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Patch‐wise brain age longitudinal reliability

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 a...

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Detalles Bibliográficos
Autores principales: Beheshti, Iman, Potvin, Olivier, Duchesne, Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7814761/
https://www.ncbi.nlm.nih.gov/pubmed/33205863
http://dx.doi.org/10.1002/hbm.25253
Descripción
Sumario: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.