期刊
HUMAN BRAIN MAPPING
卷 42, 期 3, 页码 690-698出版社
WILEY
DOI: 10.1002/hbm.25253
关键词
anatomical MRI; brain age; estimation; longitudinal study; patch‐ wise grading; reliability
资金
- Alzheimer's Society of Canada [13-32]
- Canadian Institutes for Health Research [117121]
- Fonds de recherche du Quebec Sante [30801]
- Fonds de recherche du Quebec - Sante/Pfizer Canada - Pfizer-FRQS Innovation Fund [25262]
- Fonds de recherche du Quebec -Sante/Pfizer Canada Innovation Fund [27239]
The study introduced a patch-wise technique for estimating brain age from T1w MRI data, and demonstrated its longitudinal reliability on a unique dataset. The results showed high prediction accuracy and no significant difference between manufacturers, suggesting the technique can be used for longitudinal multi-centric studies.
We recently introduced a patch-wise technique to estimate brain age from anatomical T1-weighted magnetic resonance imaging (T1w MRI) data. Here, we sought to assess its longitudinal reliability by leveraging a unique dataset of 99 longitudinal MRI scans from a single, cognitively healthy volunteer acquired over a period of 17 years (aged 29-46 years) at multiple sites. We built a robust patch-wise brain age estimation framework on the basis of 100 cognitively healthy individuals from the MindBoggle dataset (aged 19-61 years) using the Desikan-Killiany-Tourville atlas, then applied the model to the volunteer dataset. The results show a high prediction accuracy on the independent test set (R-2 = .94, mean absolute error of 0.63 years) and no statistically significant difference between manufacturers, suggesting that the patch-wise technique has high reliability and can be used for longitudinal multi-centric studies.
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