Soft Tissue Model Research Articles

How accurate is the soft tissue prediction of Dolphin Imaging for orthognathic surgery?

The purpose of this retrospective study is to evaluate the accuracy of soft tissue prediction models with Dolphin Imaging. Preoperative and 1-year postoperative Lateral cephalograms (LCG) of patients undergoing Le Fort I, bilateral sagittal split osteotomy (BSSO) or bimaxillary osteotomy (Bimax) between 2006 and 2009 were retrospectively collected. A hard tissue virtual surgery was performed on the preoperative LCG to match the hard tissue of the 1-year postoperative LCG. The soft tissue changes were then modelled by Dolphin Imaging (version 11.5b) and the differences in x- and y-coordinates of 11 hard tissue and 14 soft tissue landmarks between the predicted model and 1-year postoperative LCG were determined. Statistical analyses were performed using a one-tailed, one-sample t-test for both soft- and hard tissue differences, and a Bland-Altman plot for interobserver bias. A total of 108 patients were included, the mean age was 30 years and 23% were male. The virtual treatment was considered accurate; all hard tissue landmark differences were less than 1mm. The soft tissue model by Dolphin Imaging showed significant differences of more than 2mm for several landmarks, including the vertical positioning of Stomion Inferius (P=0.007), Lower lip (P=0.005) and Pogonion (P=0.03) in the Bimax group and horizontal positioning of Stomion Inferius (P<0.001) in the BSSO group. Dolphin Imaging gives reasonable predictions of postoperative outcome. There is, however, room for improvement, especially regarding the vertical prediction in the lower lip region.

A finite element implementation of a growth and remodeling model for soft biological tissues: Verification and application to abdominal aortic aneurysms

The general framework for growth and remodeling (G&R) of soft biological tissues shows a great potential for expanding our current understanding of biochemical and biomechanical processes, and to predict disease progression. Yet, its use is held up by the lack of a reliable and verified 3D finite element (FE) implementation capable of describing G&R processes of soft biological tissues. Thus, in this study we present the implementation of a 3D constrained mixture G&R model in a FE analysis program. In contrast to traditional finite strain FE formulations, we show that the volumetric–isochoric decomposition not only introduces numerical problems and instabilities, it also provides unphysical results. As a verification of the implementation we present adaptations of realistic aorta models to changes in the hemodynamics, i.e. changes in blood flow and pressure. The obtained results show a correspondence with the membrane theory and with clinical expectations. Application to a fusiform aneurysm model provided realistic growth rates, evolution of thickness and stress, whereas changes in the kinetic parameters show good agreement to animal models. Finally, we present simulated expansions of an asymmetric fusiform aneurysm. Non-axisymmetric elastin degradation increased the curvature of the aorta, which is characteristic for abdominal aortic aneurysms.

Gradient-enhanced continuum models of healing in damaged soft tissues.

Healing of soft biological tissue is the process of self-recovering or self-repairing the injured or damaged extracellular matrix (ECM). Healing is assumed to be stress-driven, with the objective of returning to a homeostatic stress metrics in the tissue after replacing the damaged ECM with new undamaged one. However, based on the existence of intrinsic length scales in soft tissues, it is thought that computational models of healing should be non-local. In the present study, we introduce for the first time two gradient-enhanced constitutive healing models for soft tissues including non-local variables. The first model combines a continuum damage model with a temporally homogenized growth model, where the growth direction is determined according to local principal stress directions. The second one is based on a gradient-enhanced healing model with continuously recoverable damage variable. Both models are implemented in the finite-element package Abaqus by means of a user subroutine UEL. Three two-dimensional situations simulating the healing process of soft tissues are modeled numerically with both models, and their application for simulation of balloon angioplasty is provided by illustrating the change of damage field and geometry in the media layer throughout the healing process.

