Interdatabase variability in cortical thickness measurements

Author(s)
MacDonald, M Ethan
Williams, Rebecca J
Forkert, Nils D
Berman, Avery J L
McCreary, Cheryl R
Frayne, Richard
Pike, G Bruce
Publication Date
2019-08
Abstract
<p>The phenomenon of cortical thinning with age has been well established; however, the measured rate of change varies between studies. The source of this variation could be image acquisition techniques including hardware and vendor specific differences. Databases are often consolidated to increase the number of subjects but underlying differences between these datasets could have undesired effects. We explore differences in cerebral cortex thinning between 4 databases, totaling 1382 subjects. We investigate several aspects of these databases, including: 1) differences between databases of cortical thinning rates versus age, 2) correlation of cortical thinning rates between regions for each database, and 3) regression bootstrapping to determine the effect of the number of subjects included. We also examined the effect of different databases on age prediction modeling. Cortical thinning rates were significantly different between databases in all 68 parcellated regions (ANCOVA, <i>P</i> < 0.001). Subtle differences were observed in correlation matrices and bootstrapping convergence. Age prediction modeling using a leave-one-out cross-validation approach showed varying prediction performance (0.64 < <i>R<sup>2</sup></i> < 0.82) between databases. When a database was used to calibrate the model and then applied to another database, prediction performance consistently decreased. We conclude that there are indeed differences in the measured cortical thinning rates between these large-scale databases.</p>
Citation
Cerebral Cortex, 29(8), p. 3282-3293
ISSN
1460-2199
1047-3211
Link
Publisher
Oxford University Press
Title
Interdatabase variability in cortical thickness measurements
Type of document
Journal Article
Entity Type
Publication

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