Loading...
Estimating cortical thickness trajectories in children across different scanners using transfer learning from normative models
Gaiser,C. Berthet,P. Kia,S. M. Frens,M. A. Beckmann,C. F. Muetzel,R. L. Marquand,Andre F.
Gaiser,C.
Berthet,P.
Kia,S. M.
Frens,M. A.
Beckmann,C. F.
Muetzel,R. L.
Marquand,Andre F.
Abstract
This work illustrates the use of normative models in a longitudinal neuroimaging study of children aged 6-17 years and demonstrates how such models can be used to make meaningful comparisons in longitudinal studies, even when individuals are scanned with different scanners across successive study waves. More specifically, we first estimated a large-scale reference normative model using Hierarchical Bayesian Regression from N = 42,993 individuals across the lifespan and from dozens of sites. We then transfer these models to a longitudinal developmental cohort (N = 6285) with three measurement waves acquired on two different scanners that were unseen during estimation of the reference models. We show that the use of normative models provides individual deviation scores that are independent of scanner effects and efficiently accommodate inter-site variations. Moreover, we provide empirical evidence to guide the optimization of sample size for the transfer of prior knowledge about the distribution of regional cortical thicknesses. We show that a transfer set containing as few as 25 samples per site can lead to good performance metrics on the test set. Finally, we demonstrate the clinical utility of this approach by showing that deviation scores obtained from the transferred normative models are able to detect and chart morphological heterogeneity in individuals born preterm.
Description
Publisher Copyright: © 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.
Date
2024-02-01
Journal Title
Journal ISSN
Volume Title
Publisher
Research Projects
Organizational Units
Journal Issue
Keywords
Mri, Brain age, Cortical thickness, Neurodevelopment, Normative modelling
Citation
Gaiser, C, Berthet, P, Kia, S M, Frens, M A, Beckmann, C F, Muetzel, R L & Marquand, A F 2024, 'Estimating cortical thickness trajectories in children across different scanners using transfer learning from normative models', Human Brain Mapping, vol. 45, no. 2, e26565. https://doi.org/10.1002/hbm.26565