Department of Psychiatry and Psychotherapy, Heinrich-Heine University, Duesseldorf, Germany.
Eur J Neurol. 2010 Dec;17(12):1437-44. doi: 10.1111/j.1468-1331.2010.03038.x.
Earlier evidence indicates that regional cerebral volume (rVOL) and blood flow (rCBF) variables carry independent information on incipient and early Alzheimer's disease (AD) and combining these modalities may increase discriminant performance. We compared single variables and combinations regarding their power for optimizing diagnostic accuracy.
Twelve cognitively normal elderly controls (CN), 30 subjects with mild cognitive impairment (MCI) and 15 with mild AD were examined by structural and perfusion-weighted magnetic resonance imaging (MRI) in single sessions at 1.5 Tesla. rVOLs were measured by manual volumetry, and rCBFs were calculated with a ROI-based co-localization technique.
Applying single MRI variables for the differentiation of AD versus CN, the area under curve (AUC) of receiver operating characteristic curves (ROCCs) was highest for rVOL variables (maximum of 0.972 for right amygdala). A composite marker selected and weighted by logistic regression containing left amygdalar rCBF, left hippocampal and right amygdalar rVOLs gave a diagnostic accuracy for AD versus CN of 100%. Internal cross-validation revealed a reliability of 88.9%.
Whilst external revalidation is mandatory employing a naturalistic sample containing disease controls, our phase I/II findings demonstrate that deducing composite markers from multimodal MRI acquisitions can optimize diagnostic accuracy for AD.
早期证据表明，区域性脑容量(rVOL)和血流(rCBF)变量对早期阿尔茨海默病(AD)具有独立的信息，结合这些模式可能会提高判别性能。我们比较了单一变量和组合变量，以优化诊断准确性。
12 名认知正常的老年人对照者(CN)、30 名轻度认知障碍者(MCI)和 15 名轻度 AD 患者在 1.5T 磁共振成像(MRI)单次检查中接受结构和灌注加权 MRI 检查。rVOL 通过手动容积测量进行测量，rCBF 通过基于 ROI 的共定位技术进行计算。
在 AD 与 CN 之间的鉴别中应用单一 MRI 变量，ROC 曲线的曲线下面积(AUC)最高的是 rVOL 变量(右侧杏仁核最高为 0.972)。通过逻辑回归选择和加权的复合标记物包含左侧杏仁核 rCBF、左侧海马体和右侧杏仁核 rVOL，对 AD 与 CN 的诊断准确性为 100%。内部交叉验证的可靠性为 88.9%。
虽然需要采用包含疾病对照的自然样本进行外部验证，但我们的 I/II 期研究结果表明，从多模态 MRI 采集推导出复合标记物可以优化 AD 的诊断准确性。
