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research-article

Osteoporotic hip fracture prediction: is T-score based criterion enough? A Hip Structural Analysis based model

[+] Author and Article Information
Alessandra Aldieri

PolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Corso Duca degli Abruzzi, 24 − 10129 Turin, Italy
alessandra.aldieri@polito.it

Mara Terzini

PolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Corso Duca degli Abruzzi, 24 − 10129 Turin, Italy
mara.terzini@polito.it

Giangiacomo Osella

Department of Clinical and Biological Sciences, Internal Medicine, San Luigi Gonzaga University Hospital, Orbassano, University of Torino, Regione Gonzole 10, 10043 Orbassano, Italy
giangiacomo.osella@gmail.com

Adriano M. Priola

Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Orbassano, University of Torino, Regione Gonzole 10, 10043 Orbassano, Italy
adriano.priola@inwind.it

Alberto Angeli

Department of Internal Medicine, Department of Clinical and Biological Sciences, San Luigi Gonzaga University Hospital, Orbassano, University of Torino, Regione Gonzole 10, 10043 Orbassano, Italy
alberto.angeli@unito.it

Andrea Veltri

Unit of Radiology, Department of Oncology, San Luigi Gonzaga University Hospital, Orbassano, University of Torino, Regione Gonzole 10, 10043 Orbassano, Italy
veltri.andrea@gmail.com

Alberto Audenino

PolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Corso Duca degli Abruzzi, 24 − 10129 Turin, Italy
alberto.audenino@polito.it

Cristina Bignardi

PolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Corso Duca degli Abruzzi, 24 − 10129 Turin, Italy
cristina.bignardi@polito.it

1Corresponding author.

ASME doi:10.1115/1.4040586 History: Received January 26, 2018; Revised May 30, 2018

Abstract

At present, the current gold-standard for osteoporosis diagnosis is based on bone mineral density measurement, which, however, has been demonstrated to poorly estimate fracture risk. Further parameters in the hands of the clinicians are represented by the Hip Structural Analysis (HSA) variables, which include geometric information of the proximal femur cross-section. The purpose of this study was to investigate the suitability of HSA parameters as additional hip fracture risk predictors. With this aim, twenty-eight three-dimensional patient-specific models of the proximal femur were built from CT images and a sideways fall condition was reproduced by finite element analyses. A tensile or compressive predominance based on minimum and maximum principal strains was determined at each volume element and a Risk Factor (RF) was calculated. The power of HSA variables combinations to predict the maximum superficial RF values was assessed by multivariate linear regression analysis. The optimal regression model, identified through the Akaike information criterion, only comprises two variables, the buckling ratio and the neck-shaft angle. In order to validate the study, the model was tested on two additional patients who suffered a hip fracture after a fall. The results classified the patients in the high risk level, confirming the prediction power of the adopted model.

Copyright (c) 2018 by ASME
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