Name
Title | ||
|---|---|---|
Diffusion tensor imaging measures of brain connectivity for the early diagnosis of Alzheimer's disease. |
Abstract | ||
|---|---|---|
The prognostic capacity of the diffusion tensor imaging measures fractional anisotropy (FA) and mean diffusivity (MD) to detect mild cognitive impairment (MCI) progression to Alzheimer's disease (AD) was assessed in 135 MCI patients and 72 healthy subjects over a median follow-up of 40 months. Forty-nine MCI patients (36.3%) developed AD. The factors MD left hippocampus, FA left cingulate, and FA left hippocampus emerged as predictors of progression. Age (hazard ratio [HR] 1.21), delayed text recall (HR 0.89), FA left uncinate (HR 1.90), FA left hippocampus (HR 2.21), and carrying at least one ApoE4 allele (HR 2.86) were associated with a high conversion rate. FA measures revealed the greatest discriminative capacity (Harrell's C = 0.73 versus 0.65 without FA; p = 0.034). The inclusion of FA structural connectivity data in our model improved discrimination between subjects with MCI progressing or not to dementia. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1089/brain.2018.0635 | BRAIN CONNECTIVITY |
Keywords | DocType | Volume |
Alzheimer's disease,brain connectivity,diffusion tensor imaging,early biomarker,fractional anisotropy,mild cognitive impairment | Journal | 9 |
Issue | ISSN | Citations |
8 | 2158-0014 | 0 |
PageRank | References | Authors |
0.34 | 0 | 12 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alberto Marcos | 1 | 7 | 0.81 |
| Cristina Gomez-Fernandez | 2 | 0 | 0.34 |
| Miguel Yus Fuertes | 3 | 0 | 0.34 |
| Ana Barabash Bustelo | 4 | 0 | 0.34 |
| Laura Marcos-Arribas | 5 | 0 | 0.34 |
| Cristina Lopez-Mico | 6 | 0 | 0.34 |
| Manuela Jorquera Moya | 7 | 0 | 0.34 |
| C. Pérez | 8 | 3 | 0.97 |
| Pedro Montejo Carrasco | 9 | 0 | 0.34 |
| Jose Antonio Cabranes Diaz | 10 | 0 | 0.34 |
| Juan Arrazola Garcia | 11 | 0 | 0.34 |
| fernando maestu | 12 | 18 | 0.80 |