BONE STRENGTH AND TECHNIQUES OF ASSESSMENT
Main Article Content
Keywords
bone strength, DEXA, BMD
Abstract
Bone plays a vital role in providing structural support, protecting internal organs, storing minerals, and regulating metabolic and endocrine functions. Bone strength depends on both cortical and trabecular components, which vary in proportion across different skeletal sites. With aging, remodeling imbalances lead to bone loss, microarchitectural deterioration, and osteoporosis—a silent disease often first recognized after fragility fractures. Early detection is crucial to reduce morbidity and healthcare burden. This review discusses current and emerging techniques for assessing bone health and strength. Dual-energy X-ray absorptiometry (DEXA) remains the gold standard for measuring bone mineral density (BMD), although it is influenced by patient positioning, soft tissue composition, and prior fractures. Quantitative computed tomography (QCT), including peripheral and high-resolution variants (pQCT, HR-pQCT), provides three-dimensional assessment and detailed evaluation of trabecular microarchitecture, improving fracture risk prediction. Magnetic resonance imaging (MRI) and spectroscopy offer radiation-free assessment of bone quality, while quantitative ultrasound provides a low-cost, portable screening tool. Emerging modalities such as finite element analysis, electromechanical impedance, microwave frequency methods, and machine learning algorithms show promise for individualized risk assessment and real-time monitoring. Despite these advances, limitations in accessibility, cost, and standardization remain. Integrating these technologies into clinical practice may enhance early diagnosis, optimize treatment strategies, and improve outcomes in patients at risk for osteoporosis and fractures.
References
2. Engelke, K., Libanati, C., Fuerst, T. et al. Advanced CT based In Vivo Methods for the Assessment of Bone Density, Structure, and Strength. Curr Osteoporos Rep 11, 246–255 (2013).
3. Morgan EF, G.U. Unnikrisnan GU, Hussein AI. Bone mechanical properties in healthy and diseased states.Annual review of biomedical engineering: 2018: 20: 119-14
4. Keaveny, TM E.F. Morgan, G.L. Niebur, O.C. YehBiomechanics of trabecular bone Annual review of biomedical engineering,: 2001: 3 (1): 207-333
5. Choksi, P , Jepsen KJ , Clines GA .The challenges of diagnosing osteoporosis and the limitations of currently available tools. Clinical diabetes and endocrinology,: 2018 : 4 (1) : 12
6. W.S.G.o. Prevention, M.o. Osteoporosis, W.H. Organization Prevention and management of osteoporosis: report of a WHO scientific group World Health Organization (2003)
7. Komar C, Ahmed M, Chen A, Richwin H, Zia N, Nazar A, Baue NLAdvancing methods of assessing bone quality to expand screening for osteoporosisJ Am Osteopath Assoc: 2019 : 119 : 147-154
8. Crandall CJ , Ensrud KE. Osteoporosis screening in younger postmenopausal women. Jama : 2020 : 323 (4): 67-368
9. Buckley M., Humphrey B.Glucocorticoid-induced osteoporosis.New England Journal of Medicine: 2018 : 379 (26) : 2547-2556
10. Leslie WD, Adler RA, El-Hajj Fuleihan G, Hodsman AB, Kendler DL, McClung M, Miller PD, Watts NB; International Society for Clinical Densitometry. Application of the 1994 WHO classification to populations other than postmenopausal Caucasian women: the 2005 ISCD Official Positions. J Clin Densitom. 2006 Jan-Mar;9(1):22-30. doi: 10.1016/j.jocd.2006.05.004. Epub 2006 May 12. PMID: 16731428.
11. Messina C, Albano D, Gitto S, Tofanelli L, Bazzocchi A, Ulivieri FM, Guglielmi G, Sconfienza LM. Body composition with dual energy X-ray absorptiometry: from basics to new tools. Quant Imaging Med Surg. 2020 Aug;10(8):1687-1698.
12. Shuhart CR, Yeap SS, Anderson PA, Jankowski LG, Lewiecki EM, Morse LR, Rosen HN, Weber DR, Zemel BS, Shepherd JA. Executive Summary of the 2019 ISCD Position Development Conference on Monitoring Treatment, DXA Cross-calibration and Least Significant Change, Spinal Cord Injury, Peri-prosthetic and Orthopedic Bone Health, Transgender Medicine, and Pediatrics. J Clin Densitom. 2019 Oct-Dec;22(4):453-471.
