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Prediction of Collapse Using Patient‐Specific Finite Element Analysis of Osteonecrosis of the Femoral Head

Authors :
Tai‐xian Li
Ze‐qing Huang
Yan Li
Zhi‐peng Xue
Ji‐gao Sun
Huan‐huan Gao
Hai‐jun He
Wei‐heng Chen
Source :
Orthopaedic Surgery, Vol 11, Iss 5, Pp 794-800 (2019)
Publication Year :
2019
Publisher :
Wiley, 2019.

Abstract

Objective To develop a prediction method for femoral head collapse by using patient‐specific finite element analysis of osteonecrosis of the femoral head (ONFH). Methods The retrospective study recruited 40 patients with ARCO stage‐II ONFH (40 pre‐collapse hips). Patients were divided into two groups according to the 1‐year follow‐up outcomes: patient group without femoral head collapse (noncollapse group, n = 20) and patient group with collapse (collapse group, n = 20). CT scans of the hip were performed for all patients once they joined the study. Patient‐specific finite element models were generated based on these original CT images following the same procedures: segmenting the necrotic lesion and viable proximal femur, meshing the computational models, assigning different material properties according to the Hounsfield unit distribution, simulating the stress loading of the slow walking gait, and measuring the distribution of the von Mises stress. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive performance of the maximum level of the von Mises stress. The optimal cut‐off value was selected based on the Youden index and the corresponding predictive accuracy was reported as well. Results The mean level of the maximum von Mises stress in the collapse group was 2.955 ± 0.539 MPa, whereas the mean stress level in the noncollapse group was 1.923 ± 0.793 MPa (P

Details

Language :
English
ISSN :
17577861 and 17577853
Volume :
11
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Orthopaedic Surgery
Publication Type :
Academic Journal
Accession number :
edsdoj.02534adf8f3248de97b58e899988abe1
Document Type :
article
Full Text :
https://doi.org/10.1111/os.12520