scholarly journals Identification of tumor nodule in soft tissue: An inverse finite‐element framework based on mechanical characterization

2020 ◽  
Vol 36 (8) ◽  
Author(s):  
Antonio Candito ◽  
Javier Palacio‐Torralba ◽  
Elizabeth Jiménez‐Aguilar ◽  
Daniel W. Good ◽  
Alan McNeill ◽  
...  
Keyword(s):  
Finite Element ◽  
Soft Tissue ◽  
Mechanical Characterization ◽  
Tumor Nodule

Viscoelastic characterization of soft tissue from dynamic finite element models

2008 ◽  
Vol 53 (22) ◽  
pp. 6569-6590 ◽  
Author(s):  
Hani Eskandari ◽  
Septimiu E Salcudean ◽  
Robert Rohling ◽  
Jacques Ohayon
Keyword(s):  
Finite Element ◽  
Soft Tissue ◽  
Finite Element Models ◽  
Dynamic Finite Element

scholarly journals Key considerations for finite element modelling of the residuum–prosthetic socket interface

2020 ◽  
pp. 030936462096778
Author(s):  
JW Steer ◽  
PR Worsley ◽  
M Browne ◽  
Alex Dickinson
Keyword(s):  
Finite Element ◽  
Soft Tissue ◽  
Finite Element Modelling ◽  
Soft Tissues ◽  
Shear Stresses ◽  
Material Models ◽  
Element Modelling ◽  
Prosthetic Socket ◽  
Highly Nonlinear ◽  
Socket Interface

Background: Finite element modelling has long been proposed to support prosthetic socket design. However, there is minimal detail in the literature to inform practice in developing and interpreting these complex, highly nonlinear models. Objectives: To identify best practice recommendations for finite element modelling of lower limb prosthetics, considering key modelling approaches and inputs. Study design: Computational modelling. Methods: This study developed a parametric finite element model using magnetic resonance imaging data from a person with transtibial amputation. Comparative analyses were performed considering socket loading methods, socket–residuum interface parameters and soft tissue material models from the literature, to quantify their effect on the residuum’s biomechanical response to a range of parameterised socket designs. Results: These variables had a marked impact on the finite element model’s predictions for limb–socket interface pressure and soft tissue shear distribution. Conclusions: All modelling decisions should be justified biomechanically and clinically. In order to represent the prosthetic loading scenario in silico, researchers should (1) consider the effects of donning and interface friction to capture the generated soft tissue shear stresses, (2) use representative stiffness hyperelastic material models for soft tissues when using strain to predict injury and (3) interrogate models comparatively, against a clinically-used control.

Quantifying Variability in Lumbar L4-L5 Soft Tissue Properties for Use in Finite-Element Analysis

2016 ◽  
Vol 1 (3) ◽  
Author(s):  
Dana J. Coombs ◽  
Paul J. Rullkoetter ◽  
Peter J. Laz
Keyword(s):  
Finite Element ◽  
Soft Tissue ◽  
Experimental Testing ◽  
Intersubject Variability ◽  
Probabilistic Representation ◽  
Posterior Portion ◽  
Annulus Fibrosis ◽  
Interspinous Ligament ◽  
Constitutive Material Model ◽  
The Impact

Soft tissue structures of the L4-L5 level of the human lumbar spine are represented in finite-element (FE) models, which are used to evaluate spine biomechanics and implant performance. These models typically use average properties; however, experimental testing reports variation up to 40% in ligament stiffness and even greater variability for annulus fibrosis (AF) properties. Probabilistic approaches enable consideration of the impact of intersubject variability on model outputs. However, there are challenges in directly applying the variability in measured load–displacement response of structures to a finite-element model. Accordingly, the objectives of this study were to perform a comprehensive review of the properties of the L4-L5 structures and to develop a probabilistic representation to characterize variability in the stiffness of spinal ligaments and parameters of a Holzapfel–Gasser–Ogden constitutive material model of the disk. The probabilistic representation was determined based on direct mechanical test data as found in the literature. Monte Carlo simulations were used to determine the uncertainty of the Holzapfel–Gasser–Ogden constitutive model. A single stiffness parameter was defined to characterize each ligament, with the anterior longitudinal ligament (ALL) being the stiffest, while the posterior longitudinal ligament and interspinous ligament (ISL) had the greatest variation. The posterior portion of the annulus fibrosis had the greatest stiffness and greatest variation up to 300% in circumferential loading. The resulting probabilistic representation can be utilized to include intersubject variability in biomechanics evaluations.

scholarly journals Biaxial estimation of biomechanical constitutive parameters of passive porcine sclera soft tissue

2021 ◽  
Author(s):  
Zwelihle Ndlovu ◽  
Dawood Desai ◽  
Thanyani Pandelani ◽  
Harry Ngwangwa ◽  
Fulufhelo Nemavhola
Keyword(s):  
Finite Element ◽  
Soft Tissue ◽  
Finite Element Model ◽  
Test Data ◽  
Element Model ◽  
Finite Element Models ◽  
Anisotropic Model ◽  
Material Models ◽  
Material Parameters ◽  
Constitutive Parameters

This study assesses the modelling capabilities of four constitutive hyperplastic material models to fit the experimental data of the porcine sclera soft tissue. It further estimates the material parameters and discusses their applicability to a finite element model by examining the statistical dispersion measured through the standard deviation. Fifteen sclera tissues were harvested from porcine’ slaughtered at an abattoir and were subjected to equi-biaxial testing. The results show that all the four material models yielded very good correlations at correlations above 96 %. The polynomial (anisotropic) model gave the best correlation of 98 %. However, the estimated material parameters varied widely from one test to another such that there would be needed to normalise the test data to avoid long optimisation processes after applying the average material parameters to finite element models. However, for application of the estimated material parameters to finite element models, there would be needed to consider normalising the test data to reduce the search region for the optimisation algorithms. Although the polynomial (anisotropic) model yielded the best correlation, it was found that the Choi-Vito had the least variation in the estimated material parameters thereby making it an easier option for application of its material parameters to a finite element model and also requiring minimum effort in the optimisation procedure. For the porcine sclera tissue, it was found that the anisotropy more influenced by the fiber-related properties than the background material matrix related properties.

Tissue Elasticity Estimation with Optical Coherence Elastography: Toward Mechanical Characterization of In Vivo Soft Tissue

2005 ◽  
Vol 33 (11) ◽  
pp. 1631-1639 ◽  
Author(s):  
Ahmad S. Khalil ◽  
Raymond C. Chan ◽  
Alexandra H. Chau ◽  
Brett E. Bouma ◽  
Mohammad R. Kaazempur Mofrad
Keyword(s):  
Soft Tissue ◽  
Mechanical Characterization ◽  
Optical Coherence ◽  
Tissue Elasticity

Mechanical Characterization of Soft Tissue Constituents for Cancer Detection

2019 ◽  
Vol 39 (6) ◽  
pp. 817-826
Author(s):  
Shima Zaeimdar ◽  
Parvind Kaur Grewal ◽  
Zahra Haeri ◽  
Farid Golnaraghi
Keyword(s):  
Soft Tissue ◽  
Cancer Detection ◽  
Mechanical Characterization
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