机构：[1]Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, China内科系统神经内科神经科系统神经内科江苏省人民医院[2]Department of Neurology, Mudanjiang Medical University Affiliated HongQi Hospital, Mudanjiang, China内科系统神经内科江苏省人民医院[3]BrainNow Research Institute, Shenzhen, Guangdong Province, China[4]Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong, China[5]Department of Psychiatry, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom[6]China-UK Centre for Cognition and Aging Research, Faculty of Psychology, Southwest University, Chongqing, China[7]Department of Radiology, XuanWu Hospital of Capital Medical University, Beijing, China医技科室放射科医技科室放射科江苏省人民医院[8]Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, Hong Kong, China医技科室介入放射科江苏省人民医院[9]Center of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China[10]Beijing Institute of Geriatrics, Beijing, China[11]National Clinical Research Center for Geriatric Disorders, Beijing, China
As an enrichment strategy supplemented by the diagnostic framework of subjective cognitive decline (SCD), SCD plus identifies features that may increase the likelihood of including future-Alzheimer's disease (AD) patients. This study aimed to identify the shared and distinct atrophy patterns between patients specified by SCD plus and amnestic mild cognitive impairment (aMCI, a prodromal stage of AD) and to investigate the extent that automated brain magnetic resonance imaging (MRI) volumetry can differentiate patients with SCD from normal control (NC) participants and patients with aMCI. We acquired structural MRI brain scans from 44 patients with aMCI, 40 patients with SCD (who met the major criteria of SCD plus), and 48 NC participants. Automatic brain segmentation was performed to quantify the volumetric measures of cognitive-relevant areas. These volumetric measures were compared across the 3 groups with analysis of variance. In addition, we performed support vector machine analyses using volumetric measures of single regions or multiple regions to further evaluate the sensitivity of automated brain volumetry in differentiating a specific group from another. The atrophy patterns in patients with aMCI and SCD were similar. Using the regional volumetric measures, we achieved high performance in differentiating aMCI and SCD from NCs (average classification accuracy [ACC] > 90%). However, the performance was not ideal when differentiating aMCI from SCD (ACC < 63%). In conclusion, patients with SCD specified by SCD plus presented similar atrophy patterns as patients with aMCI, which was distinguishable from NC participants. Future studies should aim to associate the atrophy patterns of SCD with possible conversion to aMCI or AD in a longitudinal design.
基金：
National Key Research and Development Program of China [2016YFC1306300, 2016YFC0103000]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China [31371007, 81571755, 81430037, 61633018, 6150332, 81771795, 81601454, 81522021]; Beijing Municipal Government [PXM2019_026283_000002]; Beijing Nature Science FoundationBeijing Natural Science Foundation [7161009]; Beijing Municipal Science & Technology CommissionBeijing Municipal Science & Technology Commission [Z161100002616020]; Fundamental and Clinical Cooperative Research Program of Capital Medical University [16JL-L08]
第一作者机构：[1]Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, China[2]Department of Neurology, Mudanjiang Medical University Affiliated HongQi Hospital, Mudanjiang, China
通讯作者：
通讯机构：[1]Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, China[3]BrainNow Research Institute, Shenzhen, Guangdong Province, China[8]Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, Hong Kong, China[9]Center of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China[10]Beijing Institute of Geriatrics, Beijing, China[11]National Clinical Research Center for Geriatric Disorders, Beijing, China
推荐引用方式(GB/T 7714)：
Weina Zhao,Yishan Luo,Lei Zhao,et al.Automated Brain MRI Volumetry Differentiates Early Stages of Alzheimer's Disease From Normal Aging.[J].Journal of geriatric psychiatry and neurology.2019,32(6):354-364.doi:10.1177/0891988719862637.
APA：
Weina Zhao,Yishan Luo,Lei Zhao,Vincent Mok,Li Su...&Ying Han.(2019).Automated Brain MRI Volumetry Differentiates Early Stages of Alzheimer's Disease From Normal Aging..Journal of geriatric psychiatry and neurology,32,(6)
MLA：
Weina Zhao,et al."Automated Brain MRI Volumetry Differentiates Early Stages of Alzheimer's Disease From Normal Aging.".Journal of geriatric psychiatry and neurology 32..6(2019):354-364
