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3D patient-specific finite element models of the proximal femur based on DXA towards the classification of fracture and non-fracture cases

Research output: Contribution to journalArticle

Carlos Ruiz Wills, Andy Luis Olivares, Simone Tassani, Mario Ceresa, Veronika Zimmer, Miguel A. González Ballester, Luis Miguel del Río, Ludovic Humbert, Jérôme Noailly

Original languageEnglish
Pages (from-to)89-99
Number of pages11
Early online date3 Jan 2019
Publication statusPublished - 1 Apr 2019

King's Authors


Osteoporotic bone fractures reduce quality of life and drastically increase mortality. Minimally irradiating imaging techniques such as dual-energy X-ray absorptiometry (DXA) allow assessment of bone loss through the use of bone mineral density (BMD) as descriptor. Yet, the accuracy of fracture risk predictions remains limited. Recently, DXA-based 3D modelling algorithms were proposed to analyse the geometry and BMD spatial distribution of the proximal femur. This study hypothesizes that such approaches can benefit from finite element (FE)-based biomechanical analyses to improve fracture risk prediction. One hundred and eleven subjects were included in this study and stratified in two groups: (a) 62 fracture cases, and (b) 49 non-fracture controls. Side fall was simulated using a static peak load that depended on patient mass and height. Local mechanical fields were calculated based on relationships between tissue stiffness and BMD. The area under the curve (AUC) of the receiver operating characteristic method evaluated the ability of calculated biomechanical descriptors to discriminate fracture and control cases. The results showed that the major principal stress was better discriminator (AUC > 0.80) than the volumetric BMD (AUC ≤ 0.70). High discrimination capacity was achieved when the analysis was performed by bone type, zone of fracture and gender/sex (AUC of 0.91 for women, trabecular bone and trochanter area), and outcomes suggested that the trabecular bone is critical for fracture discrimination. In conclusion, 3D FE models derived from DXA scans might significantly improve the prediction of hip fracture risk; providing a new insight for clinicians to use FE simulations in clinical practice for osteoporosis management.

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