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使用颞叶癫痫模型评估自动检测不同脑萎缩方面的方法学选择的影响。

Impact of methodologic choice for automatic detection of different aspects of brain atrophy by using temporal lobe epilepsy as a model.

机构信息

Center for Imaging of Neurodegenerative Diseases and Department of Radiology, University of California-San Francisco, CA, USA.

出版信息

AJNR Am J Neuroradiol. 2011 Oct;32(9):1669-76. doi: 10.3174/ajnr.A2578. Epub 2011 Aug 18.

Abstract

BACKGROUND AND PURPOSE

VBM, DBM, and cortical thickness measurement techniques are commonly used automated methods to detect structural brain changes based on MR imaging. The goal of this study was to demonstrate the pathology detected by the 3 methods and to provide guidance as to which method to choose for specific research questions. This goal was accomplished by 1) identifying structural abnormalities associated with TLE with (TLE-mts) and without (TLE-no) hippocampal sclerosis, which are known to be associated with different types of brain atrophy, by using these 3 methods; and 2) determining the aspect of the disease pathology identified by each method.

MATERIALS AND METHODS

T1-weighted MR images were acquired for 15 TLE-mts patients, 14 TLE-no patients, and 33 controls on a high-field 4T scanner. Optimized VBM was carried out by using SPM software, DBM was performed by using a fluid-flow registration algorithm, and cortical thickness was analyzed by using FS-CT.

RESULTS

In TLE-mts, the most pronounced volume losses were identified in the ipsilateral hippocampus and mesial temporal region, bilateral thalamus, and cerebellum, by using SPM-VBM and DBM. In TLE-no, the most widespread changes were cortical and identified by using FS-CT, affecting the bilateral temporal lobes, insula, and frontal and occipital lobes. DBM revealed 2 clusters of reduced volume complementing FS-CT analysis. SPM-VBM did not show any significant volume losses in TLE-no.

CONCLUSIONS

These results demonstrate that the 3 methods detect different aspects of brain atrophy and that the choice of the method should be guided by the suspected pathology of the disease.

摘要

背景与目的

VBM、DBM 和皮质厚度测量技术是常用于基于 MRI 检测结构脑变化的自动方法。本研究的目的是展示 3 种方法检测到的病理学,并为特定研究问题提供选择方法的指导。通过以下方式实现这一目标:1)通过使用这 3 种方法,识别与海马硬化(TLE-mts)和无海马硬化(TLE-no)相关的 TLE 患者的结构异常,已知它们与不同类型的脑萎缩相关;2)确定每种方法识别的疾病病理学的方面。

材料和方法

在一台高场 4T 扫描仪上,为 15 名 TLE-mts 患者、14 名 TLE-no 患者和 33 名对照者采集 T1 加权 MR 图像。使用 SPM 软件进行优化 VBM,使用流体流动配准算法进行 DBM,使用 FS-CT 进行皮质厚度分析。

结果

在 TLE-mts 中,SPM-VBM 和 DBM 均显示同侧海马体和内侧颞叶区域、双侧丘脑和小脑的体积损失最为明显。在 TLE-no 中,FS-CT 显示最广泛的变化为皮质变化,影响双侧颞叶、脑岛以及额顶叶。DBM 揭示了 2 个体积减少的簇,补充了 FS-CT 分析。TLE-no 中 SPM-VBM 未显示任何显著的体积损失。

结论

这些结果表明,3 种方法检测到不同方面的脑萎缩,并且应根据疾病的可疑病理学来选择方法。

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