ECTS2013 Poster Presentations Bone biomechanics and quality (28 abstracts)
Prediction of vertebral body stiffness in patients with multiple myeloma using qCT-based finite element models
Graeme Campbell 1 , Christian Graeff 3 , Sarah Giravent 1 , Felix Thomsen 1 , Jaime Pena 1 , A Wulff 1 , A Günther 1 , Claus C Glüer 1 & Jan Borggrefe 1,
1Christian-Albrechts Universität zu Kiel, Kiel, Germany; 2Universitätsklinikum Köln, Köln, Germany; 3GSI Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt, Germany.
Multiple myeloma (MM) is associated with lytic bone destruction leading to high fracture incidence in the vertebrae. Accurate assessment of fracture risk is required for physicians to determine the necessity for surgery. This risk is currently determined by examining lesion size or number; however, this method does not consider the biomechanical attributes of the bone. Finite element (FE) modelling can simulate mechanical loading on vertebral bodies, and estimate mechanical integrity, potentially giving a more reliable prediction of fracture risk.
Vertebral quantitative computed tomography (qCT) scans were evaluated in 60 MM patients, 30 with fracture and 30 without. From the images, in-house software was used to generate linear FE models that consisted of tetrahedral elements with transverse isotropic material properties. Elemental stiffness was calculated from local bone mineral density (BMD) values. Uniaxial compression was simulated to a deformation of 1 mm and the apparent level stiffness determined. t-Tests were used to compare stiffness between fracture and non-fracture groups, and standardized odds ratios (normalized to S.D.) and 95% CIs were calculated. Using structural and mineral data from previous work, correlations between stiffness and bone volume ratio (BV/TV), trabecular BMD (tBMD), trabecular separation (TbSp), and cortical BMD (cBMD) were determined.
Vertebral body stiffness in patients with fracture was significantly lower than those without (16.3 vs 23.4 kN/mm, P=0.012), and the age-adjusted logistic regression revealed an OR/S.D. of 3.57 (1.17–10.84). Significant correlations between stiffness and tBMD (R=0.6639, P<0.001), Tb.Sp (R=−0.5255, P<0.001) and cBMD (R=0.52, P<0.001) were observed.
Reduced vertebral stiffness was associated with fracture prevalence, indicating that this is a potential parameter for the assessment of fracture risk in patients with MM. Both trabecular (tBMD, Tb.Sp) and cortical (cBMD) parameters significantly correlated with stiffness. Future work will involve the development of nonlinear FE models in order to predict vertebral strength.
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Bone Abstracts
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