Literature DB >> 19398043

Prediction of proximal femur strength using a CT-based nonlinear finite element method: differences in predicted fracture load and site with changing load and boundary conditions.

Masahiko Bessho1, Isao Ohnishi, Takuya Matsumoto, Satoru Ohashi, Juntaro Matsuyama, Kenji Tobita, Masako Kaneko, Kozo Nakamura.   

Abstract

The annual occurrence of hip fracture due to osteoporosis as of 2002 had reached 120,000 in Japan. The increase has been very rapid. From a biomechanical perspective, hip fractures are thought to be caused in real settings by different directions of loading. Thus, clarification of the loading directions under which the proximal femur is most vulnerable to fracture would be helpful for elucidating fracture mechanics and establishing preventive interventions. The purpose of the current study was to clarify the influence of loading direction on strength and fracture site of the proximal femur using the CT-based nonlinear FE method to determine loading directions under which the proximal femur is most vulnerable to fracture. Contralateral femora were analyzed in 42 women with hip fracture (mean age, 82.4 years), comprising 20 neck fractures and 22 trochanteric fractures. Within 1 week after fracture, quantitative CT of the contralateral femur was performed in each patient and 3-dimensional FE models were created. One stance loading configuration (SC) and four different fall loading configurations (FC) were assigned. Nonlinear FE analysis was performed. Differences in fracture loads depending on differences in loading direction were analyzed and correlations among fracture loads in different loading directions were assessed. Next, fracture sites were also analyzed. Mean predicted fracture load in the SC was 3150 N. Mean fracture loads were 2270 N in FC1, 1060 N in FC2, 980 N in FC3, and 710 N in FC4. The correlation between predicted fracture loads in SC and those in each FC was significant with a correlation coefficient of 0.467-0.631. Predicted fracture sites in the SC appeared at the subcapital region in all patients and were categorized as neck fracture. However, trochanteric fractures occurred in all fall configurations except FC1. In FC1, a significant correlation was seen between real fracture type and predicted type. The current investigation could contribute to the acquisition of useful knowledge allowing the establishment of more efficacious means of preventing hip fractures.

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Year:  2009        PMID: 19398043     DOI: 10.1016/j.bone.2009.04.241

Source DB:  PubMed          Journal:  Bone        ISSN: 1873-2763            Impact factor:   4.398


  24 in total

Review 1.  Advanced CT based in vivo methods for the assessment of bone density, structure, and strength.

Authors:  K Engelke; C Libanati; T Fuerst; P Zysset; H K Genant
Journal:  Curr Osteoporos Rep       Date:  2013-09       Impact factor: 5.096

2.  Interactive graph-cut segmentation for fast creation of finite element models from clinical ct data for hip fracture prediction.

Authors:  Yves Pauchard; Thomas Fitze; Diego Browarnik; Amiraslan Eskandari; Irene Pauchard; William Enns-Bray; Halldór Pálsson; Sigurdur Sigurdsson; Stephen J Ferguson; Tamara B Harris; Vilmundur Gudnason; Benedikt Helgason
Journal:  Comput Methods Biomech Biomed Engin       Date:  2016-05-10       Impact factor: 1.763

3.  Morphological analysis of the acetabular cartilage surface in elderly subjects.

Authors:  Keisuke Akiyama; Takashi Sakai; Junichiro Koyanagi; Hideki Yoshikawa; Kazuomi Sugamoto
Journal:  Surg Radiol Anat       Date:  2015-01-22       Impact factor: 1.246

4.  QCT-based failure analysis of proximal femurs under various loading orientations.

Authors:  Majid Mirzaei; Maziyar Keshavarzian; Fatemeh Alavi; Pegah Amiri; Saeid Samiezadeh
Journal:  Med Biol Eng Comput       Date:  2015-03-03       Impact factor: 2.602

5.  Robust QCT/FEA models of proximal femur stiffness and fracture load during a sideways fall on the hip.

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

Review 6.  Patient-Specific Bone Multiscale Modelling, Fracture Simulation and Risk Analysis-A Survey.

Authors:  Amadeus C S de Alcântara; Israel Assis; Daniel Prada; Konrad Mehle; Stefan Schwan; Lucia Costa-Paiva; Munir S Skaf; Luiz C Wrobel; Paulo Sollero
Journal:  Materials (Basel)       Date:  2019-12-24       Impact factor: 3.623

Review 7.  On challenges in clinical assessment of hip fracture risk using image-based biomechanical modelling: a critical review.

Authors:  Yunhua Luo
Journal:  J Bone Miner Metab       Date:  2021-01-09       Impact factor: 2.626

8.  Patellar morphology and femoral component geometry influence patellofemoral contact stress in total knee arthroplasty without patellar resurfacing.

Authors:  Atsushi Takahashi; Hirotaka Sano; Masahiro Ohnuma; Mitsuhiro Kashiwaba; Daisuke Chiba; Masayuki Kamimura; Takehiko Sugita; Eiji Itoi
Journal:  Knee Surg Sports Traumatol Arthrosc       Date:  2011-11-16       Impact factor: 4.342

9.  Osteoporosis and Hip Fracture Risk From Routine Computed Tomography Scans: The Fracture, Osteoporosis, and CT Utilization Study (FOCUS).

Authors:  Annette L Adams; Heidi Fischer; David L Kopperdahl; David C Lee; Dennis M Black; Mary L Bouxsein; Shireen Fatemi; Sundeep Khosla; Eric S Orwoll; Ethel S Siris; Tony M Keaveny
Journal:  J Bone Miner Res       Date:  2018-04-17       Impact factor: 6.741

Review 10.  A biomechanical sorting of clinical risk factors affecting osteoporotic hip fracture.

Authors:  Y Luo
Journal:  Osteoporos Int       Date:  2015-09-11       Impact factor: 4.507

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