Finite Element Assessment of Bone Fragility from Clinical Images

2021 ◽  
Author(s):  
Enrico Schileo ◽  
Fulvia Taddei
Keyword(s):  
Finite Element ◽  
Bone Fragility ◽  
Clinical Images

scholarly journals Development of diabetes-sensitive fracture resistance analysis using finite element method to predict diabetic bone fragility and bone quality

Bone Reports ◽  
2021 ◽  
Vol 14 ◽  
pp. 100883
Author(s):  
Cemre Yavuz ◽  
Eva Maria Wölfel ◽  
Katharina Jähn-Rickert ◽  
Herbert Mushumba ◽  
Birgit Wulff ◽  
...  
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Bone Quality ◽  
Fracture Resistance ◽  
Bone Fragility ◽  
Resistance Analysis ◽  
Element Method

Assessment of Bone Fragility in Patients With Multiple Myeloma Using QCT-Based Finite Element Modeling

2016 ◽  
Vol 32 (1) ◽  
pp. 151-156 ◽  
Author(s):  
Graeme M Campbell ◽  
Jaime A Peña ◽  
Sarah Giravent ◽  
Felix Thomsen ◽  
Timo Damm ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Finite Element ◽  
Finite Element Modeling ◽  
Bone Fragility ◽  
Element Modeling

A Predictive Analysis of Wall Stress in Abdominal Aortic Aneurysms Using a Neural Network Model

2021 ◽  
Author(s):  
Balaji Rengarajan ◽  
Sourav Patnaik ◽  
Ender A. Finol
Keyword(s):  
Neural Network ◽  
Finite Element ◽  
Finite Element Modeling ◽  
Wall Stress ◽  
Aortic Aneurysms ◽  
Multivariate Adaptive Regression Splines ◽  
Patient Specific ◽  
Clinical Images ◽  
Element Modeling ◽  
Abdominal Aortic

Abstract In the present work, we investigated the use of geometric indices to predict patient-specific abdominal aortic aneurysm (AAA) wall stress by means of a novel neural network (NN) modeling approach. We conducted a retrospective review of existing clinical images of two patient groups: 98 asymptomatic and 50 symptomatic AAA. The images were subject to a protocol consisting of image segmentation, processing, volume meshing, finite element modeling, and geometry quantification, from which 53 geometric indices and the spatially averaged wall stress (SAWS) were calculated. We developed feed-forward NN models composed of an input layer, two dense layers, and an output layer using Keras, a deep learning library in Python. The NN models were trained, tested, and validated independently for both AAA groups using all geometric indices, as well as a reduced set of indices resulting from a variable reduction procedure. We compared the performance of the NN models with two standard machine learning algorithms (MARS: multivariate adaptive regression splines and GAM: generalized additive model) and a linear regression model (GLM: generalized linear model). The NN-based approach exhibited the highest overall mean goodness-of-fit and lowest overall relative error compared to MARS, GAM, and GLM, when using the reduced sets of indices to predict SAWS for both AAA groups. The use of NN modeling represents a promising alternative methodology for the estimation of AAA wall stress using geometric indices as surrogates, in lieu of finite element modeling.

The Importance of Intrinsic Damage Properties to Bone Fragility: A Finite Element Study

2012 ◽  
Vol 135 (1) ◽  
Author(s):  
M. R. Hardisty ◽  
R. Zauel ◽  
S. M. Stover ◽  
D. P. Fyhrie
Keyword(s):  
Finite Element ◽  
Yield Strength ◽  
Trabecular Bone ◽  
Bone Tissue ◽  
Material Properties ◽  
Mechanical Energy ◽  
Bone Fragility ◽  
Intrinsic Properties ◽  
Microdamage Accumulation ◽  
Apparent Level

As the average age of the population has increased, the incidence of age-related bone fracture has also increased. While some of the increase of fracture incidence with age is related to loss of bone mass, a significant part of the risk is unexplained and may be caused by changes in intrinsic material properties of the hard tissue. This investigation focused on understanding how changes to the intrinsic damage properties affect bone fragility. We hypothesized that the intrinsic (μm) damage properties of bone tissue strongly and nonlinearly affect mechanical behavior at the apparent (whole tissue, cm) level. The importance of intrinsic properties on the apparent level behavior of trabecular bone tissue was investigated using voxel based finite element analysis. Trabecular bone cores from human T12 vertebrae were scanned using microcomputed tomography (μCT) and the images used to build nonlinear finite element models. Isotropic and initially homogenous material properties were used for all elements. The elastic modulus (Ei) of individual elements was reduced with a secant damage rule relating only principal tensile tissue strain to modulus damage. Apparent level resistance to fracture as a function of changes in the intrinsic damage properties was measured using the mechanical energy to failure per unit volume (apparent toughness modulus, Wa) and the apparent yield strength (σay, calculated using the 0.2% offset). Intrinsic damage properties had a profound nonlinear effect on the apparent tissue level mechanical response. Intrinsic level failure occurs prior to apparent yield strength (σay). Apparent yield strength (σay) and toughness vary strongly (1200% and 400%, respectively) with relatively small changes in the intrinsic damage behavior. The range of apparent maximum stresses predicted by the models was consistent with those measured experimentally for these trabecular bone cores from the experimental axial compressive loading (experimental: σmax = 3.0–4.3 MPa; modeling: σmax = 2–16 MPa). This finding differs significantly from previous studies based on nondamaging intrinsic material models. Further observations were that this intrinsic damage model reproduced important experimental apparent level behaviors including softening after peak load, microdamage accumulation before apparent yield (0.2% offset), unload softening, and sensitivity of the apparent level mechanical properties to variability of the intrinsic properties.

