Metabolic Imaging

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

[Metabolic Imaging @ImagingFat]

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.

[Metabolic Imaging @ImagingFat]

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.

[Metabolic Imaging @ImagingFat]

7/ Read the full paper here: https://t.co/Mxr7qFS132

Huge congratulations to 1. Marili Niglas, 2. Marjola Thanaj and 3. Brandon Whitcher for leading these research projects.

[Metabolic Imaging @ImagingFat]

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.

[Metabolic Imaging @ImagingFat]

New paper out! https://t.co/arvsXDLmN3 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.

[Metabolic Imaging @ImagingFat]

@aifbw @timeshighered These blunt rules ignore people’s real circumstances and risk shutting out exceptional talent. You’re a powerful example of just how much brilliance would be lost @aifbw

[Metabolic Imaging @ImagingFat]

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 https://t.co/VQEChnj9b2

[Metabolic Imaging @ImagingFat]

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

[Perspectum @PerspectumGroup]

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.

🔗 https://t.co/oRT0lGTSJv

👉 BBC https://t.co/7F3kR0vCfr

#Perspectum #BodyComposition #MedicalImaging #ClinicalResearch #Pharma #ClinicalTrials #UKBiobank #Collaboration

[UK Biobank @uk_biobank]

All speaker presentations from last month's 100K Imaging Project celebration at the Royal Society are now available to view ✅

[Metabolic Imaging @ImagingFat]

@davidtroponin @LifeSciWestmin I had no idea that there was a university TikTok account 😂

[Metabolic Imaging @ImagingFat]

@manuelcorpas @NatureGenet Congratulations @manuelcorpas

[School of Life Sciences, University of Westminster @LifeSciWestmin]

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

[Metabolic Imaging @ImagingFat]

@claire76 @pollyhayes Could be this year as I’m in the same outfit 😂

[Metabolic Imaging @ImagingFat]

Please to share our latest @RCOptimalHealth paper led by Elena Sorokin and @YaghootkarH now published in @FrontGenetics @LifeSciWestmin https://t.co/u5V3NVBrnL