Morin SN, Feldman S, Funnell L, Giangregorio L, Kim S, McDonald-Blumer H, et al. Clinical practice guideline for management of osteoporosis and fracture prevention in Canada: 2023 update. Can Med Assoc J. 2023;195(39):E1333-48. https://doi.org/10.1503/cmaj.221647.

Article  Google Scholar 

Nikitovic M, Wodchis WP, Krahn MD, Cadarette SM. Direct health-care costs attributed to hip fractures among seniors: a matched cohort study. Osteoporos Int. 2013;24(2):659–69. https://doi.org/10.1007/s00198-012-2034-6.

Article  CAS  PubMed  Google Scholar 

Roux S, Cabana F, Carrier N, Beaulieu M, April PM, Beaulieu MC, et al. The World Health Organization fracture risk assessment tool (FRAX) underestimates incident and recurrent fractures in consecutive patients with fragility fractures. J Clin Endocrinol Metab. 2014;99(7):2400–8. https://doi.org/10.1210/jc.2013-4507.

Article  CAS  PubMed  Google Scholar 

Cosman F, De Beur SJ, LeBoff MS, Lewiecki EM, Tanner B, Randall S, et al. Clinician’s guide to prevention and treatment of osteoporosis. Osteoporos Int. 2014;25(10):2359–81. https://doi.org/10.1007/s00198-014-2794-2.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Schini M, Johansson H, Harvey NC, Lorentzon M, Kanis JA, McCloskey EV. An overview of the use of the fracture risk assessment tool (FRAX) in osteoporosis. J Endocrinol Invest. 2023;47(3):501–11. https://doi.org/10.1007/s40618-023-02219-9.

Article  PubMed  PubMed Central  Google Scholar 

Schuit SCE, Van Der Klift M, Weel AEAM, De Laet CEDH, Burger H, Seeman E, et al. Fracture incidence and association with bone mineral density in elderly men and women: the Rotterdam study. Bone. 2004;34(1):195–202. https://doi.org/10.1016/j.bone.2003.10.001.

Article  CAS  PubMed  Google Scholar 

Sarkalkan N, Weinans H, Zadpoor AA. Statistical shape and appearance models of bones. Bone. 2014;60:129–40. https://doi.org/10.1016/j.bone.2013.12.006.

Article  PubMed  Google Scholar 

Heimann T, Meinzer HP. Statistical shape models for 3D medical image segmentation: a review. Med Image Anal. 2009;13(4):543–63. https://doi.org/10.1016/j.media.2009.05.004.

Article  PubMed  Google Scholar 

Castro-Mateos I, Pozo JM, Cootes TF, Wilkinson JM, Eastell R, Frangi AF. Statistical shape and appearance models in osteoporosis. Curr Osteoporos Rep. 2014;12(2):163–73. https://doi.org/10.1007/s11914-014-0206-3.

Article  PubMed  Google Scholar 

Brett AD, Brown JK. Quantitative computed tomography and opportunistic bone density screening by dual use of computed tomography scans. J Orthop Transl. 2015;3(4):178–84. https://doi.org/10.1016/j.jot.2015.08.006.

Article  Google Scholar 

Gazzotti S, Aparisi Gómez MP, Schileo E, Taddei F, Sangiorgi L, Fusaro M, et al. High-resolution peripheral quantitative computed tomography: research or clinical practice? Br J Radiol. 2023;96(1150):20221016. https://doi.org/10.1259/bjr.20221016.

Article  PubMed  PubMed Central  Google Scholar 

Cordes C, Baum T, Dieckmeyer M, Ruschke S, Diefenbach MN, Hauner H, et al. MR-based assessment of bone marrow fat in osteoporosis, diabetes, and obesity. Front Endocrinol. 2016;7:00074. https://doi.org/10.3389/fendo.2016.00074.

Article  Google Scholar 

Sangondimath G, Sen RK, Fr T. DEXA and imaging in osteoporosis. Indian J Orthop. 2023;57(S1):82–93. https://doi.org/10.1007/s43465-023-01059-2.

Article  PubMed  PubMed Central  Google Scholar 

Hammadi IO, Dawah Abas A, Hammad Ayed K. Face recognition using deep learning methods a review. Int J Eng Technol. 2019;7(4):6181–8. https://doi.org/10.14419/ijet.v7i4.22375.

Article  Google Scholar 

Yao IZ, Dong M, Hwang WYK. Deep learning applications in clinical cancer detection: a review of implementation challenges and solutions. Mayo Clin Proc Digit Health. 2025;3(3):100253. https://doi.org/10.1016/j.mcpdig.2025.100253.

Article  PubMed  PubMed Central  Google Scholar 

Huppe M, Myant CW. 3D tibial HU reconstruction from biplanar X-rays utilizing a hybrid PCA-CNN framework. Comput Biol Med. 2026;202:111434. https://doi.org/10.1016/j.compbiomed.2025.111434.

