Identification of Conversion from Mild Cognitive Impairment to Alzheimer's Disease Using Multivariate Predictors
文献类型：期刊论文
| 作者 | Cui, Yue1 ; Liu, Bing2; Luo, Suhuai1; Zhen, Xiantong2; Fan, Ming2; Liu, Tao1,3,4; Zhu, Wanlin3,4; Park, Mira1; Jiang, Tianzi2,5; Jin, Jesse S.1
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| 刊名 | PLOS ONE
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| 出版日期 | 2011-07-21 |
| 卷号 | 6期号:7 |
| 英文摘要 | Prediction of conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is of major interest in AD research. A large number of potential predictors have been proposed, with most investigations tending to examine one or a set of related predictors. In this study, we simultaneously examined multiple features from different modalities of data, including structural magnetic resonance imaging (MRI) morphometry, cerebrospinal fluid (CSF) biomarkers and neuropsychological and functional measures (NMs), to explore an optimal set of predictors of conversion from MCI to AD in an Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. After FreeSurfer-derived MRI feature extraction, CSF and NM feature collection, feature selection was employed to choose optimal subsets of features from each modality. Support vector machine (SVM) classifiers were then trained on normal control (NC) and AD participants. Testing was conducted on MCIc (MCI individuals who have converted to AD within 24 months) and MCInc (MCI individuals who have not converted to AD within 24 months) groups. Classification results demonstrated that NMs outperformed CSF and MRI features. The combination of selected NM, MRI and CSF features attained an accuracy of 67.13%, a sensitivity of 96.43%, a specificity of 48.28%, and an AUC (area under curve) of 0.796. Analysis of the predictive values of MCIc who converted at different follow-up evaluations showed that the predictive values were significantly different between individuals who converted within 12 months and after 12 months. This study establishes meaningful multivariate predictors composed of selected NM, MRI and CSF measures which may be useful and practical for clinical diagnosis. |
| WOS标题词 | Science & Technology |
| 类目[WOS] | Multidisciplinary Sciences |
| 研究领域[WOS] | Science & Technology - Other Topics |
| 关键词[WOS] | DIMENSIONAL PATTERN-CLASSIFICATION ; NEUROIMAGING INITIATIVE ADNI ; HUMAN CEREBRAL-CORTEX ; CSF BIOMARKERS ; BRAIN ATROPHY ; MCI PATIENTS ; BASE-LINE ; DIAGNOSIS ; MRI ; SEGMENTATION |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000292956800014 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/3119]  |
| 专题 | 自动化研究所_脑网络组研究中心 |
| 作者单位 | 1.Univ Newcastle, Sch Design Commun & Informat Technol, Newcastle, NSW 2300, Australia 2.Chinese Acad Sci, Inst Automat, LIAMA Ctr Computat Med, Natl Lab Pattern Recognit, Beijing, Peoples R China 3.Prince Wales Hosp, Inst Neuropsychiat, Sydney, NSW, Australia 4.Univ New S Wales, Sch Psychiat, Brain & Ageing Res Program, Sydney, NSW, Australia 5.Univ Elect Sci & Technol China, Sch Life Sci & Technol, Minist Educ, Key Lab NeuroInformat, Chengdu 610054, Peoples R China |
| 推荐引用方式 GB/T 7714 | Cui, Yue,Liu, Bing,Luo, Suhuai,et al. Identification of Conversion from Mild Cognitive Impairment to Alzheimer's Disease Using Multivariate Predictors[J]. PLOS ONE,2011,6(7). |
| APA | Cui, Yue.,Liu, Bing.,Luo, Suhuai.,Zhen, Xiantong.,Fan, Ming.,...&Alzheimers Dis Neuroimaging.(2011).Identification of Conversion from Mild Cognitive Impairment to Alzheimer's Disease Using Multivariate Predictors.PLOS ONE,6(7). |
| MLA | Cui, Yue,et al."Identification of Conversion from Mild Cognitive Impairment to Alzheimer's Disease Using Multivariate Predictors".PLOS ONE 6.7(2011). |
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来源：自动化研究所
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