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Prediction of risk of fracture in the tibia due to altered bone mineral density distribution resulting from disuse : a finite element study

Gislason, Magnus and Coupaud, Sylvie and Sasagawa, Keisuke and Tanabe, Yuji and Purcell, Mariel and Allan, David B and Tanner, K. Elizabeth (2014) Prediction of risk of fracture in the tibia due to altered bone mineral density distribution resulting from disuse : a finite element study. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 228 (2). p. 165. ISSN 0954-4119

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The disuse-related bone loss that results from immobilisation following injury shares characteristics with osteoporosis in postmenopausal women and the aged, with decreases in bone mineral density (BMD) leading to weakening of the bone and increased risk of fracture. The aim of the study was to use the finite element method to: (i) calculate the mechanical response of the tibia under mechanical load and (ii) estimate the risk of fracture; comparing between two groups, an able bodied (AB) group and spinal cord injury (SCI) patients group suffering from varying degree of bone loss. The tibiae of eight male subjects with chronic SCI and those of four able-bodied (AB) age-matched controls were scanned using multi-slice peripheral Quantitative Computed Tomography. Images were used to develop full three-dimensional models of the tibiae in Mimics (Materialise) and exported into Abaqus (Simulia) for calculation of stress distribution and fracture risk in response to specified loading conditions – compression, bending and torsion. The percentage of elements that exceeded a calculated value of the ultimate stress provided an estimate of the risk of fracture for each subject, which differed between SCI subjects and their controls. The differences in BMD distribution along the tibia in different subjects resulted in different regions of the bone being at high risk of fracture under set loading conditions, illustrating the benefit of creating individual material distribution models. A predictive tool can be developed based on these models, to enable clinicians to estimate the amount of loading that can be safely allowed onto the skeletal frame of individual patients who suffer from extensive musculoskeletal degeneration (including SCI, multiple sclerosis and the ageing population). The ultimate aim would be to reduce fracture occurrence in these vulnerable groups.