header advert
Results 1 - 2 of 2
Results per page:
Applied filters
Content I can access

Include Proceedings
Dates
Year From

Year To
Orthopaedic Proceedings
Vol. 96-B, Issue SUPP_11 | Pages 75 - 75
1 Jul 2014
Farinella G Viceconti M Schileo E Falcinelli C Yang L Eastell R
Full Access

Summary

A retrospective study on 98 patients shows that FE-based bone strength from CT data (using validated FE models) is a suitable candidate to discriminate fractured versus controls within a clinical cohort.

Introduction

Subject-specific Finite element models (FEM) from CT data are a promising tool to non-invasively assess the bone strength and the risk of fracture of bones in vivo in individual patients. The current clinical indicators, based on the epidemiological models like the FRAX tool, give limitation estimation of the risk of femoral neck fracture and they do not account for the mechanical determinants of the fracture. Aim of the present study is to prove the better predictive accuracy of individualised computer models based a CT-FEM protocol, with the accuracy of a widely used standard of care, the FRAX risk indicator.


Orthopaedic Proceedings
Vol. 96-B, Issue SUPP_11 | Pages 186 - 186
1 Jul 2014
Falcinelli C Schileo E Balistreri L Baruffaldi F Toni A Albisinni U Ceccarelli F Milandri L Viceconti M Taddei F
Full Access

Summary Statement

In a retrospective study, FE-based bone strength from CT data showed a greater ability than aBMD to discriminate proximal femur fractures versus controls.

Introduction

Personalised Finite Element (FE) models from Computed Tomography (CT) data are superior to bone mineral density (BMD) in predicting proximal femoral strength in vitro [Cody, 1999]. However, results similar to BMD were obtained in vivo, in retrospective classification of generic prevalent fractures [Amin, 2011] and in prospective classification of femoral fractures [Orwoll, 2009]. The aim of this work is to test, in a case-control retrospective study, the ability of a different, validated FE modelling procedure [Schileo, 2008] to: (i) discriminate between groups of proximal femoral fractures and controls; (ii) individually classify fractures and controls.