A finite element study on intra-operative corrective forces and evaluation of screw density in scoliosis surgeries

2018 ◽  
Vol 232 (12) ◽  
pp. 1245-1254 ◽  
Author(s):  
Ameneh Musapoor ◽  
Mohammad Nikkhoo ◽  
Mohammad Haghpanahi
Keyword(s):  
Finite Element ◽  
Pedicle Screws ◽  
Element Model ◽  
Applied Force ◽  
Patient Specific ◽  
Scoliosis Surgery ◽  
Element Analysis ◽  
Clinical Images ◽  
Significant Difference ◽  
Screw Density

Scoliosis is an abnormal sideways curvature of the spine and rib cage, which may need surgical treatments. Most of the corrective maneuvers in scoliosis surgeries are based on surgeon’s experience; hence, there is great interest of understanding how the correction ratio can be influenced by the magnitude of forces and moments. Therefore, the objective of this study was to develop and validate a detailed finite element model of the thoracolumbar which can be used to simulate the scoliosis surgeries based on patient-specific clinical images. The validated models of five patients were carefully developed, and the surgery procedures were simulated and the corrective forces were estimated using inverse finite element analysis during the surgery. Furthermore, parametric studies including the influences of the corrective force magnitude and screw density were evaluated. The results showed that the maximum estimated correction force and moment were 173 (±55.43) N and 10.67 (±2.02) N m, respectively, which were aligned with measured clinical observations. The sensitivity analysis on the magnitude of applied force to the screws showed that correction ratio was slightly increased in level 1 (i.e. FB = 1.3 ×  F) but decreased in level 2 (i.e. FB = 1.6 ×  F). In addition, the parametric study on increasing the number of pedicle screws showed that there was no significant difference between lower and higher screw density. However, the stress distribution was significantly greater using higher screw density during correction maneuvers. In conclusion, this study shows a direct relationship between the applied force/moment and screw density and the correction ratio up to a border line which should be defined accurately. This detailed computational modeling can be used in clinic in hope of achieving the optimum outcome of scoliosis surgery using individual patient-specific characterization.

Potential bone fragility of mid-shaft atypical femoral fracture: Biomechanical analysis by a CT-based nonlinear finite element method

Injury ◽  
2019 ◽  
Vol 50 (11) ◽  
pp. 1876-1882 ◽  
Author(s):  
Atsuhiro Tano ◽  
Yoto Oh ◽  
Kazuyuki Fukushima ◽  
Yoshiro Kurosa ◽  
Yoshiaki Wakabayashi ◽  
...  
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Femoral Fracture ◽  
Bone Fragility ◽  
Nonlinear Finite Element ◽  
Biomechanical Analysis ◽  
Atypical Femoral Fracture ◽  
Nonlinear Finite Element Method ◽  
Element Method

Individual Trabecula Segmentation (ITS)-Based Plate-Rod Microstructural Finite Element Model Predicts Nonlinear Mechanical Properties of Human Trabecular Bone

2012 ◽  
Author(s):  
Bin Zhou ◽  
Ji Wang ◽  
Arnav Sanyal ◽  
Aaron J. Fields ◽  
Hong Wang ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Finite Element ◽  
High Resolution ◽  
Trabecular Bone ◽  
Element Model ◽  
Bone Fragility ◽  
Fe Model ◽  
Computationally Efficient ◽  
Human Trabecular Bone ◽  
Voxel Model

Osteoporosis is a major bone disease characterized by low bone mass and microarchitecture deterioration, which affects primarily trabecular sites and leads to increased bone fragility. Trabecular bone mechanical properties have direct relations with bone fragility. High-resolution image based-finite element (FE) models with the detailed 3D microstructure have been widely utilized to assess the mechanical properties of trabecular bone. Voxel-based FE model can be generated by converting individual voxels of high resolution bone images into 8-node brick elements. A number of studies have compared mechanical properties predicted by the voxel model with those by mechanical testing and have demonstrated that the voxel FE model can accurately predict the Young’s modulus and yield strength of human trabecular bone (1). However, the computational expense of the voxel-based technique, in general, limits its clinical applications, especially the nonlinear analysis for whole bone strength. Thus, it is not applicable to apply this technique to clinical use with the respect of current computer capability. There is apparent need for an alternative modeling approach that is more computationally efficient while preserving the accuracy of the predictions.

Simulation of tuning graphene plasmonic behaviors by ferroelectric domains for self-driven infrared photodetector applications

Nanoscale ◽  
2019 ◽  
Vol 11 (43) ◽  
pp. 20868-20875 ◽  
Author(s):  
Junxiong Guo ◽  
Yu Liu ◽  
Yuan Lin ◽  
Yu Tian ◽  
Jinxing Zhang ◽  
...  
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Interfacial Effect ◽  
Infrared Photodetector ◽  
The Finite Element Method ◽  
Ferroelectric Domains ◽  
Element Method

We propose a graphene plasmonic infrared photodetector tuned by ferroelectric domains and investigate the interfacial effect using the finite element method.

A Finite Element Model for the Design of Local Skin Flaps

1986 ◽  
Vol 19 (4) ◽  
pp. 807-824
Author(s):  
Wayne F. Larrabee ◽  
J.A. Galt
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Element Model ◽  
Skin Flaps ◽  
Local Skin
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