Article  PubMed  Google Scholar 

Jazinizadeh F, Quenneville CE. 3D analysis of the proximal femur compared to 2D analysis for hip fracture risk prediction in a clinical population. Ann Biomed Eng. 2021;49(4):1222–32. https://doi.org/10.1007/s10439-020-02670-2.

Article  PubMed  Google Scholar 

Aldieri A, Bhattacharya P, Paggiosi M, Eastell R, Audenino AL, Bignardi C, et al. Improving the hip fracture risk prediction with a statistical shape-and-intensity model of the proximal femur. Ann Biomed Eng. 2022;50(2):211–21. https://doi.org/10.1007/s10439-022-02918-z.

Article  PubMed  PubMed Central  Google Scholar 

Aldieri A, Paggiosi M, Eastell R, Bignardi C, Audenino AL, Bhattacharya P, et al. DXA-based statistical models of shape and intensity outperform aBMD hip fracture prediction: A retrospective study. Bone. 2024;182:117051. https://doi.org/10.1016/j.bone.2024.117051.

Article  PubMed  Google Scholar 

Scott S, Hashmi A, Ebsim R, Jung M, Saunders FR, Gregory JS, et al. DXA-derived hip shape is associated with hip fracture: a longitudinal study of 38 123 UK Biobank participants. J Bone Miner Res. 2025. https://doi.org/10.1093/jbmr/zjaf171.

Article  PubMed  PubMed Central  Google Scholar 

Tobias JH, Nethander M, Faber BG, Heppenstall SV, Ebsim R, Cootes T, et al. Femoral neck width genetic risk score is a novel independent risk factor for hip fractures. J Bone Miner Res. 2024;39(3):241–51. https://doi.org/10.1093/jbmr/zjae002.

Article  CAS  PubMed  PubMed Central  Google Scholar 

O’Rourke D, Beck BR, Harding AT, Watson SL, Pivonka P, Martelli S. Assessment of femoral neck strength and bone mineral density changes following exercise using 3D-DXA images. J Biomech. 2021;119:110315. https://doi.org/10.1016/j.jbiomech.2021.110315.

Article  PubMed  Google Scholar 

O’Rourke D, Beck BR, Harding AT, Watson SL, Pivonka P, Martelli S. Geometry and bone mineral density determinants of femoral neck strength changes following exercise. Biomech Model Mechanobiol. 2023;22(1):207–16. https://doi.org/10.1007/s10237-022-01642-w.

Article  PubMed  Google Scholar 

Grassi L, Fleps I, Sahlstedt H, Väänänen SP, Ferguson SJ, Isaksson H, et al. Validation of 3D finite element models from simulated DXA images for biofidelic simulations of sideways fall impact to the hip. Bone. 2021;142:115678. https://doi.org/10.1016/j.bone.2020.115678.

Article  PubMed  Google Scholar 

Steiner L, Synek A, Pahr DH. Femoral strength can be predicted from 2D projections using a 3D statistical deformation and texture model with finite element analysis. Med Eng Phys. 2021;93(1):72–82. https://doi.org/10.1016/j.medengphy.2021.05.012.

Article  PubMed  Google Scholar 

Taylor M, Viceconti M, Bhattacharya P, Li X. Finite element analysis informed variable selection for femoral fracture risk prediction. J Mech Behav Biomed Mater. 2021;118:104434. https://doi.org/10.1016/j.jmbbm.2021.104434.

Article  PubMed  Google Scholar 

Bevers MSAM, Wyers CE, Daniels AM, Audenaert EA, Van Kuijk SMJ, Van Rietbergen B, et al. Association between bone shape and the presence of a fracture in patients with a clinically suspected scaphoid fracture. J Biomech. 2021;128:110726. https://doi.org/10.1016/j.jbiomech.2021.110726.

Article  PubMed  Google Scholar 

Bruce OL, Baggaley M, Khassetarash A, Haider IT, Edwards WB. Tibial-fibular geometry and density variations associated with elevated bone strain and sex disparities in young active adults. Bone. 2022;161:116443. https://doi.org/10.1016/j.bone.2022.116443.

Article  PubMed  Google Scholar 

Xu Y, Carman L, Besier TF, Choisne J. Prediction accuracy of femoral and tibial stress and strain using statistical shape and density model-based finite element models in paediatrics. Biomech Model Mechanobiol. 2025;24(6):2237–49. https://doi.org/10.1007/s10237-025-02016-8.

Article  PubMed  PubMed Central  Google Scholar 

Kim Y, Lee KW, Lee S, Woo EJ, Hu KS. Age-related morphological changes of the pubic symphyseal surface: using three-dimensional statistical shape modeling. Sci Rep. 2025;15(1):494. https://doi.org/10.1038/s41598-024-84168-8.