Reliability of structural brain change in cognitively healthy adult samples.

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Opis bibliograficzny
Wydane w:	bioRxiv (Feb 20, 2025)
1. autor:	Vidal-Pineiro, Didac
Kolejni autorzy:	Sorensen, Oystein, Stromstad, Marie, Amlien, Inge K, Anderson, Micael, Baare, William Fc, Bartres-Faz, David, Brandmaier, Andreas M, Brathen, Anne Cecilie, Garrido, Pablo, Ghisletta, Paolo, Grydeland, Hakon, Henson, Richard N, Kievit, Rogier A, Korbmacher, Max, Kuhn, Simone, Ulman Lindenberger, Mowinckel, Athanasia M, Nyberg, Lars, Roe, James M, Sneve, Markus H, Sole-Padulles, Cristina, Leiv-Otto Watne, Walhovd, Kristine B, Fjell, Anders M
Wydane:	Cold Spring Harbor Laboratory Press
Hasła przedmiotowe:	Neuroimaging Medical imaging Life span Estimates Brain research Aging
Dostęp online:	Citation/Abstract Full text outside of ProQuest
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Opis
Streszczenie:	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 two 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 compared to cortical area, thickness, and volume. The reliability estimates were comparable to 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. 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.Competing Interest StatementThe authors have declared no competing interest.Footnotes* This version of the manuscript has been revised to update author names, general improvements in clarity* https://github.com/LCBC-UiO/Long_Brain_Reliability
ISSN:	2692-8205
DOI:	10.1101/2024.06.03.592804
Źródło:	Biological Science Database