Literature DB >> 22258889

Relationships between femoral strength evaluated by nonlinear finite element analysis and BMD, material distribution and geometric morphology.

He Gong1, Ming Zhang, Yubo Fan, Wai Leung Kwok, Ping Chung Leung.   

Abstract

Precise quantification of femur strength and accurate assessment of hip fracture risk would help physicians to identify individuals with high risk and encourage them to take preventive interventions. A major contributing factor of hip fracture is the reduction of hip strength, determined by the bone quality. Bone mineral density (BMD) alone cannot determine bone strength accurately. In this paper, subject-specific quantitative computer tomography (QCT) image-based finite element analyses were conducted to identify the quantitative relationships between femoral strength and BMD, material distribution and geometric morphology. Sixty-six subjects with QCT data of hip region were selected from the MrOS cohorts in Hong Kong. Subject-specific nonlinear finite element models were developed to predict strengths of proximal femurs. The models took non-linear elasto-plasticity and heterogeneity of bone tissues into consideration and derived bone strengths with proper bone failure criteria. From finite element analysis (FEA), relationships between femoral strength and BMD, material distribution, and geometric parameters were determined. Results showed that FEA-predicted femoral strength was highly correlated with BMD, material distribution, height, weight, diameters of femoral head (HD), and femoral neck (ND), as well as the moment arm for femoral neck bending-offset (OFF). Through principal components analysis, three independent principal components (PCs) were extracted. PC1 was the component of bone material quality. PC2 included height, weight, HD, and ND. PC3 mainly represented OFF. Multivariate linear regression showed that the PCs were strongly predictive of the FEA-predicted strength. This study provided quantitative information regarding the contributing factors of proximal femur strength and showed that such a biomechanical approach may have clinical potential in noninvasive assessment of hip fracture risk.

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Year:  2012        PMID: 22258889     DOI: 10.1007/s10439-012-0514-7

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  10 in total

1.  Potential of in vivo MRI-based nonlinear finite-element analysis for the assessment of trabecular bone post-yield properties.

Authors:  Ning Zhang; Jeremy F Magland; Chamith S Rajapakse; Yusuf A Bhagat; Felix W Wehrli
Journal:  Med Phys       Date:  2013-05       Impact factor: 4.071

Review 2.  Are we taking full advantage of the growing number of pharmacological treatment options for osteoporosis?

Authors:  Karl J Jepsen; Stephen H Schlecht; Kenneth M Kozloff
Journal:  Curr Opin Pharmacol       Date:  2014-04-16       Impact factor: 5.547

3.  A High-Intensity Exercise Intervention Improves Older Women Lumbar Spine and Distal Tibia Bone Microstructure and Function: A 20-Week Randomized Controlled Trial.

Authors:  Joao Pedro Pinho; Arturo Forner-Cordero; Rosa Maria Rodrigues Pereira; Arnaldo Jose Hernandez; Egidio Lima Dorea; Bruno Mezencio; Liliam Takayama; Jackeline Couto Alvarenga; Julio Cerca Serrao; Alberto Carlos Amadio
Journal:  IEEE J Transl Eng Health Med       Date:  2020-01-03       Impact factor: 3.316

4.  Study of the significance of parameters and their interaction on assessing femoral fracture risk by quantitative statistical analysis.

Authors:  Rabina Awal; Jalel Ben Hmida; Yunhua Luo; Tanvir Faisal
Journal:  Med Biol Eng Comput       Date:  2022-02-04       Impact factor: 2.602

5.  Biomechanical evaluation of axial-loading simulated experiment in wrist fractures: a finite element analysis.

Authors:  You-Liang Fan; Hai-Yun Xu; Ming-Yang Xia; Wen Zhang; Hui-Long Wen; Li-Bo Gao; Yan-Hui Pei
Journal:  J Int Med Res       Date:  2020-10       Impact factor: 1.671

6.  Prediction of Femoral Strength Based on Bone Density and Biochemical Markers in Elderly Men With Type 2 Diabetes Mellitus.

Authors:  Shaowei Jia; He Gong; Yingying Zhang; Hongmei Liu; Haipeng Cen; Rui Zhang; Yubo Fan
Journal:  Front Bioeng Biotechnol       Date:  2022-03-28

7.  Biomechanical analysis of the correlation between mid-shaft atypical femoral fracture (AFF) and axial varus deformation.

Authors:  Mathieu Severyns; Dalila Belaid; Kevin Aubert; Ali Bouchoucha; Arnaud Germaneau; Tanguy Vendeuvre
Journal:  J Orthop Surg Res       Date:  2022-03-15       Impact factor: 2.359

8.  Assessment of Hip Fracture Risk Using Cross-Section Strain Energy Determined by QCT-Based Finite Element Modeling.

Authors:  Hossein Kheirollahi; Yunhua Luo
Journal:  Biomed Res Int       Date:  2015-10-25       Impact factor: 3.411

9.  Relationship between microstructure, material distribution, and mechanical properties of sheep tibia during fracture healing process.

Authors:  Jiazi Gao; He Gong; Xing Huang; Juan Fang; Dong Zhu; Yubo Fan
Journal:  Int J Med Sci       Date:  2013-09-07       Impact factor: 3.738

Review 10.  Quantitative Computed Tomography (QCT) derived Bone Mineral Density (BMD) in finite element studies: a review of the literature.

Authors:  Nikolas K Knowles; Jacob M Reeves; Louis M Ferreira
Journal:  J Exp Orthop       Date:  2016-12-09
  10 in total

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