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Multimodal population brain imaging in the UK Biobank prospective epidemiological study
Open accessAbstract
Medical imaging has enormous potential for early disease prediction, but is impeded by the difficulty and expense of acquiring data sets before symptom onset. UK Biobank aims to address this problem directly by acquiring high-quality, consistently acquired imaging data from 100,000 predominantly healthy participants, with health outcomes being tracked over the coming decades. The brain imaging includes structural, diffusion and functional modalities. Along with body and cardiac imaging, genetics, lifestyle measures, biological phenotyping and health records, this imaging is expected to enable discovery of imaging markers of a broad range of diseases at their earliest stages, as well as provide unique insight into disease mechanisms. We describe UK Biobank brain imaging and present results derived from the first 5,000 participants' data release. Although this covers just 5% of the ultimate cohort, it has already yielded a rich range of associations between brain imaging and other measures collected by UK Biobank.
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“UK Biobank [106] is a large-scale, influential biomedical database and research resource containing genetic and health data from half a million participants.”
From Federated learning for medical image analysis: A survey (2024) · cites this paper as [106]
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Metadata
- Authors
- Miller, K. L., Alfaro-Almagro, F., Bangerter, N. K., Thomas, D. L., Yacoub, E., Xu, J., Bartsch, A. J., Jbabdi, S., Sotiropoulos, S. N., Andersson, J. L. R., Griffanti, L., Douaud, G., Okell, T. W., Weale, P., Dragonu, I., Garratt, S., Hudson, S., Collins, R., Jenkinson, M., Matthews, P. M., & Smith, S. M.
- Affiliations
- University of Oxford (GB)
- Brigham Young University (US)
- UCL Queen Square Institute of Neurology (GB)
- University of Minnesota (US)
- Icahn School of Medicine at Mount Sinai (US)
- Heidelberg University (DE)
- Siemens (United Kingdom) (GB)
- UK Biobank (GB)
- Imperial College London (GB)
- Corresponding author
- Miller, Karla L
- ORCID
- Venue
- Nature Neuroscience
- Published
- 2016-09-19
- Volume
- 19
- Issue
- 11
- Pages
- 1523-1536
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- PMC
- PMC5086094
- OpenAlex
- W2522628945
- Cited by
- 2,020
- References
- 86
- Citations by year
- 2026: 198 · 2025: 281 · 2024: 357 · 2023: 243 · 2022: 240 · 2021: 232 · 2020: 183 · 2019: 128 · 2018: 88 · 2017: 62 · 2016: 7
- FWCI
- 82.42
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Repository@Nottingham (University of Nottingham) (acceptedVersion, other-oa)
- Nottingham ePrints (University of Nottingham) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Minerva Access (University of Melbourne) (submittedVersion)
- Spiral (Imperial College London) (submittedVersion)
- Funders
- Wellcome Trust (202788/Z/16/Z)
- National Institute for Health and Care Research (NF-SI-0514-10022)
- Parkinson's UK (J-1403)
- Medical Research Council (MR/L009013/1, MC_PC_12027, MR/M024903/1, MR/K006673/1, MC_PC_15067)
- Engineering and Physical Sciences Research Council (EP/N014529/1, EP/L023067/1)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- UK Biobank, neuroimaging, multimodal neuroimaging, structural MRI, diffusion MRI, functional MRI, imaging biomarkers, early disease prediction, disease mechanisms
- MeSH terms
- Adult, Aged, Brain, Female, United Kingdom, Humans, Male, Middle Aged, Prospective Studies, Risk Factors, Epidemiologic Studies, Biological Specimen Banks, Neuroimaging
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