摘要
背景:静息态功能磁共振成像(RS-fMRI)出现作为一种很有前途的成像技术可鉴别阿尔茨海默型神经退行性疾病。该技术可检测这种疾病的早期阶段比结构的改变更敏感。最近研究发现在轻度认知障碍发现有趣状态,变更(MCI)阿尔茨海默病的前驱期的静息状态的活性。然而,它已经不作为是否RS-fMRI的改变可能是任何在个体水平和是否来自RS fMRI图像参数添加任何定量预测/分类价值标准认知测试(CTS)的诊断使用。方法:我们计算了一套基于rs-fMRI 444特征并使用21个变量从一个神经心理测试评估电池在29例MCI患者和21例健康对照。我们用这些指标来评价其对MCI/正常使用机器学习算法分类和10折交叉验证分析的影响。结果:使用这两套指标,分类精度(灵敏度/特异性/面积曲线下/阳性预测值、阴性预测值)0.9559(0.9620/0.9470/0.9517/0.9720/0.9628)是可以实现。使用CTS,有一个统计上的显着改善,突出rs-fMRI上级分类的作用。结论:RS-fMRI提供CTS MCI患者/健康对照个体的分类的补充信息。
关键词: 准确性,阿尔茨海默氏病,生物学标志,分类,轻度认知功能障碍,神经退行性变。
Current Alzheimer Research
Title:Integration of Cognitive Tests and Resting State fMRI for the Individual Identification of Mild Cognitive Impairment
Volume: 12 Issue: 6
Author(s): Leandro Beltrachini, Matteo De Marco, Zeike A. Taylor, Jyrki Lotjonen, Alejandro F. Frangi and Annalena Venneri
Affiliation:
关键词: 准确性,阿尔茨海默氏病,生物学标志,分类,轻度认知功能障碍,神经退行性变。
摘要: 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.
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Leandro Beltrachini, Matteo De Marco, Zeike A. Taylor, Jyrki Lotjonen, Alejandro F. Frangi and Annalena Venneri , Integration of Cognitive Tests and Resting State fMRI for the Individual Identification of Mild Cognitive Impairment, Current Alzheimer Research 2015; 12 (6) . https://dx.doi.org/10.2174/156720501206150716120332
DOI https://dx.doi.org/10.2174/156720501206150716120332 |
Print ISSN 1567-2050 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5828 |
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