Integration of Cognitive Tests and Resting State fMRI for the Individual Identification of Mild Cognitive Impairment
Integration of Cognitive Tests and Resting State fMRI for the Individual Identification of Mild Cognitive Impairment
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DOI：
10.2174/156720501206150716120332
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发表时间：
2015-01-01
影响因子：
2.1
通讯作者：
Venneri, Annalena
中科院分区：
文献类型：
--
作者：
Beltrachini, Leandro;De Marco, Matteo;Venneri, Annalena
背景：静息态功能磁共振成像（RS-fMRI）似乎是一种有前景的成像技术，可用于识别阿尔茨海默型神经变性的早期生物标志物，与结构改变相比，它可以更灵敏地检测这种疾病的最早阶段。最近的研究结果强调了阿尔茨海默病轻度认知障碍（MCI）前驱阶段静息态活动的有趣变化模式。然而，尚未确定 RS-fMRI 的改变是否可以在个体患者水平上具有任何诊断用途，以及源自 RS-fMRI 图像的参数是否为标准认知测试 (CT) 添加任何定量预测/分类价值。方法：我们基于 RS-fMRI 计算了一组 444 个特征，并使用了从 29 名 MCI 患者和 21 名健康对照者的神经心理学评估测试中获得的 21 个变量。我们通过机器学习算法和 10 倍交叉验证分析，使用这些指数来评估它们对 MCI/健康控制分类的影响。结果：使用两组指数时，分类准确度（敏感性/特异性/曲线下面积/阳性预测值/阴性预测值）为 0.9559 (0.9620/0.9470/0.9517/0.9720/0.9628)。与仅使用 CT 相比，有统计学上的显着改善，凸显了 RS-fMRI 的优越分类作用。结论：RS-fMRI 为 MCI 患者/健康对照个体分类提供了 CT 的补充信息。
Background: Resting-state functional magnetic resonance imaging (RS-fMRI) appears as a promising imaging technique to identify early biomarkers of Alzheimer type neurodegeneration, which can be more sensitive to detect the earliest stages of this disease than structural alterations. Recent findings have highlighted interesting patterns of alteration in resting-state activity at the mild cognitive impairment (MCI) prodromal stage of Alzheimer's disease. However, it has not been established whether RS-fMRI alterations may be of any diagnostic use at the individual patient level and whether parameters derived from RS-fMRI images add any quantitative predictive/classificatory value to standard cognitive tests (CTs). Methods: We computed a set of 444 features based on RS-fMRI and used 21 variables obtained from a neuropsychological assessment battery of tests in 29 MCI patients and 21 healthy controls. We used these indices to evaluate their impact on MCI/healthy control classification using machine learning algorithms and a 10-fold cross validation analysis. Results: A classification accuracy (sensitivity/specificity/area under curve/positive predictive value/negative predictive value) of 0.9559 (0.9620/0.9470/0.9517/0.9720/0.9628) was achieved when using both sets of indices. There was a statistically significant improvement over the use of CTs only, highlighting the superior classificatory role of RS-fMRI. Conclusions: RS-fMRI provides complementary information to CTs for MCI-patient/healthy control individual classification.