@ImagingFat

Professor of Metabolic Imaging, applying precision phenotyping to disease processes. @RCOptimalHealth, University of Westminster. All views my own.

 London, England
westminster.ac.uk/about-us/our-people/directory/thomas-louise
Joined April 2012
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THREAD: We have 3 new papers, one shared goal; mapping musculoskeletal health at scale. 1/ Our new study in the European Spine Journal of fully automated Cobb angle estimation across 33,889 @uk_biobank MRI scans, enabling population‑level assessment of spinal curvature.
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7/ Read the full paper here: doi.org/10.1038/s41598-026-6… Huge congratulations to 1. Marili Niglas, 2. Marjola Thanaj and 3. Brandon Whitcher for leading these research projects.

Heterogeneity, longitudinal decline, and metabolic risk in MRI-based quantification of 20 individ...

Scientific Reports - Heterogeneity, longitudinal decline, and metabolic risk in MRI-based quantification of 20 individual hip and thigh muscles

nature.com
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8/ Together, these studies form a unified step forward: large‑scale, automated musculoskeletal phenotyping that connects spinal curvature, muscle composition, metabolic health, and disease risk. 🧵 End.
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New paper out! nature.com/articles/s43856-0… Using data from 32,961 @uk_biobank participants, we compared DXA vs MRI for body composition. Key takeaways: DXA works well for fat measures. It overestimates lean mass vs MRI.

Comparing DXA and MRI body composition measurements in cross-sectional and longitudinal cohorts

Communications Medicine - Basty et al. compare DXA and MRI measurements of body fat and muscle in over 32,000 UK Biobank participants, including some repeat scans after about two and a half years....

nature.com
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MRI shows a 4–5% muscle/lean mass decline over ~2.5 years — missed by DXA. Bottom line: DXA is practical at scale, but MRI gives a more precise picture of lean mass change, especially in ageing and longitudinal studies.
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Using deep learning on 44k @uk_biobank abdominal MRIs, we mapped heart and vascular structures, linked these traits to CVD risk, and uncovered 15 new genetic associations. Abdominal MRI is a powerful, untapped tool for understanding cardiovascular health rdcu.be/e5f3C
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I was ridiculously excited to meet @AuntMinnie today! You never know what’s going to happen next at @RSN. There is just so much to explore. A fantastic first day #RSNA25
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Metabolic Imaging retweeted
Perspectum
@PerspectumGroup10 Sep 2025
We’re proud to share the publication of a new paper in the Journal of Abdominal Radiology on automated MRI quantification of body fat and skeletal muscle. Study highlights: ✅ For clinicians: A rapid, single-slice assessment of body fat and muscle, strongly correlated with gold-standard volumetric measures, to support routine monitoring, triage, and decision-making. 💊 For pharma: Trial-ready volumetric MRI biomarkers for body composition, validated against expert manual segmentations and interchangeable across methods and vendors, enabling objective, scalable endpoints in obesity, cardiometabolic and musculoskeletal trials 👏 Congratulations to Magdalena Nowak, Luis Núñez, Charles E. Hill, Tim Pagliaro, John McGonigle, Marili Niglas, Camilo Bell-Bradford, Matthew Robson, Helena Thomaides Brears, E. Louise Thomas, and Jimmy D. Bell on this important contribution. 🔗 link.springer.com/article/10… 👉 BBC bbc.co.uk/news/articles/c8d6… #Perspectum #BodyComposition #MedicalImaging #ClinicalResearch #Pharma #ClinicalTrials #UKBiobank #Collaboration
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Metabolic Imaging retweeted
UK Biobank@uk_biobank14 Aug 2025
All speaker presentations from last month's 100K Imaging Project celebration at the Royal Society are now available to view ✅
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Wonderful to see out graduating students walk across the stage at the Royal Festival Hall this afternoon. What a joyous celebration of their achievement, congratulations to all of our graduates and their families 🎓@UniWestminster
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Please to share our latest @RCOptimalHealth paper led by Elena Sorokin and @YaghootkarH now published in @FrontGenetics @LifeSciWestmin frontiersin.org/journals/gen…

Frontiers | Genetic subtypes of type 2 diabetes are distinguished through the lens of abdominal MRI

ObjectiveThis study seeks to understand type 2 diabetes (T2D) heterogeneity through detailed phenotypic characterization of various T2D genetic subtypes usin...

frontiersin.org
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Metabolic Imaging retweeted
UK Biobank@uk_biobank16 Jul 2025
Yesterday, we announced that our Imaging Project achieved the original goal of scanning 100,000 participants. ✅ Learn more about how the altruism of 100K volunteers is positively impacting health research here: ukbiobank.ac.uk/discoveries-…
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Many congratulations to the @uk_biobank for reaching this extraordinary milestone. We are so proud to see the fantastic research of our @RCOptimalHealth team led by Prof Louise Thomas (@ImagingFat) and Prof Jimmy Bell being featured in the press coverage today.
UK Biobank@uk_biobank15 Jul 2025
100,000 Participants scanned ✅ We are delighted to have completed the world's largest whole body imaging project, scanning the brains, hearts, abdomens, blood vessels, bones and joints of 100,000 volunteers.
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Also out this week in @IntJObesity Changes in abdominal subcutaneous adipose tissue thickness associate with disease and anthropometric factors led by our fantastic Marjola Thanaj @uk_biobank @LifeSciWestmin @RCOptimalHealth nature.com/articles/s41366-0…

Changes in abdominal subcutaneous adipose tissue thickness associate with disease and anthropomet...

International Journal of Obesity - Changes in abdominal subcutaneous adipose tissue thickness associate with disease and anthropometric factors

nature.com
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Our new publication: Deep learning predicts onset acceleration of 38 age-associated diseases from blood and body composition biomarkers in the UK Biobank led by our brilliant Mica Xu Ji @GeroScienceAGE @uk_biobank @LifeSciWestmin @RCOptimalHealth link.springer.com/article/10…

Deep learning predicts onset acceleration of 38 age-associated diseases from blood and body...

GeroScience - A major challenge in multimorbid aging is understanding how diseases co-occur and identifying high-risk groups for accelerated disease development, but to date associations in the...

link.springer.com
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