Quantifying the material and structural determinants of bone strength

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748 M.L. Bouxsein, E. Seeman / Best Practice & Research Clinical Rheumatology 23 (2009) 741–753 properties and loading conditions influence the strength predictions. Nonetheless, this state-of-the-art technique is among the most promising tools available today for clinical assessment of bone strength and fracture risk [112]. 3D-QCT (or HR-pQCT) scans are directly converted, voxel by voxel, into a finite element model, which accurately represents the 3D geometry and heterogeneous density distribution of the bone of interest (Fig. 6). Forces simulating activities that cause fractures are applied to this model, and the stiffness and strength of the bone in response to the applied forces are computed. These analyses can incorporate different in vivo loading conditions, such as compressive and bending loading for the vertebrae, or stance and fall loading for the femur. Several studies in human cadaveric femurs, vertebrae and forearms have shown that bone strength is better predicted by FE analyses than by BMD alone [113–116]. Over 15 years ago, Faulkner and colleagues reported that QCT-based FE analysis of vertebral strength discriminated between women with and without vertebral fracture, with less overlap between the two groups than observed using QCT [117]. More recently, QCT-based FE analyses have been shown to discriminate women with vertebral fractures from controls[118] and to explore the mechanisms underlying increased bone strength following anabolic and/or anti-catabolic treatment[57,119,120,121]. The deleterious effects of glucocorticoids on femoral strength have also been explored by in vivo QCT-based FE analyses [122]. In postmenopausal women matched for age, weight and history of hormone therapy, FE analyses showed that femoral strength in women with a history of glucocorticoid use was w15% lower than controls for both fall-loading and stance configurations. The feasibility of in vivo micro-FEA using both MR and HR-pQCT has also been demonstrated in clinical studies [78,82,123,124]. High-resolution MR images of trabecular bone in the distal radius were subjected to FE analysis to determine effects of trabecular microarchitecture on bone mechanical properties in normal and osteopenic postmenopausal women [123]. MR images of trabecular architecture in the calcaneus were also assessed using FE to quantify the response to 1 year idoxifene [124]. In both cases, the use of FE analysis provided additional information regarding bone structure and strength to that available from structure measurements alone. Thus, this approach warrants further investigation. However, because this technique presently requires extensive computational resources and specialised software, widespread evaluation will likely be limited. To date, there are few data on the precision of the technique and its ability to reflect disease- and age-related changes, and no prospective fracture studies exist. However, cross-sectional studies using HR-pQCT have shown the FEA-based strength estimates discriminate women with prior history of distal radius fracture [76,82]. Improved imaging and computational methods have made subject-specific FE analyses more feasible, and further technological advances will continue. Fig. 6. Finite element model of the proximal femur in a sideways fall configuration. Colors represent plastic strain, showing likely regions of failure. Image courtesy of Dr. David Kopperdahl, O.N. Diagnostics.
Conclusions Novel non-invasive techniques for assessment of the structural determinants of bone strength are available. These techniques quantify the macro- and microstructure of bone such as bone size, shape, cortical thickness, cortical density, a surrogate of cortical porosity, trabecular number, thickness and separation. FE analysis, by combining bone geometry with material characteristics, provides good estimates of whole bone strength. Whether these strength and/or morphological features singly or together will improve fracture prediction or serve as surrogates of anti-fracture efficacy is not known. Although several studies provide promising data for these technique, these methodologies remain research tools as most have not been rigorously tested for their ability to predict fracture risk in prospective studies and to monitor treatment response. Use of 3D imaging modalities to assess the determinants of bone strength is a research area of high interest and relevance to clinicians. However, there is a need for additional developments and studies to determine the clinical utility of these imaging modalities. Future research is aimed at developing techniques that are better suited to assess those at highest risk of fracture, to diagnose patients early in the disease process, to identify specific treatable components of skeletal fragility and to monitor treatment efficacy. These developments are needed given the inevitable future of a growing elderly population combined with shrinking resources for medical care. Acknowledgements We thank Drs. Sharmala Majumdar, Claus Glüer, Thomas Lang and David Kopperdahl for generously providing images. References M.L. Bouxsein, E. Seeman / Best Practice & Research Clinical Rheumatology 23 (2009) 741–753 749 [1] U.S. Department of Health and Human Services. Bone health and osteoporosis: a report of the surgeon general. Rockville, MD: U.S. Department of Health and Human Services, Office of the Surgeon General; 2004. [2] Rosen CJ. Clinical practice. Postmenopausal osteoporosis. N Engl J Med 2005;353(6):595–603. [3] Seeman E, Compston J, Adachi J, et al. Non-compliance: the Achilles’ heel of anti-fracture efficacy. Osteoporos Int 2007;18(6):711–9. [4] Proceedings of a symposium. Consensus Development Conference on Osteoporosis. October 19–20, 1990, Copenhagen, Denmark. Am J Med 1991;91(5B):1S–68. [5] Bouxsein M. Biomechanics of age-related fractures. In: Marcus R, Feldman D, Nelson D, Rosen C, editors. Osteoporosis. 3rd edn., vol. I. San Diego, CA: Elsevier Academic Press; 2007. p. 601–16. [6] Johnell O, Kanis JA, Oden A, et al. Predictive value of BMD for hip and other fractures. J Bone Miner Res 2005;20(7): 1185–94. [7] Siris ES, Chen YT, Abbott TA, et al. Bone mineral density thresholds for pharmacological intervention to prevent fractures. Arch Intern Med 2004;164(10):1108–12. [8] Wainwright SA, Marshall LM, Ensrud KE, et al. Hip fracture in women without osteoporosis. J Clin Endocrinol Metab 2005;90(5):2787–93. [9] Schuit SC, van der Klift M, Weel AE, et al. Fracture incidence and association with bone mineral density in elderly men and women: the Rotterdam Study. Bone 2004;34(1):195–202. [10] Cummings SR. How drugs decrease fracture risk: lessons from trials. J Musculoskelet Neuronal Interact 2002;2(3): 198–200. [11] Sarkar S, Mitlak BH, Wong M, et al. Relationships between bone mineral density and incident vertebral fracture risk with raloxifene therapy. J Bone Miner Res 2002;17(1):1–10. [12] Delmas P, Seeman E. Changes in bone mineral density explain little of the reduction in vertebral or nonvertebral fracture risk with anti-resorptive therapy. Bone 2004;34(4):599–604. [13] Watts NB, Geusens P, Barton IP, Felsenberg D. Relationship between changes in BMD and nonvertebral fracture incidence associated with risedronate: reduction in risk of nonvertebral fracture is not related to change in BMD. J Bone Miner Res 2005;20(12):2097–104. [14] Bouxsein ML. Bone quality: where do we go from here? Osteoporos Int 2003;14(Suppl. 5):118–27. *[15] Seeman E, Delmas PD. Bone quality–the material and structural basis of bone strength and fragility. N Engl J Med 2006;354(21):2250–61. [16] Engelke K, Gluer CC. Quality and performance measures in bone densitometry: part 1: errors and diagnosis. Osteoporos Int 2006;17(9):1283–92. [17] Marshall D, Johnell O, Wedel H. Meta-analysis of how well measures of bone mineral density predict occurrence of osteoporotic fractures. BMJ 1996;312(7041):1254–9. [18] WHO Study Group. Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. Geneva: World Health Organization; 1994. [19] Carter DR, Bouxsein ML, Marcus R. New approaches for interpreting projected bone densitometry. J Bone Miner Res 1992;7:137–45.
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