Assessing cognitive impairment and disability in older adults through the lens of whole brain white matter patterns.
Hyun Woong RohNishant ChauhanSang Won SeoSeong Hye ChoiEun-Joo KimSoo Hyun ChoByeong C KimJin Wook ChoiYoung-Sil AnBumhee ParkSun Min LeeSo Young MoonYou Jin NamSunhwa HongSang Joon SonChang Hyung HongDongha LeePublished in: Alzheimer's & dementia : the journal of the Alzheimer's Association (2024)
The ensemble model combined both magnetic resonance imaging (MRI) and amyloid positron emission tomography (PET) and demonstrated a significantly higher classification performance for cognitive impairment and disability. Alzheimer's disease (AD) revealed a notably higher heterogeneity compared to that in subjective cognitive decline, mild cognitive impairment, or vascular dementia. White matter inter-subject variability (WM-ISV) was significantly correlated with blood-based biomarkers (glial fibrillary acidic protein and phosphorylated tau-217 [p-tau217]) and with the polygenic risk score for AD. White matter pattern analysis has significant potential as an adjunct neuroimaging biomarker for clinical decision-making processes and determining cognitive impairment and disability.
Keyphrases
- white matter
- cognitive impairment
- cognitive decline
- mild cognitive impairment
- multiple sclerosis
- positron emission tomography
- computed tomography
- magnetic resonance imaging
- contrast enhanced
- decision making
- pet ct
- pet imaging
- single cell
- cerebrospinal fluid
- deep learning
- machine learning
- physical activity
- diffusion weighted imaging
- spinal cord injury
- ionic liquid
- convolutional neural network
- subarachnoid hemorrhage
- brain injury
- climate change