Such standards for human brain measurement have not yet materialized from decades of neuroimaging research, probably owing to the challenges of integrating MRI data across multiple, methodologically diverse studies targeting distinct developmental epochs and clinical conditions 13. Mental illness and dementia collectively represent the single biggest global health burden 11, highlighting the urgent need for normative brain charts as an anchor point for standardized quantification of brain structure over the lifespan 12. Preterm birth and neurogenetic disorders are also associated with marked abnormalities of brain structure 8, 9 that persist into adult life 9, 10 and are associated with learning disabilities and mental health disorders. The lack of tools for standardized assessment of brain development and ageing is particularly relevant to research studies of psychiatric disorders, which are increasingly recognized as a consequence of atypical brain development 6, and neurodegenerative diseases that cause pathological brain changes in the context of normative senescence 7. There are no analogous charts available for quantification of age-related changes in the human brain, although it is known to go through a prolonged and complex maturational program from pregnancy to the third decade 4, followed by progressive senescence from approximately the sixth decade 5. However, growth charts are currently available only for a small set of anthropometric variables, such as height, weight and head circumference, and only for the first decade of life. The simple framework of growth charts to quantify age-related change was first published in the late eighteenth century 1 and remains a cornerstone of paediatric healthcare-an enduring example of the utility of standardized norms to benchmark individual trajectories of development.
In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. Brain charts identified previously unreported neurodevelopmental milestones 3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. MRI metrics were quantified by centile scores, relative to non-linear trajectories 2 of brain structural changes, and rates of change, over the lifespan. With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age.
Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( ).
However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight 1. Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. Nature volume 604, pages 525–533 ( 2022) Cite this article ENIGMA Developmental Brain Age Working Group,.Alzheimer’s Disease Repository Without Borders Investigators,.Alzheimer’s Disease Neuroimaging Initiative,.
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