ArticleJBMR plus2025
Cortical bone mechanics technology signal quality maintains robustness across a range of biometric profiles.
Article in JBMR plus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- In vivo mechanical assessment of cortical bone rigidity enhances fracture discrimination beyond DXA in postmenopausal women.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2026Article
- In Vivo Mechanical Assessment of Cortical Bone Rigidity Enhances Fracture Discrimination Beyond DXA in Postmenopausal Women.medRxiv : the preprint server for health sciences · 2025Article
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Authors and funding
11 authors.
Funding
Abstract
Current methods of diagnosing osteoporosis, such as DXA, have limitations in predicting fracture risk. Cortical bone mechanics technology (CBMT) offers a novel approach by using a three-point bend test with multifrequency vibration analysis to directly measure ulnar bending stiffness and calculate flexural rigidity, a mechanical property highly predictive of whole-bone strength under bending conditions. Cortical bone mechanics technology targets the diaphyseal ulna, a site composed primarily of cortical bone, enhancing its specificity for cortical bone quality. In this study of 388 postmenopausal women, we developed and validated a 20-point signal quality indicator (SQI) scoring system to quantify CBMT signal quality and evaluated its relationship to biometric characteristics. The SQI was developed through expert assessment of representative frequency response function (vibration data) trials and refined over 17 iterations. The final system achieved excellent classification performance (AUC = 0.974; sensitivity, specificity, and accuracy all >97%). A total of 22 740 trials were collected across 758 total arm tests, sampling 10 ulnar sites per arm under three vibration amplitudes. Two expert analysts evaluated signal features associated with high signal quality. The resulting SQI is fully automated and provides real-time feedback. All correlations between SQI scores and biometric attributes were weak or very weak (|ρ| < 0.30). The correlations with body weight (ρ = -0.11), BMI (ρ = -0.12), ulnar BMD (ρ = -0.17), CBMT-derived flexural rigidity (ρ = -0.28), and grip strength (ρ = 0.17) were statistically significant (
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Registered trials
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