학술논문

Charting brain growth and aging at high spatial precision
Document Type
article
Source
Subject
Biological Sciences
Biomedical and Clinical Sciences
Health Sciences
Biomedical Imaging
Neurosciences
Neurological
Good Health and Well Being
Adolescent
Adult
Aged
Aged
80 and over
Aging
Big Data
Brain
Child
Child
Preschool
Cohort Studies
Female
Humans
Magnetic Resonance Imaging
Male
Middle Aged
Models
Statistical
Neuroimaging
Young Adult
normative model
lifespan
growth chart
brain chart
big data
individual prediction
Human
human
neuroscience
Biochemistry and Cell Biology
Biological sciences
Biomedical and clinical sciences
Health sciences
Language
Abstract
Defining reference models for population variation, and the ability to study individual deviations is essential for understanding inter-individual variability and its relation to the onset and progression of medical conditions. In this work, we assembled a reference cohort of neuroimaging data from 82 sites (N=58,836; ages 2-100) and used normative modeling to characterize lifespan trajectories of cortical thickness and subcortical volume. Models are validated against a manually quality checked subset (N=24,354) and we provide an interface for transferring to new data sources. We showcase the clinical value by applying the models to a transdiagnostic psychiatric sample (N=1985), showing they can be used to quantify variability underlying multiple disorders whilst also refining case-control inferences. These models will be augmented with additional samples and imaging modalities as they become available. This provides a common reference platform to bind results from different studies and ultimately paves the way for personalized clinical decision-making.