Virtual Orthodontic Surgical Planning to Improve the Accuracy of the Surgery-First Approach: A Prospective Evaluation

We developed an innovative computer-assisted method to increase the accuracy of the surgery-first (SF) approach by linking the virtual orthodontic planning (VOP) with the virtual surgical planning(VSP). Fifteen consecutive patients were enrolled from 2013 to 2015. All 15 patients had initially undergone cone-beam computed tomography (CBCT; 15×15 field-of-view) and intraoral digital scanning of the dental arches. The DICOM (Digital Imaging and Communications in Medicine) data set and STL files were processed using the SimPlant O&O platform (Dentsply-Sirona, York, PA), which facilitates skeletal, dental, and soft tissue modeling and subsequent realization of the VOP/VSP. The VSP was reproduced using computer-aided design and computer-aided manufacturing surgical splints, and the VOP was realized via postoperative orthodontic treatment. At the end of treatment, all the patients underwent repeat CBCT and digital scanning of the dental arches, and the new data sets were compared with the original data sets to determine the deviations. To evaluate skeletal accuracy, we assessed all points within an arbitrary range of -2 to+2mm. To evaluate dental accuracy, the arbitrary range was -0.8 to+0.8mm. The average duration of orthodontic treatment was 17.9months. The accuracy of maxillary treatment averaged 0.0702±2.0724mm and that of mandibular treatment, 0.2811±1.9993mm. The average upper and lower dental arch accuracy was -0.0029±1.125 and -0.0147±1.263mm, respectively. The maxillary surgery accuracy was 75.3% and that of mandibular surgery 74.0%, both within the -2 to+2-mm range. The upper and lower arch accuracy was 58.86 and 51.53%, respectively, both within the -0.8 to+0.8-mm range. The use of the VOP/VSP improved the diagnostic and therapeutic SF preoperative planning. VOP contributed significantly in this context. The accuracy of skeletal repositioning was acceptable; however, the VSP should be rendered more reproducibly in the future to minimize the need for orthodontic compensation and to maximize the advantages of SF.

Novel applications of intelligent computing paradigms for the analysis of nonlinear reactive transport model of the fluid in soft tissues and microvessels

This article presents a methodology to solve a one-dimensional steady-state nonlinear reactive transport model (RTM) that is meant for fluid and solute transport model of soft tissues and microvessels. The methodology integrates the artificial neural network (ANN), genetic algorithms (GAs), and pattern search (PS) aided by active-set technique (AST) and interior-point technique (IPT). The RTM is represented with nonlinear second-order system based on the boundary value problem of ordinary differential equation. The ANN modeling is used for governing expression of RTM to form a fitness function in mean square sense, and optimization solvers based on the GA, PS, GA-AST, GA-IPT, PS-AST, PS-IPT are used for viable learning of weights. Proposed techniques are applied to different nonlinear RTMs based on variation in the characteristic reaction rate and half-saturation concentration. The proposed stochastic numerical solutions are compared with state-of-the-art solvers in order to check the accuracy and convergence based on sufficient large multiple runs of the algorithms.

A new model of soft tissue with constraints for interactive surgical simulation

Background and objectives: An accurate and real-time model of soft tissue is critical for surgical simulation for which a user interacts haptically and visually with simulated patients. This paper focuses on the real-time deformation model of brain tissue for the interactive surgical simulation, such as neurosurgical simulation.Methods: A new Finite Element Method (FEM) based model with constraints is proposed for the brain tissue in neurosurgical simulation. A new energy function of constraints characterizing the interaction between the virtual instrument and the soft tissue is incorporated into the optimization problem derived from the implicit integration scheme. Distance and permanent deformation constraints are introduced to describe the interaction in the convexity meningioma dissection and hemostasis. The proposed model is particularly suitable for GPU-based computing, making it possible to achieve real-time performance.Results and conclusions: Simulation results show that the simulated soft tissue exhibits the behaviors of adhesion and permanent deformation under the constraints. Experiments show that the proposed model is able to converge to the exact solution of the implicit Euler method after 96 iterations. The proposed model was implemented in the development of a neurosurgical simulator, in which surgical procedures such as dissection of convexity meningioma and hemostasis were simulated.

On fibre dispersion modelling of soft biological tissues: a review.

Collagen fibres within fibrous soft biological tissues such as artery walls, cartilage, myocardiums, corneas and heart valves are responsible for their anisotropic mechanical behaviour. It has recently been recognized that the dispersed orientation of these fibres has a significant effect on the mechanical response of the tissues. Modelling of the dispersed structure is important for the prediction of the stress and deformation characteristics in (patho)physiological tissues under various loading conditions. This paper provides a timely and critical review of the continuum modelling of fibre dispersion, specifically, the angular integration and the generalized structure tensor models. The models are used in representative numerical examples to fit sets of experimental data that have been obtained from mechanical tests and fibre structural information from second-harmonic imaging. In particular, patches of healthy and diseased aortic tissues are investigated, and it is shown that the predictions of the models fit very well with the data. It is straightforward to use the models described herein within a finite-element framework, which will enable more realistic (and clinically relevant) boundary-value problems to be solved. This also provides a basis for further developments of material models and points to the need for additional mechanical and microstructural data that can inform further advances in the material modelling.

