Analysis of several biomechanical models for the simulation of lamb liver behaviour using similarity coefficients from medical image

An introduction to the Ogden model in biomechanics: benefits, implementation tools and limitations

Constitutive models are important to biomechanics for two key reasons. First, constitutive modelling is an essential component of characterizing tissues' mechanical properties for informing theoretical and computational models of biomechanical systems. Second, constitutive models can be used as a theoretical framework for extracting and comparing key quantities of interest from material characterization experiments. Over the past five decades, the Ogden model has emerged as a popular constitutive model in soft tissue biomechanics with relevance to both informing theoretical and computational models and to comparing material characterization experiments. The goal of this short review is threefold. First, we will discuss the broad relevance of the Ogden model to soft tissue biomechanics and the general characteristics of soft tissues that are suitable for approximating with the Ogden model. Second, we will highlight exemplary uses of the Ogden model in brain tissue, blood clot and other tissues. Finally, we offer a tutorial on fitting the one-term Ogden model to pure shear experimental data via both an analytical approximation of homogeneous deformation and a finite-element model of the tissue domain. Overall, we anticipate that this short review will serve as a practical introduction to the use of the Ogden model in biomechanics. This article is part of the theme issue 'The Ogden model of rubber mechanics: Fifty years of impact on nonlinear elasticity'.

An introduction to the Ogden model in biomechanics: benefits, implementation tools and limitations

Constitutive models are important to biomechanics for two key reasons. First, constitutive modelling is an essential component of characterizing tissues' mechanical properties for informing theoretical and computational models of biomechanical systems. Second, constitutive models can be used as a theoretical framework for extracting and comparing key quantities of interest from material characterization experiments. Over the past five decades, the Ogden model has emerged as a popular constitutive model in soft tissue biomechanics with relevance to both informing theoretical and computational models and to comparing material characterization experiments. The goal of this short review is threefold. First, we will discuss the broad relevance of the Ogden model to soft tissue biomechanics and the general characteristics of soft tissues that are suitable for approximating with the Ogden model. Second, we will highlight exemplary uses of the Ogden model in brain tissue, blood clot and other tissues. Finally, we offer a tutorial on fitting the one-term Ogden model to pure shear experimental data via both an analytical approximation of homogeneous deformation and a finite-element model of the tissue domain. Overall, we anticipate that this short review will serve as a practical introduction to the use of the Ogden model in biomechanics. This article is part of the theme issue 'The Ogden model of rubber mechanics: Fifty years of impact on nonlinear elasticity'.

Analysis of the passive biomechanical behavior of a sheep-specific aortic artery in pulsatile flow conditions

In this work, a novel numerical-experimental procedure is proposed, through the use of the Cardiac Simulation Test (CST), device that allows the exposure of the arterial tissue to in-vitro conditions, mimicking cardiac cycles generated by the heart. The main goal is to describe mechanical response of the arterial wall under physiological conditions, when it is subjected to a variable pressure wave over time, which causes a stress state affecting the biomechanical behavior of the artery wall. In order to get information related to stress and strain states, numerical simulation via finite element method, is performed under a condition of systolic and diastolic pressure. The description of this methodological procedure is performed with a sample corresponding to a sheep aorta without cardiovascular pathologies. There are two major findings: the evaluation of the mechanical properties of the sheep aorta through the above-mentioned tests and, the numerical simulation of the mechanical response under the conditions present in the CST. The results state that differences between numerical and experimental circumferential stretch in diastole and systole to distinct zones studied do not exceed 1%. However, greater discrepancies can be seen in the distensibility and incremental modulus, two main indicators, which are in the order of 30%. In addition, numerical results determine an increase of the principal maximum stress and strain between the case of systolic and diastolic pressure, corresponding to 31.1% and 14.9% for the stress and strain measurement respectively; where maximum values of these variables are located in the zone of the ascending aorta and the aortic arch.

A finite element-based machine learning approach for modeling the mechanical behavior of the breast tissues under compression in real-time

This work presents a data-driven method to simulate, in real-time, the biomechanical behavior of the breast tissues in some image-guided interventions such as biopsies or radiotherapy dose delivery as well as to speed up multimodal registration algorithms. Ten real breasts were used for this work. Their deformation due to the displacement of two compression plates was simulated off-line using the finite element (FE) method. Three machine learning models were trained with the data from those simulations. Then, they were used to predict in real-time the deformation of the breast tissues during the compression. The models were a decision tree and two tree-based ensemble methods (extremely randomized trees and random forest). Two different experimental setups were designed to validate and study the performance of these models under different conditions. The mean 3D Euclidean distance between nodes predicted by the models and those extracted from the FE simulations was calculated to assess the performance of the models in the validation set. The experiments proved that extremely randomized trees performed better than the other two models. The mean error committed by the three models in the prediction of the nodal displacements was under 2 mm, a threshold usually set for clinical applications. The time needed for breast compression prediction is sufficiently short to allow its use in real-time (<0.2 s).

Design and validation of an augmented reality system for laparoscopic surgery in a real environment

Purpose. This work presents the protocol carried out in the development and validation of an augmented reality system which was installed in an operating theatre to help surgeons with trocar placement during laparoscopic surgery. The purpose of this validation is to demonstrate the improvements that this system can provide to the field of medicine, particularly surgery. Method. Two experiments that were noninvasive for both the patient and the surgeon were designed. In one of these experiments the augmented reality system was used, the other one was the control experiment, and the system was not used. The type of operation selected for all cases was a cholecystectomy due to the low degree of complexity and complications before, during, and after the surgery. The technique used in the placement of trocars was the French technique, but the results can be extrapolated to any other technique and operation. Results and Conclusion. Four clinicians and ninety-six measurements obtained of twenty-four patients (randomly assigned in each experiment) were involved in these experiments. The final results show an improvement in accuracy and variability of 33% and 63%, respectively, in comparison to traditional methods, demonstrating that the use of an augmented reality system offers advantages for trocar placement in laparoscopic surgery.