Fragility fracture risk prediction using quantitative magnetic resonance and Vertebral Bone Quality scoring beyond density.
Authors
Affiliations (8)
Affiliations (8)
- Department of Orthopaedics, Madras Medical College, Chennai 600003, Tamil Nadu, India.
- Department of Orthopaedics, Government Medical College and Hospital, Thiruvallur 602001, Tamil Nadu, India.
- Department of Orthopaedics, ACS Medical College and Hospital, Dr MGR Educational and Research Institute, Chennai 600077, Tamil Nadu, India.
- Department of Regenerative Medicine, Agathisha Institute of Stemcell and Regenerative Medicine, Chennai 600030, Tamil Nadu, India.
- Department of Orthopaedics, Orthopaedic Research Group, Coimbatore 641045, Tamil Nadu, India.
- Department of Orthopaedics, Jawaharlal Institute of Postgraduate Medical Education and Research, Karaikal 609602, Puducherry, India.
- Central Research Laboratory, Meenakshi Medical College Hospital and Research Institute, Meenakshi Academy of Higher Education and Research, Kanchipuram 631552, Tamil Nadu, India.
- Department of Orthopaedics, Orthopaedic Research Group, Coimbatore 641045, Tamil Nadu, India. [email protected].
Abstract
Fragility fractures represent a significant global health burden, with osteoporosis affecting over 500 million individuals and contributing to nearly 9 million fractures annually. Conventional diagnosis relies on dual-energy X-ray absorptiometry (DEXA) to measure bone mineral density (BMD), yet BMD alone explains only part of fracture risk. Many fractures occur in patients without osteoporosis by DEXA criteria, underscoring the limitations of bone quantity-based assessment. Advances in imaging and biomarker research highlight the importance of bone quality, microarchitecture, and marrow composition in fracture prediction. Quantitative magnetic resonance imaging (MRI) techniques - including T1ρ, T2 mapping, proton density fat fraction, and diffusion-weighted imaging - offer non-invasive insights into collagen integrity, proteoglycan content, water distribution, and marrow adiposity. These parameters correlate with trabecular deterioration and cortical porosity, enhancing risk stratification beyond BMD. Similarly, Vertebral Bone Quality (VBQ) scoring, derived from routine T1-weighted MRI, provides a practical surrogate for bone quality by quantifying vertebral marrow signal intensity relative to cerebrospinal fluid. Modified VBQ improves accuracy by minimising posterior vertebral artefacts, demonstrating stronger correlation with DEXA T scores and trabecular microarchitecture. Studies show VBQ predicts vertebral fragility fractures independently of BMD, with sensitivity exceeding 90% and discriminatory ability comparable to the fracture risk assessment tool and trabecular bone score. Integration of quantitative MRI and VBQ/modified VBQ into predictive models, supported by artificial intelligence, enables opportunistic, radiation-free screening and more precise fracture risk assessment. Together, these advanced imaging biomarkers represent a paradigm shift toward comprehensive evaluation of bone strength, bridging the gap between bone quantity and quality for improved prevention and management of fragility fractures.