The Effect of Age Correction on Multivariate Classification in Alzheimer's Disease, with a Focus on the Characteristics of Incorrectly and Correctly Classified Subjects.
The Effect of Age Correction on Multivariate Classification in Alzheimer's Disease, with a Focus on the Characteristics of Incorrectly and Correctly Classified Subjects.
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DOI：
10.1007/s10548-015-0455-1
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发表时间：
2016-03
期刊：
影响因子：
2.7
通讯作者：
AddNeuroMed consortium and the Alzheimer’s Disease Neuroimaging Initiative
中科院分区：
文献类型：
--
作者：
Falahati F;Ferreira D;Soininen H;Mecocci P;Vellas B;Tsolaki M;Kłoszewska I;Lovestone S;Eriksdotter M;Wahlund LO;Simmons A;Westman E;AddNeuroMed consortium and the Alzheimer’s Disease Neuroimaging Initiative
阿尔茨海默病（AD）和正常衰老中萎缩模式的相似性表明，在使用结构磁共振成像（MRI）数据的多变量模型中，年龄是一个混杂因素。研究不同年龄校正方法对AD诊断和轻度认知功能损害（MCI）进展预测的影响，并探讨正确分类和错误分类受试者的特点。研究中纳入了来自两个多中心队列的数据[AD = 297，MCI = 445，对照（CTL）= 340]。从MRI中提取了34个皮质厚度和21个皮质下体积测量值。年龄校正方法包括：使用年龄作为MRI衍生测量的协变量，并基于CTL测量对年龄相关变化进行线性去趋势。对潜在结构的正交投影用于区分AD和CTL受试者，并预测MCI进展为AD，长达36个月的随访。这两种年龄校正方法都提高了模型在拟合优度和预测优度以及分类和预测准确性方面的质量。年龄校正后，有效地消除了分类和预测结果中观察到的年龄关联。对正确和错误分类的受试者的详细分析突出了其他因素的年龄相关性：ApoE基因型，整体认知障碍和性别。两种年龄校正方法的结果相似，表明年龄可以部分掩盖其他方面的影响，如认知障碍，ApoE-e4基因型和性别。与脑萎缩相关的脑萎缩与这些因素的关系可能比以前认为的更重要。本文的在线版本（doi：10.1007/s10548-015-0455-1）包含补充材料，可供授权用户使用。
The similarity of atrophy patterns in Alzheimer’s disease (AD) and in normal aging suggests age as a confounding factor in multivariate models that use structural magnetic resonance imaging (MRI) data. To study the effect and compare different age correction approaches on AD diagnosis and prediction of mild cognitive impairment (MCI) progression as well as investigate the characteristics of correctly and incorrectly classified subjects. Data from two multi-center cohorts were included in the study [AD = 297, MCI = 445, controls (CTL) = 340]. 34 cortical thickness and 21 subcortical volumetric measures were extracted from MRI. The age correction approaches involved: using age as a covariate to MRI-derived measures and linear detrending of age-related changes based on CTL measures. Orthogonal projections to latent structures was used to discriminate between AD and CTL subjects, and to predict MCI progression to AD, up to 36-months follow-up. Both age correction approaches improved models’ quality in terms of goodness of fit and goodness of prediction, as well as classification and prediction accuracies. The observed age associations in classification and prediction results were effectively eliminated after age correction. A detailed analysis of correctly and incorrectly classified subjects highlighted age associations in other factors: ApoE genotype, global cognitive impairment and gender. The two methods for age correction gave similar results and show that age can partially masks the influence of other aspects such as cognitive impairment, ApoE-e4 genotype and gender. Age-related brain atrophy may have a more important association with these factors than previously believed. The online version of this article (doi:10.1007/s10548-015-0455-1) contains supplementary material, which is available to authorized users.