Brain reference charts for a lifespan compiled from 124,000 MRI scans


By Michael Woodhead

7 Apr 2022

A ‘reference library’ of brain charts from MRI scans that will serve as neuroimaging benchmarks across the 100 year human lifespan has been created by a team of international researchers including Australian specialists.

The reference charts for human brain development are being made available as an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data. They are the result of a research project spanning six continents and bringing together possibly the largest ever MRI datasets ever aggregated – almost 125,000 brain scans from over 100 different studies.

Writing in Nature, the researchers said there were currently no standard references to quantify the maturation and healthy ageing of the human brain, unlike growth charts used to measure traits such as height and weight in children.

To address this issue, a team led by scientists at Cambridge University’s Brain Mapping Unit, collated data from 123,984 MRI brain scans of 101,457 individuals aged between 115 days after conception and 100 years old, from over 100 studies worldwide.

The team created charts of normal brain development across a lifetime, which they say can be used to generate ‘centile scores’ to determine whether an individual is on a standard trajectory.

The brain charts showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies,” they wrote.

“The approximately 100-year age range enabled the delineation of milestones and critical periods in maturation of the human brain, revealing an early growth epoch across its constituent tissue classes—beginning before 17 post-conception weeks, when the brain is at approximately 10% of its maximum size, and ending by age 3, when the brain is at approximately 80% of the maximum size,” they wrote.

The standard framework also enabled the detection of patterns of changes in brain anatomy associated with disease; for example, predictions of a transition from a diagnosis of mild cognitive impairment to that of Alzheimer’s disease.

“Perhaps most importantly, GAMLSS modelling enabled harmonisation across technically diverse studies, and thus unlocked the potential value of combining primary MRI studies at scale to generate normative, sex-stratified brain growth charts, and individual centile scores of typicality and atypicality,” they said.

Although not intended for clinical use at present, the team hopes the charts will become a routine clinical tool similar to how standardised paediatric growth charts are used.

“As ongoing and future efforts provide increasing amounts of high-quality MRI data, we predict an iterative process of improved brain charts for an increasing number of multimodal neuroimaging phenotype,” they said.

The Australian centres that contributed to the study include Monash University, the University of Melbourne, the University of Sydney, Florey Institute of Neuroscience and Mental Health and the Murdoch Children’s Research Institute (MCRI).

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