13. Carey JJ, Delaney MF. Utility of DXA for monitoring, technical aspects of DXA BMD measurement and precision testing. Bone. 2017 Nov;104:44-53
14. Qaseem A, Forciea MA, McLean RM, Denberg TD; Clinical Guidelines Committee of the American College of Physicians; Barry MJ, Cooke M, Fitterman N, Harris RP, Humphrey LL, Kansagara D, McLean RM, Mir TP, Schünemann HJ. Treatment of Low Bone Density or Osteoporosis to Prevent Fractures in Men and Women: A Clinical Practice Guideline Update From the American College of Physicians. Ann Intern Med. 2017 Jun 6;166(11):818-839. doi: 10.7326/M15-1361. Epub 2017 May 9. Erratum in: Ann Intern Med. 2017 Sep 19;167(6):448.
15. Aldieri A, Terzini M, Osella G, Priola AM, Angeli A, Veltri A, Audenino AL, Bignardi C. Osteoporotic Hip Fracture Prediction: Is T-Score-Based Criterion Enough? A Hip Structural Analysis-Based Model. J Biomech Eng. 2018 Nov 1;140(11):111004.
16. Shin YH, Gong HS, Kim KM, Lee JH, Kwon O, Baek GH. Evaluation of Hip Geometry Parameters in Patients With a Distal Radius Fracture. J Clin Densitom. 2020 Oct-Dec;23(4):576-581
17. Aldieri A, Terzini M, Audenino AL, Bignardi C, Morbiducci U. Combining shape and intensity dxa-based statistical approaches for osteoporotic HIP fracture risk assessment. Comput Biol Med. 2020 Dec;127:104093
18. Hathcock JT, Stickle RL. Principles and concepts of computed tomography. Vet Clin North Am Small Anim Pract. 1993 Mar;23(2):399-415.
19. Rietzel E, Pan T, Chen GT. Four-dimensional computed tomography: image formation and clinical protocol. Med Phys. 2005 Apr;32(4):874-89.
20. Nam KH, Seo I, Kim DH, Lee JI, Choi BK, Han IH. Machine Learning Model to Predict Osteoporotic Spine with Hounsfield Units on Lumbar Computed Tomography. J Korean Neurosurg Soc. 2019 Jul;62(4):442-449.
21. Johannesdottir F, Allaire B, Kopperdahl DL, Keaveny TM, Sigurdsson S, Bredella MA, Anderson DE, Samelson EJ, Kiel DP, Gudnason VG, Bouxsein ML. Bone density and strength from thoracic and lumbar CT scans both predict incident vertebral fractures independently of fracture location. Osteoporos Int. 2021 Feb;32(2):261-269.
22. Shiraishi K, Chiba K, Okazaki N, Yokota K, Nakazoe Y, Kidera K, Yonekura A, Tomita M, Osaki M. In vivo analysis of subchondral trabecular bone in patients with osteoarthritis of the knee using second-generation high-resolution peripheral quantitative computed tomography (HR-pQCT). Bone. 2020 Mar;132:115155.
23. Jiang H, Robinson DL, McDonald M, Lee PVS, Kontulainen SA, Johnston JD, Yates CJ, Wark JD. Predicting experimentally-derived failure load at the distal radius using finite element modelling based on peripheral quantitative computed tomography cross-sections (pQCT-FE): A validation study. Bone. 2019 Dec;129:115051
24. Tognarelli JM, Dawood M, Shariff MI, Grover VP, Crossey MM, Cox IJ, Taylor-Robinson SD, McPhail MJ. Magnetic Resonance Spectroscopy: Principles and Techniques: Lessons for Clinicians. J Clin Exp Hepatol. 2015 Dec;5(4):320-8.
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Soumya Ranjan Mohanty
DM Endocrinology & Metabolism Senior resident Department of Endocrinology & Metabolism Institute of Medical Sciences, Banaras Hindu University, Varanasi ORCID id- 0009-0002-3415-7412
Mallavarapu Manisha
DM Endocrinology & Metabolism Senior resident Department of Endocrinology & Metabolism Institute of Medical Sciences, Banaras Hindu University, Varanasi ORCID id- 0009-0003-2801-1449