Prediction of Progressive Mild Cognitive Impairment by Multi-Modal Neuroimaging Biomarkers
文献类型：期刊论文
| 作者 | Xu, Lele1; Wu, Xia1,2,3; Li, Rui4 ; Chen, Kewei5,6; Long, Zhiying2,3; Zhang, Jiacai1; Guo, Xiaojuan1; Yao, Li1,2,3; Alzheimer Dis Neuroimaging
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| 刊名 | JOURNAL OF ALZHEIMERS DISEASE
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| 出版日期 | 2016 |
| 卷号 | 51期号:4页码:1045-1056 |
| ISSN号 | 1387-2877 |
| 关键词 | Florbetapir positron emission tomography fluorodeoxyglucose positron emission tomography magnetic resonance imaging mild cognitive impairment multi-modality prediction progressive mild cognitive impairment |
| 英文摘要 | For patients with mild cognitive impairment (MCI), the likelihood of progression to probable Alzheimer's disease (AD) is important not only for individual patient care, but also for the identification of participants in clinical trial, so as to provide early interventions. Biomarkers based on various neuroimaging modalities could offer complementary information regarding different aspects of disease progression. The current study adopted a weighted multi-modality sparse representation-based classification method to combine data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, from three imaging modalities: Volumetric magnetic resonance imaging (MRI), fluorodeoxyglucose (FDG) positron emission tomography (PET), and florbetapir PET. We included 117 normal controls (NC) and 110 MCI patients, 27 of whom progressed to AD within 36 months (pMCI), while the remaining 83 remained stable (sMCI) over the same time period. Modality-specific biomarkers were identified to distinguish MCI from NC and to predict pMCI among MCI. These included the hippocampus, amygdala, middle temporal and inferior temporal regions for MRI, the posterior cingulum, precentral, and postcentral regions for FDG-PET, and the hippocampus, amygdala, and putamen for florbetapir PET. Results indicated that FDG-PET may be a more effective modality in discriminating MCI from NC and in predicting pMCI than florbetapir PET and MRI. Combining modality-specific sensitive biomarkers from the three modalities boosted the discrimination accuracy of MCI from NC (76.7%) and the prediction accuracy of pMCI (82.5%) when compared with the best single-modality results (73.6% for MCI and 75.6% for pMCI with FDG-PET). |
| WOS标题词 | Science & Technology ; Life Sciences & Biomedicine |
| 类目[WOS] | Neurosciences |
| 研究领域[WOS] | Neurosciences & Neurology |
| 关键词[WOS] | POSITRON-EMISSION-TOMOGRAPHY ; ALZHEIMERS-DISEASE ; FDG-PET ; SPARSE REPRESENTATION ; CSF BIOMARKERS ; AMYLOID LOAD ; MRI ; MCI ; CLASSIFICATION ; CONVERSION |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000374239300011 |
| 源URL | [http://ir.psych.ac.cn/handle/311026/19965]  |
| 专题 | 心理研究所_中国科学院心理健康重点实验室 |
| 作者单位 | 1.Beijing Normal Univ, Coll Informat Sci & Technol, 19 Xin Jie Kou Wai Da Jie, Beijing 100875, Peoples R China 2.Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China 3.Beijing Normal Univ, IDG McGovern Inst Brain Res, Beijing 100875, Peoples R China 4.Chinese Acad Sci, Inst Psychol, Key Lab Mental Hlth, Ctr Aging Psychol, Beijing 100101, Peoples R China 5.Banner Alzheimers Inst, Phoenix, AZ USA 6.Banner Good Samaritan PET Ctr, Phoenix, AZ USA |
| 推荐引用方式 GB/T 7714 | Xu, Lele,Wu, Xia,Li, Rui,et al. Prediction of Progressive Mild Cognitive Impairment by Multi-Modal Neuroimaging Biomarkers[J]. JOURNAL OF ALZHEIMERS DISEASE,2016,51(4):1045-1056. |
| APA | Xu, Lele.,Wu, Xia.,Li, Rui.,Chen, Kewei.,Long, Zhiying.,...&Alzheimer Dis Neuroimaging.(2016).Prediction of Progressive Mild Cognitive Impairment by Multi-Modal Neuroimaging Biomarkers.JOURNAL OF ALZHEIMERS DISEASE,51(4),1045-1056. |
| MLA | Xu, Lele,et al."Prediction of Progressive Mild Cognitive Impairment by Multi-Modal Neuroimaging Biomarkers".JOURNAL OF ALZHEIMERS DISEASE 51.4(2016):1045-1056. |
入库方式： OAI收割
来源：心理研究所
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