Participant followup rate can bias structural imaging measures in longitudinal studies

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...

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Autores principales:	Richard Beare, Gareth Ball, Joseph Yuan-Mou Yang, Chris Moran, Velandai Srikanth, Marc Seal
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	FreeSurfer longitudinal pipeline Cortical thickness Longitudinal bias Individual template Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/616c0121afff4b5bb1c179caa5c91144
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id	oai:doaj.org-article:616c0121afff4b5bb1c179caa5c91144
record_format	dspace
spelling	oai:doaj.org-article:616c0121afff4b5bb1c179caa5c911442021-12-02T05:04:30ZParticipant followup rate can bias structural imaging measures in longitudinal studies2666-956010.1016/j.ynirp.2021.100066https://doaj.org/article/616c0121afff4b5bb1c179caa5c911442021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2666956021000647https://doaj.org/toc/2666-9560Longitudinal 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.Richard BeareGareth BallJoseph Yuan-Mou YangChris MoranVelandai SrikanthMarc SealElsevierarticleFreeSurfer longitudinal pipelineCortical thicknessLongitudinal biasIndividual templateNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENNeuroimage: Reports, Vol 1, Iss 4, Pp 100066- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	FreeSurfer longitudinal pipeline Cortical thickness Longitudinal bias Individual template Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	FreeSurfer longitudinal pipeline Cortical thickness Longitudinal bias Individual template Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Richard Beare Gareth Ball Joseph Yuan-Mou Yang Chris Moran Velandai Srikanth Marc Seal Participant followup rate can bias structural imaging measures in longitudinal studies
description	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.
format	article
author	Richard Beare Gareth Ball Joseph Yuan-Mou Yang Chris Moran Velandai Srikanth Marc Seal
author_facet	Richard Beare Gareth Ball Joseph Yuan-Mou Yang Chris Moran Velandai Srikanth Marc Seal
author_sort	Richard Beare
title	Participant followup rate can bias structural imaging measures in longitudinal studies
title_short	Participant followup rate can bias structural imaging measures in longitudinal studies
title_full	Participant followup rate can bias structural imaging measures in longitudinal studies
title_fullStr	Participant followup rate can bias structural imaging measures in longitudinal studies
title_full_unstemmed	Participant followup rate can bias structural imaging measures in longitudinal studies
title_sort	participant followup rate can bias structural imaging measures in longitudinal studies
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/616c0121afff4b5bb1c179caa5c91144
work_keys_str_mv	AT richardbeare participantfollowupratecanbiasstructuralimagingmeasuresinlongitudinalstudies AT garethball participantfollowupratecanbiasstructuralimagingmeasuresinlongitudinalstudies AT josephyuanmouyang participantfollowupratecanbiasstructuralimagingmeasuresinlongitudinalstudies AT chrismoran participantfollowupratecanbiasstructuralimagingmeasuresinlongitudinalstudies AT velandaisrikanth participantfollowupratecanbiasstructuralimagingmeasuresinlongitudinalstudies AT marcseal participantfollowupratecanbiasstructuralimagingmeasuresinlongitudinalstudies
_version_	1718400653234012160

Participant followup rate can bias structural imaging measures in longitudinal studies

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