Participant followup rate can bias structural imaging measures in longitudinal studies

Richard Beare; Gareth Ball; Joseph Yuan-Mou Yang; Chris Moran; Velandai Srikanth; Marc Seal

Neuroimage: Reports (Dec 2021)

Participant followup rate can bias structural imaging measures in longitudinal studies

Richard Beare,
Gareth Ball,
Joseph Yuan-Mou Yang,
Chris Moran,
Velandai Srikanth,
Marc Seal

Affiliations

Richard Beare: Developmental Imaging, Murdoch Children’s Research Institute, Australia; Monash University, Academic Unit, Peninsula Clinical School, Central Clinical School, Melbourne, Victoria, Australia; Corresponding author. Developmental Imaging, Murdoch Children's Research Institute, Australia.
Gareth Ball: Developmental Imaging, Murdoch Children’s Research Institute, Australia; Department of Paediatrics, University of Melbourne, Australia
Joseph Yuan-Mou Yang: Developmental Imaging, Murdoch Children’s Research Institute, Australia; Department of Paediatrics, University of Melbourne, Australia; Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, Royal Children’s Hospital, Australia; Neuroscience Research, Murdoch Children’s Research Institute, Australia
Chris Moran: Monash University, Academic Unit, Peninsula Clinical School, Central Clinical School, Melbourne, Victoria, Australia; Department of Geriatric Medicine, Peninsula Health, Melbourne, Victoria, Australia
Velandai Srikanth: Monash University, Academic Unit, Peninsula Clinical School, Central Clinical School, Melbourne, Victoria, Australia; Department of Geriatric Medicine, Peninsula Health, Melbourne, Victoria, Australia; University of Tasmania, Menzies Institute for Medical Research, Hobart, Australia
Marc Seal: Developmental Imaging, Murdoch Children’s Research Institute, Australia; Department of Paediatrics, University of Melbourne, Australia

Journal volume & issue: Vol. 1, no. 4
p. 100066

Abstract

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Longitudinal MRI analysis is essential to accurately describe neuroanatomical changes over time. Loss of participants to followup (dropout) in longitudinal studies is inevitable and can lead to great difficulty in interpretation of statistical results if dropout is correlated with a study outcome or exposure. Beyond this, technical aspects of longitudinal MRI analysis require specialised processing pipelines to improve reliability while avoiding bias towards individual timepoints. In this article we test whether there is an additional problem that must be considered in longitudinal imaging studies, namely whether dropout has an impact on the function of FreeSurfer, a popular software pipeline used to estimate important structural brain metrics.We find that the number of acquisitions available per individual can impact the estimation of cortical thickness and brain volume using the FreeSurfer longitudinal pipeline, and can induce group differences in brain metrics. The effect on trajectories of brain metrics is smaller than the effect on brain metrics.

Published in Neuroimage: Reports

ISSN: 2666-9560 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry
Website: https://www.journals.elsevier.com/neuroimage-reports

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