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比较轻度认知障碍和早期阿尔茨海默病中海马体积的手动和自动测定。

Comparison of manual and automated determination of hippocampal volumes in MCI and early AD.

机构信息

IU Center for Neuroimaging, Div. of Imaging Sciences, Dept. of Radiology, Indiana University School of Medicine, 950 W Walnut St., R2 E124, Indianapolis, IN 46202, USA.

出版信息

Brain Imaging Behav. 2010 Mar;4(1):86-95. doi: 10.1007/s11682-010-9088-x.

Abstract

MRI-based hippocampal volume analysis has been extensively employed given its potential as a biomarker for brain disorders such as Alzheimer's disease (AD), and accurate and efficient determination of hippocampal volumes from brain images is still a challenging issue. We compared an automated method, FreeSurfer (V4), with a published manual protocol for the determination of hippocampal volumes from T1-weighted MRI scans. Our study included MRI data from 125 older adult subjects: healthy controls with no significant cognitive complaints or deficits (HC, n=38), euthymic individuals with cognitive complaints (CC, n=39) but intact neuropsychological performance, and patients with amnestic mild cognitive impairment (MCI, n=37) or a clinical diagnosis of probable AD (AD, n=11). Pearson correlations and intraclass correlation coefficients (ICCs) were calculated to evaluate the relationship between results of the manual tracing and FreeSurfer methods and to estimate their agreement. Results indicated that these two methods derived highly correlated results with strong agreement. After controlling for the age, sex and intracranial volume in statistical group analysis, both the manual tracing and FreeSurfer methods yield similar patterns: both the MCI group and the AD group showed hippocampal volume reduction compared to both the HC group and the CC group, and the HC and CC groups did not differ. These comparisons suggest that FreeSurfer has the potential to be used in automated determination of hippocampal volumes for large-scale MCI/AD-related MRI studies, where manual methods are inefficient or not feasible.

摘要

基于 MRI 的海马体积分析因其可能作为阿尔茨海默病 (AD) 等脑部疾病的生物标志物而得到广泛应用,而从脑部图像准确、高效地确定海马体积仍然是一个具有挑战性的问题。我们比较了一种自动化方法 FreeSurfer (V4) 和一种已发表的手动方法,以确定 T1 加权 MRI 扫描中海马体积。我们的研究包括 125 名老年受试者的 MRI 数据:无明显认知主诉或缺陷的健康对照者 (HC,n=38)、有认知主诉但神经心理学表现正常的心境正常个体 (CC,n=39)、以及有遗忘型轻度认知障碍 (MCI,n=37) 或临床诊断为可能 AD (AD,n=11) 的患者。我们计算了 Pearson 相关系数和组内相关系数 (ICC),以评估手动追踪和 FreeSurfer 方法结果之间的关系,并估计它们的一致性。结果表明,这两种方法得出的结果高度相关,具有很强的一致性。在统计组分析中控制年龄、性别和颅内体积后,手动追踪和 FreeSurfer 方法得出的结果模式相似:MCI 组和 AD 组的海马体积均较 HC 组和 CC 组减少,而 HC 组和 CC 组之间没有差异。这些比较表明,FreeSurfer 有可能用于自动确定大规模 MCI/AD 相关 MRI 研究中的海马体积,在这些研究中,手动方法效率低下或不可行。

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