In a remarkable achievement that is already impacting how we detect and diagnose disease, UK Biobank has completed the world’s largest whole body imaging project, scanning the brains, hearts, abdomens, blood vessels, bones and joints of 100,000 volunteers. These scans, on this scale, show us what is happening in people’s bodies as they age so we can understand how, why and when we get sick.
Since 2015, UK Biobank’s imaging data have been released in batches1 and scientists around the world are using these data to develop better diagnostic tests for life-altering conditions such as heart disease, dementia and cancer. Soon, approved researchers will have access to over one billion de-identified images, from 100,000 volunteers. Used alongside UK Biobank’s existing information on lifestyle, medical history, genetics and blood proteins collected from the same volunteers over the past 15 years, these imaging data allow researchers to see, in ways that were previously impossible, how all aspects of our lives influence our health.
So far, over 1,300 peer-reviewed scientific papers have been published based on UK Biobank's imaging data. Results from these are already improving patient care in the NHS and beyond. For example:
NHS memory clinics across the UK now use processes developed from UK Biobank to analyse brain magnetic resonance (MR) images2, helping to more accurately diagnose dementia.
Cardiac care has been improved in over 90 countries as clinicians use an AI tool, developed using UK Biobank data3, to analyse heart scans in less than a second - where it used to take nearly a quarter of an hour - allowing them time to focus on the cases that require most care4.
After 11 years, 100,000 imaging appointments lasting around 5 hours each, and over £60 million investment5, UK Biobank has reached this momentous milestone. “The unprecedented scale of this imaging project – more than 10 times bigger than anything that existed before – makes it possible for scientists to see patterns of disease that just couldn’t otherwise be seen. Collecting scans from 100,000 volunteers seemed to be a pipe dream… some experts even asked if we’d included an extra zero by mistake! This massive imaging project is making the invisible visible. What’s more, by combining these images from different parts of the body with all the genetic and lifestyle information from our volunteers, scientists are getting a far better understanding of how our bodies work,” said Professor Sir Rory Collins, Principal Investigator and Chief Executive of UK Biobank.
During each appointment, over 12,000 Magnetic Resonance (MR) images from the brain, heart and abdomen were collected per person, as well as whole body scans that measure bone density and body fat, and an ultrasound of the carotid arteries. Each volunteer also provided the same detailed data as when they first signed up to UK Biobank around 15 years ago, including lifestyle information, physical measures (like height, weight and grip strength), and a blood sample. “I signed up to my imaging appointment because I want to help create a healthier future for all of us to enjoy. That’s why I first volunteered to be part of UK Biobank over 15 years ago – to be of use to scientists who are working hard to help future generations,” said, Alison, a member of UK Biobank’s Participant Advisory Group.
Imaging data on this scale provides more information on rare diseases and the different stages of common diseases. Scientists can also better compare healthy bodies to ones with multiple conditions, ultimately leading to researchers finding more powerful markers of disease. “UK Biobank’s imaging study has transformed the landscape of biomedical research forever. The sheer volume of data propelled major advances in computerised image analysis. Now researchers can measure the size, shape, and composition of nearly every organ and tissue in the body in seconds, rather than hours per person,” said, Professor Louise Thomas, Professor of Metabolic Imaging at the University of Westminster.
As well as providing impacts which are benefiting patients right now, these imaging data are driving discovery science, which should lead to new diagnostic tests and treatments. These include:
Developing an AI model that creates a personalised version of a healthy heart (based on the individual’s age, sex, weight and height), that could be used to pinpoint the differences between a patient's real heart and its healthy model and catch potential signs of heart diseases early6.
Revealing how our organs can be biologically older than our chronological age, so that doctors might be able to look at someone’s body scan and clinical data to see what organs are at risk of developing disease, and find ways to prevent it, ultimately extending lifespan7.
Uncovering new ways in which the heart and brain are connected. For example, how structural changes to the heart cause an increased risk of psychiatric disorders, including depression. This is crucial for our understanding of brain diseases8.
Highlighting how an invasive surgical procedure can be replaced with an MRI scan to diagnose and monitor a common condition called fatty liver disease9.
Predicting the early onset of 38 diseases by combining MR images with other health data and using AI, showing the power of advanced technology to foresee health risks well before symptoms appear10.
Showing how consuming one to two units of alcohol per day is linked to potentially harmful reductions in brain size and brain structure11, which is likely to lead to an increased risk of memory loss and dementia.
Revealing that people with the same BMI can store fat in very different ways based on their genes – some which raise the risk of diseases such as diabetes and heart disease, and others in a protective way12.
Using DEXA scanning to identify that 1 in 10 middle-aged people, with no other symptoms, have calcification in the abdominal area of the aorta (main blood vessel of the body), a largely under-diagnosed lethal condition13.
Data on this scale are unlocking opportunities to use machine learning to help predict disease years before symptoms start to appear. “The beauty of UK Biobank is the breadth of the data collected from the generous volunteers, and the imaging scans add another layer of exquisite detail. One recent study used the brain imaging data from 20,000 participants, along with activity monitoring and genetic data, to develop an AI tool to predict who may go on to develop Alzheimer’s and Parkinson’s diseases14. I can’t wait to see what imaging data on 100,000 individuals will reveal!” said, Professor Paul Matthews, Chair of the UK Biobank Imaging Working Group.
