralized thirty-seven out of 38 (97%) patients (sensitivity = 94%; specificity = 100%). The only false localization came from a patient with equivocal z-scores on the temporal lobes and this patient turned out to have poor outcome.

Conclusion: The computer-assisted lateralization of TLE using ZPET provides an accurate, fast and objective way of seizure evaluation.

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