Assessment of the individual fracture risk of the proximal femur by using statistical appearance models

Medical Physics
Benedikt SchulerRainer Schubert

Abstract

Standard diagnostic techniques to quantify bone mineral density (BMD) include dual-energy x-ray absorptiometry (DXA) and quantitative computed tomography. However, BMD alone is not sufficient to predict the fracture risk for an individual patient. Therefore, the development of tools, which can assess the bone quality in order to predict individual biomechanics of a bone, would mean a significant improvement for the prevention of fragility fractures. In this study, a new approach to predict the fracture risk of proximal femora using a statistical appearance model will be presented. 100 CT data sets of human femur cadaver specimens are used to create statistical appearance models for the prediction of the individual fracture load (FL). Calculating these models offers the possibility to use information about the inner structure of the proximal femur, as well as geometric properties of the femoral bone for FL prediction. By applying principal component analysis, statistical models have been calculated in different regions of interest. For each of these models, the individual model parameters for each single data set were calculated and used as predictor variables in a multilinear regression model. By this means, the best working re...Continue Reading

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Citations

Jun 1, 2013·Current Osteoporosis Reports·Julio Carballido-Gamio, Daniel P Nicolella
Apr 3, 2014·Current Osteoporosis Reports·Isaac Castro-MateosAlejandro F Frangi
Aug 19, 2014·Medical Engineering & Physics·Lorenzo GrassiFulvia Taddei
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Dec 23, 2016·Biomechanics and Modeling in Mechanobiology·Lorenzo GrassiHanna Isaksson
Jun 27, 2019·Annals of Biomedical Engineering·Julio Carballido-GamioXiaoguang Cheng

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