Department of Psychology, CSHC, University of Oslo, Oslo, Norway.
AJNR Am J Neuroradiol. 2010 Feb;31(2):347-54. doi: 10.3174/ajnr.A1809. Epub 2010 Jan 14.
Different biomarkers for AD may potentially be complementary in diagnosis and prognosis of AD. Our aim was to combine MR imaging, FDG-PET, and CSF biomarkers in the diagnostic classification and 2-year prognosis of MCI and AD, by examining the following: 1) which measures are most sensitive to diagnostic status, 2) to what extent the methods provide unique information in diagnostic classification, and 3) which measures are most predictive of clinical decline.
ADNI baseline MR imaging, FDG-PET, and CSF data from 42 controls, 73 patients with MCI, and 38 patients with AD; and 2-year clinical follow-up data for 36 controls, 51 patients with MCI, and 25 patients with AD were analyzed. The hippocampus and entorhinal, parahippocampal, retrosplenial, precuneus, inferior parietal, supramarginal, middle temporal, lateral, and medial orbitofrontal cortices were used as regions of interest. CSF variables included Abeta42, t-tau, p-tau, and ratios of t-tau/Abeta42 and p-tau/Abeta42. Regression analyses were performed to determine the sensitivity of measures to diagnostic status as well as 2-year change in CDR-SB, MMSE, and delayed logical memory in MCI.
Hippocampal volume, retrosplenial thickness, and t-tau/Abeta42 uniquely predicted diagnostic group. Change in CDR-SB was best predicted by retrosplenial thickness; MMSE, by retrosplenial metabolism and thickness; and delayed logical memory, by hippocampal volume.
All biomarkers were sensitive to the diagnostic group. Combining MR imaging morphometry and CSF biomarkers improved diagnostic classification (controls versus AD). MR imaging morphometry and PET were largely overlapping in value for discrimination. Baseline MR imaging and PET measures were more predictive of clinical change in MCI than were CSF measures.
不同的 AD 生物标志物在 AD 的诊断和预后中可能具有互补作用。我们的目的是通过检查以下内容，将 MRI、FDG-PET 和 CSF 生物标志物结合起来，用于 MCI 和 AD 的诊断分类和 2 年预后：1）哪些指标对诊断状态最敏感，2）这些方法在诊断分类中提供了多少独特的信息，3）哪些指标对临床衰退最具预测性。
对 42 名对照者、73 名 MCI 患者和 38 名 AD 患者的 ADNI 基线 MRI、FDG-PET 和 CSF 数据以及 36 名对照者、51 名 MCI 患者和 25 名 AD 患者的 2 年临床随访数据进行了分析。海马体和内嗅皮质、海马旁回、后扣带回、楔前叶、下顶叶、缘上回、颞中回、外侧和内侧眶额皮质被用作感兴趣区。CSF 变量包括 Abeta42、t-tau、p-tau 以及 t-tau/Abeta42 和 p-tau/Abeta42 的比值。进行回归分析以确定各指标对诊断状态的敏感性以及 MCI 中 CDR-SB、MMSE 和延迟逻辑记忆的 2 年变化。
海马体体积、后扣带回厚度和 t-tau/Abeta42 可独特预测诊断组。CDR-SB 的变化主要由后扣带回厚度预测；MMSE 由后扣带回代谢和厚度预测；而延迟逻辑记忆由海马体体积预测。
所有生物标志物均对诊断组敏感。将 MRI 形态计量学和 CSF 生物标志物相结合可改善诊断分类（对照组与 AD）。MRI 形态计量学和 PET 在区分方面具有很大的重叠价值。与 CSF 测量值相比，基线 MRI 和 PET 测量值对 MCI 患者的临床变化更具预测性。
