Multivariate and univariate neuroimaging biomarkers of Alzheimer's disease
Multivariate and univariate neuroimaging biomarkers of Alzheimer's disease
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DOI：
10.1016/j.neuroimage.2008.01.056
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发表时间：
2008-05-01
期刊：
影响因子：
5.7
通讯作者：
Stern, Yaakov
中科院分区：
文献类型：
--
作者：
Habeck, Christian;Foster, Norman L.;Stern, Yaakov
我们对FDG-PET扫描进行了单变量和多变量判别分析，以评估其识别阿尔茨海默病（AD）的能力。FDG-PET扫描来自两个来源：在密歇根大学对17名AD患者和33名健康老年对照进行了扫描;在慕尼黑工业大学对102名早期AD患者和20名健康老年对照进行了扫描德国。我们选择了20例AD患者和20例年龄匹配的健康对照者作为衍生样本，其余的分为5个重复样本。在复制样本中确定诊断AD标志物的灵敏度和特异性以及来自衍生样本的阈值标准。虽然单变量和多变量分析都产生了在衍生样本中具有高分类准确性的标记物，但多变量标记物在复制样本中的诊断性能上级。此外，补充分析表明，其业绩不受关键区域损失的影响。AD的多变量测量利用成像数据的协方差结构，并提供可能上级单变量测量的互补的临床相关信息。爱思唯尔公司出版
We performed univariate and multivariate discriminant analysis of FDG-PET scans to evaluate their ability to identify Alzheimer's disease ( AD). FDG-PET scans came from two sources: 17 AD patients and 33 healthy elderly controls were scanned at the University of Michigan; 102 early AD patients and 20 healthy elderly controls were scanned at the Technical University of Munich, Germany. We selected a derivation sample of 20 AD patients and 20 healthy controls matched on age with the remainder divided into 5 replication samples. The sensitivity and specificity of diagnostic AD-markers and threshold criteria from the derivation sample were determined in the replication samples. Although both univariate and multivariate analyses produced markers with high classification accuracy in the derivation sample, the multivariate marker's diagnostic performance in the replication samples was superior. Further, supplementary analysis showed its performance to be unaffected by the loss of key regions. Multivariate measures of AD utilize the covariance structure of imaging data and provide complementary, clinically relevant information that may be superior to univariate measures. Published by Elsevier Inc.