Patch-wise brain age longitudinal reliability

Hum Brain Mapp. 2021 Feb 15;42(3):690-698. doi: 10.1002/hbm.25253. Epub 2020 Nov 18.

Abstract

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 (R2 = .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.

Keywords: anatomical MRI; brain age; estimation; longitudinal study; patch-wise grading; reliability.

Publication types

  • Multicenter Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Factors
  • Atlases as Topic
  • Brain / anatomy & histology*
  • Brain / diagnostic imaging*
  • Datasets as Topic
  • Female
  • Humans
  • Longitudinal Studies
  • Magnetic Resonance Imaging / standards*
  • Male
  • Middle Aged
  • Neuroimaging / standards*
  • Reproducibility of Results
  • Young Adult