Author Identifier (ORCID)
Abadi K. Gebre: https://orcid.org/0000-0002-1975-0085
Marc Sim: https://orcid.org/0000-0001-5166-0605
Syed Zulqarnain Gilani: https://orcid.org/0000-0002-7448-2327
Afsah Saleem: https://orcid.org/0000-0001-7240-0837
Cassandra Smith: https://orcid.org/0000-0002-2517-2824
Joshua R. Lewis: https://orcid.org/0000-0003-1003-8443
Abstract
Abdominal aortic calcification (AAC), a marker of subclinical cardiovascular disease, has previously shown to be associated with low BMD and fracture. However, it remains unclear whether AAC is associated with trabecular bone score (TBS), a gray-level textural measure, or whether it predicts fracture risk independent of this measure. Here, we examined the cross-sectional association of AAC scored using a validated machine learning algorithm (ML-AAC24) with TBS, and their simultaneous associations with incident fractures in 7691 individuals (93.4% women) through the Manitoba BMD Registry (mean age 75.3 yr). The association between ML-AAC24 and TBS was tested using generalized linear regression. Cox proportional hazards models tested the simultaneous relationships of ML-AAC24 and TBS with incident fractures. At baseline, 41.3% of the study cohort had low (<2), 32.4% had moderate (2 to <6), and 26.3% had high (≥6) ML-AAC24. Compared to low ML-AAC24, high ML-AAC24 was associated with a 0.81% lower TBS in the multivariable-adjusted model. Independent of each other and multiple established fracture risk factors, ML-AAC24 and TBS were each associated with an increased risk of incident fractures. Specifically, high ML-AAC24 (HR 1.41, 95% CI: 1.15-1.73, compared to low ML-AAC24) and lower TBS (HR 1.13, 95% CI: 1.05-1.22, per SD decrease) were associated with increased relative hazards for any incident fracture. High ML-AAC24 and lower TBS were also associated with incident major osteoporotic fracture (HR 1.48, 95% CI: 1.18-1.87 and HR 1.15, 95% CI: 1.06-1.25, respectively) and hip fracture (HR 1.56, 95% CI: 1.05-2.31 and HR 1.25, 95% CI: 1.08-1.44, respectively). In conclusion, high ML-AAC24 is associated with lower TBS in older adults attending routine osteoporosis screening. Both measures were associated with incident fractures. The findings of this study highlight high ML-AAC24, seen in more than 1 in 4 of the study cohort, and lower TBS provide complementary prognostic information for fracture risk.
Keywords
Artificial intelligence, BMD, bone texture, DXA, fracture, vascular calcification
Document Type
Journal Article
Date of Publication
3-30-2026
Volume
41
Issue
4
PubMed ID
41071096
Publication Title
Journal of Bone and Mineral Research
Publisher
Oxford Academic
School
Nutrition and Health Innovation Research Institute / School of Medical and Health Sciences / Centre for Artificial Intelligence and Machine Learning (CAIML) / School of Science
RAS ID
84252
Funders
Rady Innovation Fund, University of Manitoba / Medical Research Future Fund 2022 Cardiovascular Health Mission Grant (2024225) / Royal Perth Hospital Research Foundation Fellowship / Western Australian Future Health Research and Innovation Fund / Raine Medical Research Foundation / National Heart Foundation of Australia (107194, 102817)
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
First Page
406
Last Page
414
Comments
Gebre, A. K., Sim, M., Gilani, S. Z., Saleem, A., Smith, C., Hans, D., Reid, S., Monchka, B. A., Kimelman, D., Jozani, M. J., Schousboe, J. T., Lewis, J. R., & Leslie, W. D. (2026). Automated abdominal aortic calcification and trabecular bone score independently predict incident fracture during routine osteoporosis screening. Journal of Bone and Mineral Research, 41(4), 406–414. https://doi.org/10.1093/jbmr/zjaf144