In vivo and in vitro comparative assessment of the log-linearized Hunt–Crossley model for impact-contact modeling in physical human–robot interactions

In physical human–robot interactions, making the robot perceive in real time the mechanical contact impedance is critical for interactions safety, robot control and haptic rendering for robot teleoperation and can be achieved through online parametric model identification. Probing the viscoelastic properties of tissues is also a medical concern. For soft viscoelastic biological tissues, the Hunt–Crossley model is a contact force model computationally inexpensive while being accurate. As this model is non-linear, a log linear approximation has been proposed to achieve a fast and real-time identification using a recursive least squares approach. In this article, we want to regard the log-linearized expression of the Hunt–Crossley model no more as an approximation, but rather as a valuable empirical mechanical model of soft biological tissues. We show through experimental data fit and sophisticated statistical analysis that the log-linearized Hunt–Crossley model performs always closely to the Hunt–Crossley model and is even often slightly better. The experimental conditions investigated are related to impact and contact interactions, relevant in the context of Cobotics.

Waveform-Dependent Electrosurgical Effects on Soft Hydrated Tissues

Electrosurgical procedures are ubiquitously used in surgery. The commonly used power modes, including the coagulation and blend modes, utilize nonsinusoidal or modulated current waveforms. For the same power setting, the coagulation, blend, and pure cutting modes have different heating and thermal damage outcomes due to the frequency dependence of electrical conductivity of soft hydrated tissues. In this paper, we propose a multiphysics model of soft tissues to account for the effects of multifrequency electrosurgical power modes within the framework of a continuum thermomechanical model based on mixture theory. Electrical and frequency spectrum results from different power modes at low- and high-power settings are presented. Model predictions are compared with in vivo electrosurgical heating experiments on porcine liver tissue. The accuracy of the model in predicting experimentally observed temperature profiles is found to be overall greater when frequency-dependence is included. An Arrhenius type model indicates that more tissue damage is correlated with larger duty cycles in multifrequency modes.

A coupled approach for identification of nonlinear and compressible material models for soft tissue based on different experimental setups – Exemplified and detailed for lung parenchyma

In this paper, a coupled inverse analysis is proposed to identify nonlinear compressible hyperelastic material models described by two sets of experiments. While the overall approach is applicable for different materials, here it will be presented for viable lung parenchyma. Characterizing the material properties of lung parenchyma is essential to describe and predict the mechanical behavior of the respiratory system in health and disease. During breathing and mechanical ventilation, lung parenchyma is mainly subjected to volumetric deformations along with isochoric and asymmetric deformations that occur especially in diseased heterogeneous lungs. Notwithstanding, most studies examine lung tissue in predominantly isochoric tension tests. In this paper, we investigate the volumetric material behavior as well as the isochoric deformations in two sets of experiments: namely, volume–pressure-change experiments (performed with 287 samples of 26 rats) and uniaxial tension tests (performed with 30 samples of 5 rats). Based on these sets of experiments, we propose a coupled inverse analysis, which simultaneously incorporates both measurement sets to optimize the material parameters. Accordingly, we determine a suitable material model using the experimental results of both sets of experiments in one coupled identification process. The identified strain energy function with the corresponding material parameters Ψ=356.7Pa(I1−3)+331.7Pa(I3−1.075−1)+278.2Pa(I3−13I1−3)3+5.766Pa(I313−1)6 is validated to model both sets of experiments precisely. Hence, this constitutive model describes the complex volumetric and isochoric nonlinear material behavior of lung parenchyma. This derived material model can be used for nonlinear finite element simulations of lung parenchyma and will help to quantify the stresses and strains of lung tissue during spontaneous and artificial breathing; thus, allowing new insights into lung function and biology.

3D Ultrasound Imaging of Residual Limbs With Camera-Based Motion Compensation.