This project has also led to a global democratisation of access to imaging data, by turning the MR images into data that are useable by researchers outside the imaging field, including those in less wealthy countries. “We’ve had such incredible feedback about how researchers across the world are using findings from the imaging project in areas of science that would not have ever considered using body scanning information before,” said, Professor Naomi Allen, Chief Scientist at UK Biobank.
UK Biobank’s imaging project was piloted in 2014 with over 7,000 volunteers scanned – a record-breaking number at that time. The main phase started in 2016, welcoming 100,000 of UK Biobank’s 500,000 volunteers to a 5-hour imaging appointment at one of four dedicated imaging centres across the country. The project is continuing to invite UK Biobank’s volunteers to imaging appointments beyond the 100,000 target.
A second phase of the imaging project was launched in 2022, aiming to perform repeat imaging on 60,000 of these 100,000 scanned participants, at least two years after their first imaging appointment. This project is ongoing and expected to reach completion in 2029.
UK Biobank data are made available to approved researchers in staggered releases via the secure cloud-based UK Biobank Research Analysis Platform (UKB-RAP). Imaging data from all 100,000 participants are expected to be made available to researchers by the end of 2025.
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For a digital pack containing photos and more details about the project please visit this link. For more information and requests for interview please contact: Naomi Clarke, Head of Press, UK Biobank naomi.clarke@ukbiobank.ac.uk +44 (0)7903 158 979 or Grace Tyrrell, Press Officer, UK Biobank grace.tyrrell@ukbiobank.ac.uk +44 (0)7484 075217.
Notes to editors:
UK Biobank is the world’s most comprehensive source of biomedical data available for health research in the public interest. Over the past 15 years we have collected biological, health and lifestyle information from 500,000 UK volunteers. The dataset is continuously growing, with additions including the world’s largest set of whole genome sequencing data, imaging data from 100,000 participants and a first-of-its kind set of protein biomarkers from 54,000 participants. Since 2012, scientists from universities, charities, companies and governments across the world can apply to use the data to advance modern medicine and drive the discovery of new preventions, treatments and cures. Over 21,000 researchers, based in more than 60 countries, are using UK Biobank data, and more than 16,000 peer-reviewed scientific papers have been published as a result. The data are de-identified and stored on our secure cloud-based platform. UK Biobank is a registered charity and was established by Wellcome and the Medical Research Council in 2003. You can read more about our funding here. www.ukbiobank.ac.uk, LinkedIn, X (Twitter), Facebook, Instagram
References:
New tranches of data from UK Biobank’s imaging assessment are uploaded to UK Biobank’s Data Showcase on a regular basis, with the first imaging data for 5,000 participants uploaded in October 2015. Currently, imaging data for over 80,000 participants are available to approved researchers.
Adapting UK Biobank imaging for use in a routine memory clinic setting: The Oxford Brain Health Clinic, Griffanti et al, NeuroImage: Clinical, November 2022. https://www.sciencedirect.com/science/article/pii/S2213158222003382
A population-based phenome-wide association study of cardiac and aortic structure and function, Bai et al, Nature Medicine, August 2020. https://www.nature.com/articles/s41591-020-1009-y
A Multicenter, Scan-Rescan, Human and Machine Learning CMR Study to Test Generalizability and Precision in Imaging Biomarker Analysis, Bhuva et al, Circulation: Cardiovascular Imaging, September 2019 https://www.ahajournals.org/doi/full/10.1161/CIRCIMAGING.119.009214
The programme to image 100,000 participants was funded by the government-funded Medical Research Council (MRC), Wellcome, the British Heart Foundation (BHF), and Dementias Platform UK (DPUK), who together provided a total of £62million.
A personalized time-resolved 3D mesh generative model for unveiling normal heart dynamics, Qiao et al, Nature Machine Intelligence, May 2025. https://www.nature.com/articles/s42256-025-01035-5
Heterogeneous aging across multiple organ systems and prediction of chronic disease and mortality, Tian et al, Nature Medicine, April 2023. https://www.nature.com/articles/s41591-023-02296-6
Heart-brain connections: Phenotypic and genetic insights from magnetic resonance images, Zhao et al, Science, June 2023. https://www.science.org/doi/10.1126/science.abn6598
Cardiac and liver impairment on multiorgan MRI and risk of major adverse cardiovascular and liver events, Jackson et al, Nature Medicine, May 2025. https://www.nature.com/articles/s41591-025-03654-2
Deep learning predicts onset acceleration of 38 age-associated diseases from blood and body composition biomarkers in the UK Biobank, Ji et al, GeroScience, June 2025. https://link.springer.com/article/10.1007/s11357-025-01702-w
Associations between alcohol consumption and gray and white matter volumes in the UK Biobank, Daviet et al, Nature Communications, March 2022. https://www.nature.com/articles/s41467-022-28735-5
Genetic Evidence for Different Adiposity Phenotypes and Their Opposing Influences on Ectopic Fat and Risk of Cardiometabolic Disease, Martin et al, Diabetes, May 2021. https://diabetesjournals.org/diabetes/article/70/8/1843/137911/Genetic-Evidence-for-Different-Adiposity
Calcification of the abdominal aorta is an under-appreciated cardiovascular disease risk factor in the general population, Sethi et al, Frontiers in Cardiovascular Medicine, October 2022. https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2022.1003246/full
Multi-modal machine learning approach for early detection of neurodegenerative diseases leveraging brain MRI and wearable sensor data, Li et al, PLOS Digital Health, April 2025. https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000795
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