| Autor: |
Chang-Le Chen, Ming-Che Kuo, Wen-Chau Wu, Yung-Chin Hsu, Ruey-Meei Wu, Wen-Yih Isaac Tseng |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
NeuroImage: Clinical, Vol 34, Iss , Pp 102997- (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2213-1582 |
| DOI: |
10.1016/j.nicl.2022.102997 |
| Popis: |
Multiple system atrophy (MSA) and Parkinson’s disease (PD) belong to alpha-synucleinopathy, but they have very different clinical courses and prognoses. An imaging biomarker that can differentiate between the two diseases early in the disease course is desirable for appropriate treatment. Neuroimaging-based brain age paradigm provides an individualized marker to differentiate aberrant brain aging patterns in neurodegenerative diseases. In this study, patients with MSA (N = 23), PD (N = 33), and healthy controls (N = 34; HC) were recruited. A deep learning approach was used to estimate brain-predicted age difference (PAD) of gray matter (GM) and white matter (WM) based on image features extracted from T1-weighted and diffusion-weighted magnetic resonance images, respectively. Spatial normative models of image features were utilized to quantify neuroanatomical impairments in patients, which were then used to estimate the contributions of image features to brain age measures. For PAD of GM (GM-PAD), patients with MSA had significantly older brain age (9.33 years) than those with PD (0.75 years; P = 0.002) and HC (-1.47 years; P |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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