@article{b11e55e089e84ac6a5a266994f91838b,
title = "Prediction of 7-year's conversion from subjective cognitive decline to mild cognitive impairment",
abstract = "Subjective cognitive decline (SCD) is a high-risk yet less understood status before developing Alzheimer's disease (AD). This work included 76 SCD individuals with two (baseline and 7 years later) neuropsychological evaluations and a baseline T1-weighted structural MRI. A machine learning-based model was trained based on 198 baseline neuroimaging (morphometric) features and a battery of 25 clinical measurements to discriminate 24 progressive SCDs who converted to mild cognitive impairment (MCI) at follow-up from 52 stable SCDs. The SCD progression was satisfactorily predicted with the combined features. A history of stroke, a low education level, a low baseline MoCA score, a shrunk left amygdala, and enlarged white matter at the banks of the right superior temporal sulcus were found to favor the progression. This is to date the largest retrospective study of SCD-to-MCI conversion with the longest follow-up, suggesting predictable far-future cognitive decline for the risky populations with baseline measures only. These findings provide valuable knowledge to the future neuropathological studies of AD in its prodromal phase.",
keywords = "MRI, machine learning, prediction, subjective cognitive decline",
author = "Ling Yue and Dan Hu and Han Zhang and Junhao Wen and Ye Wu and Wei Li and Lin Sun and Xia Li and Jinghua Wang and Guanjun Li and Tao Wang and Dinggang Shen and Shifu Xiao",
note = "Funding Information: Shanghai Clinical Research Center for Mental Health, Grant/Award Number: 19MC1911100; Shanghai Jiaotong University School of Medicine, Grant/Award Numbers: CBXJ201815, YG2016MS38; Shanghai Mental Health Center, Grant/Award Numbers: 2018‐FX‐05, 2020zd01, CRC2017ZD02; Shanghai Municipal Human Resources Development Program, Grant/Award Number: 2017BR054; the China Ministry of Science and Technology, Grant/Award Number: 2009BAI77B03; the National Natural Science Foundation of China, Grant/Award Number: 81830059 Funding information Funding Information: This work was supported by the China Ministry of Science and Technology (2009BAI77B03), Shanghai Mental Health Center (CRC2017ZD02, 2018-FX-05, 2020zd01), Shanghai Clinical Research Center for Mental Health (SCRC-MH, 19MC1911100), the National Natural Science Foundation of China (81830059), Shanghai Jiaotong University School of Medicine (CBXJ201815, YG2016MS38), and Shanghai Municipal Human Resources Development Program (2017BR054). Funding Information: This work was supported by the China Ministry of Science and Technology (2009BAI77B03), Shanghai Mental Health Center (CRC2017ZD02, 2018‐FX‐05, 2020zd01), Shanghai Clinical Research Center for Mental Health (SCRC‐MH, 19MC1911100), the National Natural Science Foundation of China (81830059), Shanghai Jiaotong University School of Medicine (CBXJ201815, YG2016MS38), and Shanghai Municipal Human Resources Development Program (2017BR054). Publisher Copyright: {\textcopyright} 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.",
year = "2021",
month = jan,
doi = "10.1002/hbm.25216",
language = "English",
volume = "42",
pages = "192--203",
journal = "Human Brain Mapping",
issn = "1065-9471",
publisher = "Wiley-Liss Inc.",
number = "1",
}