C M Langton1, S Pisharody, J H Keyak. 1. Institute of Health & Biomedical Innovation and School of Physical & Chemical Sciences, Queensland University of Technology, Brisbane 4001, Queensland, Australia. christian.langton@qut.edu.au
Abstract
INTRODUCTION: Bone mineral density (BMD) is currently the preferred surrogate for bone strength in clinical practice. Finite element analysis (FEA) is a computer simulation technique that can predict the deformation of a structure when a load is applied, providing a measure of stiffness (N mm(-1)). Finite element analysis of X-ray images (3D-FEXI) is a FEA technique whose analysis is derived from a single 2D radiographic image. METHODS: 18 excised human femora had previously been quantitative computed tomography scanned, from which 2D BMD-equivalent radiographic images were derived, and mechanically tested to failure in a stance-loading configuration. A 3D proximal femur shape was generated from each 2D radiographic image and used to construct 3D-FEA models. RESULTS: The coefficient of determination (R(2)%) to predict failure load was 54.5% for BMD and 80.4% for 3D-FEXI. CONCLUSIONS: This ex vivo study demonstrates that 3D-FEXI derived from a conventional 2D radiographic image has the potential to significantly increase the accuracy of failure load assessment of the proximal femur compared with that currently achieved with BMD. This approach may be readily extended to routine clinical BMD images derived by dual energy X-ray absorptiometry.
INTRODUCTION: Bone mineral density (BMD) is currently the preferred surrogate for bone strength in clinical practice. Finite element analysis (FEA) is a computer simulation technique that can predict the deformation of a structure when a load is applied, providing a measure of stiffness (N mm(-1)). Finite element analysis of X-ray images (3D-FEXI) is a FEA technique whose analysis is derived from a single 2D radiographic image. METHODS: 18 excised human femora had previously been quantitative computed tomography scanned, from which 2D BMD-equivalent radiographic images were derived, and mechanically tested to failure in a stance-loading configuration. A 3D proximal femur shape was generated from each 2D radiographic image and used to construct 3D-FEA models. RESULTS: The coefficient of determination (R(2)%) to predict failure load was 54.5% for BMD and 80.4% for 3D-FEXI. CONCLUSIONS: This ex vivo study demonstrates that 3D-FEXI derived from a conventional 2D radiographic image has the potential to significantly increase the accuracy of failure load assessment of the proximal femur compared with that currently achieved with BMD. This approach may be readily extended to routine clinical BMD images derived by dual energy X-ray absorptiometry.
Authors: Fabio M Ulivieri; Barbara C Silva; Francesco Sardanelli; Didier Hans; John P Bilezikian; Renata Caudarella Journal: Endocrine Date: 2014-05-23 Impact factor: 3.633
Authors: Chamith S Rajapakse; Alexander R Farid; Daniel C Kargilis; Brandon C Jones; Jae S Lee; Alyssa J Johncola; Alexandra S Batzdorf; Snehal S Shetye; Michael W Hast; Gregory Chang Journal: Bone Date: 2020-01-09 Impact factor: 4.398
Authors: Dan Dragomir-Daescu; Jorn Op Den Buijs; Sean McEligot; Yifei Dai; Rachel C Entwistle; Christina Salas; L Joseph Melton; Kevin E Bennet; Sundeep Khosla; Shreyasee Amin Journal: Ann Biomed Eng Date: 2010-10-29 Impact factor: 3.934