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Session: Image Analysis - Cancer
Session starts: Friday 25 January, 13:00
Presentation starts: 13:15
Room: Lecture room 559

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Loes Derikx (Orthopaedic Research Laboratory, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands)
Dennis Janssen (Orthopaedic Research Laboratory, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands)
Yvette van der Linden (Department of Clinical Oncology, Leiden University Medical Center, Leiden, The Netherlands)
An Snyers (Department of Radiation Oncology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands)
Nico Verdonschot (Orthopaedic Research Laboratory, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands and Laboratory of Biomechanical Engineering, University of Twente, Enschede, The Netherlands)
Esther Tanck (Orthopaedic Research Laboratory, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands)

Abstract:
Introduction: Current clinical practice lacks an accurate predictor of the femoral fracture risk in patients suffering metastatic bone disease. This results in large numbers of patients who are over- and undertreated with complex surgery [1, 2]. The aim of this study is to assess whether patient-specific finite element (FE) models are able to discriminate between patients with an unexpected pathological fracture from patients who did not fracture their femur. Methods: Fourteen patients with painful femoral bone metastases with an expected low fracture risk were selected from a cohort of 66 patients. In nine cases patients suffered a uni- or bilateral fracture during follow-up (fracture group, F). Nine femora that did not fracture served as a control group (NF). Patient-specific FE models of these eighteen femora with proven malignancy were generated on the basis of quantitative computed tomography images of the femoral regions. We used four-noded tetrahedral elements and adopted non-linear isotropic material behaviour [3], based on phantom-calibrated grey values in the CT scans. The FE models were loaded until failure using an axial compressive load. The femoral failure load was calculated as the main outcome parameter. The failure location was defined by elements that plastically deformed when the failure load was reached. The mean failure load corrected for body weight, the work and the structural stiffness were compared between the fracture group and non-fracture group using independent T-tests. The predicted fracture locations were compared to clinical reports if available. Results: The FE-predicted failure load in the fracture group was significantly lower than in the non-fracture group (mean difference 3.66*BW, p < 0.01). No significant difference in structural stiffness was found. Good agreement was found between the predicted failure courses and the clinically reported fractures. Discussion: This study showed that patient-specific FE models improve upon current clinical methods in the prediction of fracture risk in metastatic bone disease. In a set of femora with a low fracture risk, FE models correctly differentiated between femora with and without an unexpected fracture by applying only a very simple loading condition. These results will be further validated in a larger patient population using more realistic loading conditions.