Reliability of structural brain change in cognitively healthy adult samples

In neuroimaging research, tracking individuals over time is key to understanding the interplay between brain changes and genetic, environmental, or cognitive factors across the lifespan. Yet, the extent to which we can estimate the individual trajectories of brain change over time with precision remains uncertain. In this study, we estimated the reliability of structural brain change in cognitively healthy adults from multiple samples and assessed the influence of follow-up time and number of observations. Estimates of cross-sectional measurement error and brain change variance were obtained using the longitudinal FreeSurfer processing stream. Our findings showed, on average, modest longitudinal reliability with 2 years of follow-up. Increasing the follow-up time was associated with a substantial increase in longitudinal reliability, while the impact of increasing the number of observations was comparatively minor. On average, 2-year follow-up studies require ≈2.7 and ≈4.0 times more individuals than designs with follow-ups of 4 and 6 years to achieve comparable statistical power. Subcortical volume exhibited higher longitudinal reliability than cortical area, thickness, and volume. The reliability estimates were comparable with those estimated from empirical data. The reliability estimates were affected by both the cohort's age where younger adults had lower reliability of change and the preprocessing pipeline where the FreeSurfer's longitudinal stream was notably superior than the cross-sectional stream. Suboptimal reliability inflated sample size requirements and compromised the ability to distinguish individual trajectories of brain aging. This study underscores the importance of long-term follow-ups and the need to consider reliability in longitudinal neuroimaging research.

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Publication Details

Journal
Imaging Neuroscience
Published
2025-01-01
DOI
https://doi.org/10.1162/imag_a_00547
Citations
11
Primary Topic
Health, Environment, Cognitive Aging
Type
article
Field-Weighted Citation Impact
13.20

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article

Reliability of structural brain change in cognitively healthy adult samples

Didac Vidal‐Piñeiro, Markus H. Sneve, Marie Strømstad, James M. Roe et al.
11 citations
Imaging Neuroscience
Health, Environment, Cognitive Aging
13.20
article

Reliability of structural brain change in cognitively healthy adult samples

Didac Vidal‐Piñeiro, Markus H. Sneve, Marie Strømstad, James M. Roe, Andreas M. Brandmaier, Anders M. Fjell, Richard N. Henson, Anne Cecilie Sjøli Bråthen, Inge K. Amlien, Håkon Grydeland, Øystein Sørensen, Pablo Garrido, David Bartrés‐Faz, Athanasia M. Mowinckel, Paolo Ghisletta, Rogier Kievit, Kristine B. Walhovd, William F.C. Baaré, Cristina Solé‐Padullés, Lars Nyberg, Simone Kühn, Micael Anderson, Max Kormacher, Leiv-Otto Watne, Ulman Lindenberger
article en
11 citations

Abstract

In neuroimaging research, tracking individuals over time is key to understanding the interplay between brain changes and genetic, environmental, or cognitive factors across the lifespan. Yet, the extent to which we can estimate the individual trajectories of brain change over time with precision remains uncertain. In this study, we estimated the reliability of structural brain change in cognitively healthy adults from multiple samples and assessed the influence of follow-up time and number of observations. Estimates of cross-sectional measurement error and brain change variance were obtained using the longitudinal FreeSurfer processing stream. Our findings showed, on average, modest longitudinal reliability with 2 years of follow-up. Increasing the follow-up time was associated with a substantial increase in longitudinal reliability, while the impact of increasing the number of observations was comparatively minor. On average, 2-year follow-up studies require ≈2.7 and ≈4.0 times more individuals than designs with follow-ups of 4 and 6 years to achieve comparable statistical power. Subcortical volume exhibited higher longitudinal reliability than cortical area, thickness, and volume. The reliability estimates were comparable with those estimated from empirical data. The reliability estimates were affected by both the cohort's age where younger adults had lower reliability of change and the preprocessing pipeline where the FreeSurfer's longitudinal stream was notably superior than the cross-sectional stream. Suboptimal reliability inflated sample size requirements and compromised the ability to distinguish individual trajectories of brain aging. This study underscores the importance of long-term follow-ups and the need to consider reliability in longitudinal neuroimaging research.

Imaging NeuroscienceVol. 3
University of Geneva (CH), Oslo University Hospital (NO), Radboud University Nijmegen (NL), Universität Hamburg (DE), Western Norway University of Applied Sciences (NO), University of Oslo (NO), MRC Cognition and Brain Sciences Unit (GB), Akershus University Hospital (NO), Amager Hospital (DK), Hvidovre Hospital (DK), Copenhagen University Hospital (DK), Radboud University Medical Center (NL), MSB Medical School Berlin (DE), Visual Solutions (Norway) (NO), University Medical Center Hamburg-Eppendorf (DE), Max Planck Institute for Human Development (DE), Max Planck Institute for Biology of Ageing (DE), Consorci Institut D'Investigacions Biomediques August Pi I Sunyer (ES), Umeå University (SE)
Alzheimer's Association, Pfizer, Massachusetts General Hospital, Harvard University, McGill University, Fondation Brain Canada, Wellcome Trust, Child Mind Institute, Government of Canada, Cancer Research UK, British Heart Foundation, National Natural Science Foundation of China, Chinese Academy of Sciences, Helse- og Omsorgsdepartementet, Northwest Regional Development Agency, Universitetet i Oslo, Norges Forskningsråd, Centre d'Imagerie BioMédicale, Hangzhou Normal University, Pfizer Canada, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Canadian Institutes of Health Research, Medical Research Council, National Social Science Fund of China, Institute of Psychology, Chinese Academy of Sciences, National Institute on Drug Abuse
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