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阿尔茨海默病中海马萎缩率:自动分割变异性分析。

Hippocampal atrophy rates in Alzheimer's disease: automated segmentation variability analysis.

机构信息

Centre de Recherche Université Laval Robert-Giffard, 2601 de la Canadière, Québec, Canada G1J 2G3.

出版信息

Neurosci Lett. 2011 May 9;495(1):6-10. doi: 10.1016/j.neulet.2011.02.065. Epub 2011 Mar 1.

Abstract

Hippocampal (HC) atrophy and atrophy rates are putative clinical markers of progression to Alzheimer's disease (AD). We compared results given by two different automated HC segmentation techniques in the Alzheimer's Disease Neuroimaging Initiative dataset between two time intervals. We used HC volumetric automated segmentation data for a total of 683 patients at baseline (198 controls, 331 with mild cognitive impairment (MCI) and 154 with AD), 684 at 6 months (198 controls, 332 with MCI and 154 with AD) and 587 at 12 months (176 controls, 280 with MCI and 131 with AD). Segmentation techniques included FreeSurfer and SNT. We calculated HC monthly atrophy rates between baseline and 6 months and between 6 and 12 months, and used a multiple-way ANOVA for repeated measures. Mean HC volumes decrease with time. The only significant (p<0.05) main effect was diagnosis. We measured strong interaction between technique and scan interval and weak interaction between diagnoses and scan interval. When compared to mean rates from largely manual segmentation, automated segmentation results show increased atrophy rates for both SNT and FreeSurfer techniques. While sensitive, there remains substantial technique variability, likely due to differences in methodological approaches and especially neuroanatomical HC definitions. These fundamental metrological problems need to be resolved before concluding with certainty on the accuracy and reliability of automated techniques.

摘要

海马体(HC)萎缩和萎缩率是阿尔茨海默病(AD)进展的潜在临床标志物。我们在阿尔茨海默病神经影像学倡议(Alzheimer's Disease Neuroimaging Initiative)数据集的两个时间间隔内比较了两种不同的自动 HC 分割技术给出的结果。我们使用 HC 容积自动分割数据,共纳入了 683 名基线期患者(198 名对照,331 名轻度认知障碍(MCI)患者和 154 名 AD 患者),684 名 6 个月期患者(198 名对照,332 名 MCI 患者和 154 名 AD 患者)和 587 名 12 个月期患者(176 名对照,280 名 MCI 患者和 131 名 AD 患者)。分割技术包括 FreeSurfer 和 SNT。我们计算了基线至 6 个月和 6 至 12 个月期间 HC 的每月萎缩率,并使用重复测量的多因素方差分析。HC 体积随时间而减少。唯一具有显著意义(p<0.05)的主要效应是诊断。我们测量了技术和扫描间隔之间的强交互作用以及诊断和扫描间隔之间的弱交互作用。与主要依靠手动分割的平均率相比,自动分割结果显示 SNT 和 FreeSurfer 技术的萎缩率均有所增加。尽管敏感性较高,但仍存在大量技术差异,这可能是由于方法学方法的差异,尤其是神经解剖学 HC 定义的差异所致。在确定自动技术的准确性和可靠性之前,需要解决这些基本的计量学问题。

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