An international team of researchers has created a series of brain diagrams spanning our entire lives – from a 15-week-old fetus to a 100-year-old adult – that show how our brains grow rapidly in early life and slowly shrink as we go. as we age.
The graphs are the result of a research project spanning six continents and bringing together possibly the largest MRI datasets ever aggregated – nearly 125,000 brain scans from more than 100 different studies. Although not currently intended for clinical use, the team hopes the charts will become a routine clinical tool similar to how standardized pediatric growth charts are used.
Growth charts have been a cornerstone of pediatric health care for over 200 years and are ubiquitously used in clinics to help monitor the growth and development of children relative to their peers. A typical growth chart may plot age on the horizontal axis against height on the vertical axis, but rather than being a single line, it will show a range that reflects natural variability in height, height, weight or head circumference.
There are no analogous reference charts for measuring age-related changes in the human brain. The lack of standardized assessment tools for brain development and aging is particularly relevant to the study of psychiatric disorders, where the differences between conditions and their heterogeneity demand instruments that can tell something meaningful about a single individual from the same way clinical reference charts can, and to conditions such as Alzheimer’s disease that cause brain tissue degeneration and cognitive decline.
Today’s study, published in Nature, is a major step to fill this gap. Unlike pediatric growth charts, BrainChart – published on the open-access site brainchart.io – covers the whole of life, from development in the womb to old age, and aims to create a common language for describing the variability of brain development and maturation. .
The Incredible Growing and Shrinking Brain
The brain diagrams have allowed researchers to confirm – and in some cases show for the first time – developmental milestones that had previously only been hypothetical, such as at what age major classes of brain tissue reach maturity. peak volume and when specific regions of the brain mature.
Dr Richard Bethlehem from the University of Cambridge’s Department of Psychiatry, one of the study’s co-leads, said: “One of the things we were able to do, through a very concerted global effort, is to assemble data over the entire lifespan. This allowed us to measure the very early and rapid changes that occur in the brain, and the long, slow decline as we age.
Some of the key milestones observed by the team include:
- The volume of gray matter (brain cells) increases rapidly from mid-gestation, reaching a peak just before the age of six. It then begins to slowly decrease.
- The volume of white matter (brain connections) also increased rapidly from mid-gestation through infancy and peaked just before age 29.
- The decrease in white matter volume begins to accelerate after age 50.
- Gray matter volume in the subcortex (which controls basic bodily functions and behavior) peaks in adolescence at age 14½.
Towards a clinically useful tool
While the brain maps are already proving useful for research, in the long term, the team wants them to be used as a clinical tool. The datasets already contain around 165 different diagnostic labels, meaning researchers can see how the brain differs in conditions such as Alzheimer’s disease.
Alzheimer’s disease causes neurodegeneration and loss of brain tissue, so those affected by the disease are likely to have reduced brain volume compared to their peers. In the same way that some healthy adults are taller than others, there is variability in brain size – in other words, a slightly smaller brain does not necessarily indicate that something is wrong. . However, as brain diagrams show, while brain size naturally decreases with age, it does so much more rapidly in patients with Alzheimer’s disease.
Dr Bethlehem explained: “We are still at an extremely early stage with our Brain Charts, showing that it is possible to create these tools by bringing together huge sets of data. The charts are already starting to provide interesting insights into brain development, and our ambition is that in the future, as we integrate more datasets and refine the graphs, they could eventually become part of routine clinical practice.
“You can imagine them being used to help assess patients screened for conditions like Alzheimer’s disease, for example, allowing doctors to spot signs of neurodegeneration by comparing how quickly a patient’s brain volume has changed compared to its peers.”
Additionally, the team hopes to make brain maps more representative of the general population, highlighting the need for more brain MRI data on previously underrepresented socioeconomic and ethnic groups.
A huge technical feat
Dr Jakob Seidlitz of the Lifespan Brain Institute at Children’s Hospital of Philadelphia and the University of Pennsylvania, another of the study’s co-leads, said: “Creating these brain diagrams involved multiple feats techniques and a large team of collaborators. With data brain imaging, things are a little more complicated than simply pulling out a tape measure and measuring a person’s height or head circumference. There were significant challenges to overcome, including logistical and administrative hurdles as well as the enormous methodological variability we find between brain imaging datasets.”
The team used standardized neuroimaging software to extract data from MRI scans, starting with simple properties such as gray matter or white matter volume, then expanding their work to look at finer details, such as the thickness of the cortex or the volume of specific regions of the brain. They used a framework implemented by the World Health Organization for generating growth charts to construct their brain diagrams.
In total, they estimate that they used around 2 million hours of computing time, analyzing almost a petabyte of data (a petabyte equals 1,000,000,000,000,000 bytes).
“This really wouldn’t have been possible without access to Cambridge’s high-performance computing clusters,” Dr Seidlitz said. “But we still see this as a work in progress. It’s a first step towards establishing a standardized reference chart for neuroimaging. That’s why we built the website and created a large network of collaborators We plan to constantly update the tables and build on these models as new data becomes available.”
The team created the tool with a frame of reference to allow other researchers and clinicians to tune their own datasets, allowing them to be compared to the BrainChart population.
Dr Bethlehem explained: “The NHS performs millions of brain scans every year and in most of these cases they are assessed by radiologists or neurologists who draw on their vast expertise to judge whether there is something anything clinically relevant apparent on these scans. We hope clinicians in the future can compare their data to ours and produce a more comprehensive report that adds additional objective and quantitative observations to their assessment.”
“This should effectively allow the neurologist to answer the question ‘this area looks atypical but how atypical? “As the tool is standardized, it doesn’t matter where you have your brain scan – you should always be able to compare this.”
Working with Dr Bethlehem and Dr Seidlitz, the work was led by Cambridge researchers Dr Simon White and Professor Ed Bullmore, and Dr Aaron Alexander-Bloch of the University of Pennsylvania. It builds on a worldwide collective effort over the past decades to measure the structure of the human brain with MRI, in many groups of people at different ages. The team says this would not have been possible without open access to many high-quality MRI datasets, and hopes their results will contribute to greater openness and sharing of data and analysis for the science of brain imaging.
The research was supported by the British Academy, the Autism Center of Excellence, the Medical Research Council, the National Institute for Health Research (NIHR), the Wellcome Trust and the NIHR Cambridge Biomedical Research Centre.