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A new deep learning model can now read your spine radiograph and estimate its biological age, revealing hidden aging patterns that predict fracture and mortality better than chronological age.
The Discovery:
Researchers from Yonsei University and UCSF developed a convolutional neural network that estimates “spine age” from standard lateral spine radiographs and DXA vertebral fracture assessment (VFA) images. Across over 13,800 participants, this biological spine age proved more accurate than chronological age in predicting osteoporosis, fractures, and death risk, even after adjusting for other risk factors.
The Science:
The model analyzed 10,341 hospital-based and 3,517 community-based Korean participants aged 40 and above.
Spine age outperformed chronological age in detecting existing vertebral fractures (AUROC 0.77 vs. 0.72) and osteoporosis (0.66 vs. 0.52).
For every 1 standard deviation increase in predicted age difference, risk of overall fracture rose by up to 71% in hospital patients and 22% in the community group.
Incorporating spine age instead of chronological age in the FRAX hip fracture calculator improved prediction accuracy (AUROC 0.83 vs. 0.78).
People with accelerated spine aging also showed a 31% higher risk of death, independent of chronological age, sex, and health markers.
Higher spine age correlated with shorter height, lower bone density, diabetes, vertebral fractures, and surgical implants, but these explained only 40% of the variance, suggesting deeper biological mechanisms at play.
Your Action:
Ask your clinician about AI enhanced imaging for bone health. Regular spine and bone density scans, combined with resistance training, calcium and vitamin D intake, and glucose control, can slow musculoskeletal aging.
Protecting your bones now not only reduces fracture risk but also supports overall resilience as you age.
Bottom Line:
Your spine’s biological age may reveal your true fracture and mortality risk, and AI can read it from a simple X ray.
Source:
Spine age estimation using deep learning in lateral spine radiographs and DXA VFA to predict incident fracture and mortality, npj Aging, Cho et al., Yonsei University and UCSF
https://doi.org/10.1038/s41514-025-00271-8
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Disclaimer:
This newsletter is for informational purposes only and does not substitute professional medical advice. Always consult with a healthcare provider before making any changes to your health regimen.