Subject-specific finite element models can accurately predict strain levels in long bones

Schileo, Enrico; Taddei, Fulvia; Malandrino, Andrea; Cristofolini, Luca; Viceconti, Marco

doi:10.1016/j.jbiomech.2007.02.010

Cited by 285 publications

(249 citation statements)

References 53 publications

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“…In addition, several investigations showed that in the case of one-legged stance, only local differences (strains, stresses and displacement) were observed and that the whole mechanical response of the femur (fracture force and fracture location) was quite similar [35,48,67,76,83,91]. Verhulp et al [83] suggested that differences between the isotropic and orthotropic models can be substantially larger for non-stance loading such as lateral falls.…”

Section: Discussionmentioning

confidence: 99%

“…Several FE analyses with inhomogeneous isotropic material properties have been shown to predict the strains and displacements on the surface of the proximal femur with high accuracy when compared with in vitro experiments [35,48,67,76]. The same FE models with inhomogeneous orthotropic material properties produce results similar to those obtained with isotropic material properties [3,58,83].…”

Section: Introductionmentioning

confidence: 87%

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A quasi-brittle continuum damage finite element model of the human proximal femur based on element deletion

Hambli

2012

Med Biol Eng Comput

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 87%

A quasi-brittle continuum damage finite element model of the human proximal femur based on element deletion

Hambli

2012

Med Biol Eng Comput

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“…Researchers have used CT and/or MRI data to derive the morphology, but the segmentation of the objects in the spine from imaging data and the subsequent generation of the finite element mesh are the primary bottlenecks in the construction of subject-specific models. Several methods have been successfully employed in speeding up the segmentation of objects within the spine [31,32]; however, further advances are necessary towards making the image-to-mesh process fully automatic. Although currently, the in vitro testing of motion segments does not fully represent the in vivo conditions, many investigators have compared model simulations with laboratory experiments.…”

Section: Discussionmentioning

confidence: 99%

Establishment and Validation of a Computed Tomography–Based Finite Element Model of Lumbar3-5 Vertebrae

Xia¹,

Zhang²,

Chen³

et al. 2018

dtcse

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Objective: To describe a rapid method for establishing a finite element model of the lumbar vertebrae by using computed tomography (CT) images Methods: CT images of the L3-L5 vertebrae of a 75-year-old man were acquired and used to establish a finite element model using the Minics 10.01 and Hypermesh 11.0 softwares. Soft tissues, such as the intervertebral discs and ligaments, were manually meshed. The model thus generated was subjected to a vertical force of 400 N and a torsion force of 10 N·m to simulate the conditions of the human spine in the standing position. Results: The CT-based finite element model of the lumbar vertebrae was successfully established, accurately reflecting the anatomy of both vertebrae and attached soft tissues. The biomechanical response of the model to the external testing forces was within the accepted normal ranges. Conclusion: We constructed a feasible and accurate CT-based finite element model of the lumbar vertebrae with manually meshing of the soft tissue data. This model showed good consistency with in vitro experimental data. Thus, our method appeared to be useful in the construction of a finite element model of the spine.

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“…Finite element modelling is a powerful tool for computing mechanical stability of the femur [4,5] but requires 3D tissue distribution models. These advances may lead to validation and wider application of minimally invasive cement injection.…”

Section: Discussionmentioning

confidence: 99%

“…Proper pre-operative planning is therefore essential. Femoral strength and stability may be simulated using finite element (FEM) modelling [4,5] Plain radiographs such as in Fig. 1a are the default imaging modality for diagnosing osteolysis [6].…”

Section: Introductionmentioning

confidence: 99%

Voxel classification and graph cuts for automated segmentation of pathological periprosthetic hip anatomy

2012

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Purpose Automated patient-specific image-based segmentation of tissues surrounding aseptically loose hip prostheses is desired. For this we present an automated segmentation pipeline that labels periprosthetic tissues in computed tomography (CT). The intended application of this pipeline is in pre-operative planning. Methods Individual voxels were classified based on a set of automatically extracted image features. Minimum-cost graph cuts were computed on the classification results. The graphcut step enabled us to enforce geometrical containment constraints, such as cortical bone sheathing the femur's interior. The solution's novelty lies in the combination of voxel classification with multilabel graph cuts and in the way label costs were defined to enforce containment constraints.Results The segmentation pipeline was tested on a set of twelve manually segmented clinical CT volumes. The distribution of healthy tissue and bone cement was automatically determined with sensitivities greater than 82% and pathological fibrous interface tissue with a sensitivity exceeding 73%. Specificity exceeded 96% for all tissues. Conclusions The addition of a graph-cut step improved segmentation compared to voxel classification alone. The pipeline described in this paper represents a practical approach to segmenting multitissue regions from CT.

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Subject-specific finite element models can accurately predict strain levels in long bones

Cited by 285 publications

References 53 publications

A quasi-brittle continuum damage finite element model of the human proximal femur based on element deletion

A quasi-brittle continuum damage finite element model of the human proximal femur based on element deletion

Establishment and Validation of a Computed Tomography–Based Finite Element Model of Lumbar3-5 Vertebrae

Voxel classification and graph cuts for automated segmentation of pathological periprosthetic hip anatomy

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