Ultrasound is a cost-effective, readily available, and non-ionizing modality for musculoskeletal imaging. Though some research groups have pursued methods that involve submerging the transducer and imaged body segment into a water bath, many limitations remain in regards to acquiring an unloaded volumetric image of an entire human limb in a fast, safe, and adequately accurate manner. A 3D dataset of a limb is useful in several rehabilitative applications including biomechanical modeling of soft tissue, prosthetic socket design, monitoring muscle condition and disease progression, bone health, and orthopedic surgery. This paper builds on previous work from our group and presents the design, prototyping, and preliminary testing of a novel multi-modal imaging system for rapidly acquiring volumetric ultrasound imagery of human limbs, with a particular focus on residual limbs for improved prosthesis design. Our system employs a mechanized water tank setup to scan a limb with a clinical ultrasound transducer and 3D optical imagery to track motion during a scan. The iterative closest point algorithm is utilized to compensate for motion and stitch the images into a final dataset. The results show preliminary 2D and 3D imaging of both a tissue-mimicking phantom and residual limbs. A volumetric error compares the ultrasound image data obtained to a previous MRI method. The results indicate potential for future clinical implementation. Concepts presented in this paper could reasonably transfer to other imaging applications such as acoustic tomography, where motion artifact may distort image reconstruction.

Radiological properties of gold loaded soft tissue its application in nanoparticle enhanced X-ray therapy

High Zmetal basednanoparticle such as gold, platinum and bismuth are used to enhance the therapeutic outcome in radiation oncology. In this current study, we assumed 7 and 18 mg/g of gold in ICRU-44 soft tissue and analytical models are used to calculate radiological properties. Our results suggest that optimum energy is 40 KeV for maximum dose enhancement factor; it was around 2.07, 3.76 for 7 and 18 mg/g Au respectively. Energy absorption build up factor of the gold loaded soft tissue is minimum compared to soft tissue alone. Kerma relative to air values was 1.05, 1.38 and 3.97 for soft tissue, 7mg and 18mg/g Au loaded soft tissue respectively. Mass energy absorption (µen/ϼ) and attenuation coefficients (µ/ϼ) are considerably increasing in the lower energy range up to 300 KeV compare to soft tissue alone and results are discussed.

Computational investigation of the impact of assumption of affine deformation on constitutive models of soft tissues

All constitutive models proposed during the last decades for large strain composites with hyperelastic matrix use an intrinsic assumption of affine deformation between the matrix and reinforcing fibres. While for typical technical composites the affinity of deformation between fibres and matrix till high loads is ensured by targeted creation of their chemical bonds, this need not to be the case with soft biological tissues. For instance, this assumption might be disputable for arterial tissues with their matrix consisting of very compliant gel-like proteoglycans. On the other hand, no constitutive model proposed till now has been capable to give a reasonable fit of all mechanical tests of some pathological tissues with low initial stiffness, such as aortic aneurysm wall. Thus, a question occurs whether this discrepancy could not be caused by the intrinsic assumption of affine deformation used in all models. To test the impact of this assumption on the simulated response in some mechanical tests, two finite element models of specimens of arterial tissues were created, both including matrix and fibres separately. The former model mimicked the affine deformation of matrix and fibres by merging all the nodes of both components, while the deformation of fibres was independent of the matrix in the latter model, with exception of both fibre ends. Differences in reaction forces of specimens were evaluated in various strain states and directions with respect to the orientation of fibres. The evaluated differences between models with affine and non-affine deformations were significant but smaller than typical inaccuracies of constitutive models when fitting aortic aneurysm tissues.

Skin and Soft Tissue Models for Acinetobacter baumannii Infection.

Multidrug-resistant A. baumannii are important Gram-negative pathogens causing persistent wound infections in both wounded and burned victims, which often result in secondary complications such as delayed wound healing, skin graft failure, and sometimes more serious outcomes such as sepsis and amputation. The choice of antibiotics to remediate these A. baumannii infections is becoming limited; and therefore, there has been a renewed interest in the research and development of new antibacterials targeting this pathogen. However, the evaluation of safety and efficacy is made more difficult by the lack of well-established in vivo models. This chapter describes established rodent and large animal models that have been used to investigate and develop treatments for A. baumannii skin and soft tissue infections.

Evaluation of dose distribution of 12C ion beam in radiotherapy by FLUKA as a Monte Carlo simulation Code

Introduction: Nowadays, the use of heavy ion beams in cancer therapy have been developed worldwide. Materials and Methods: It requires accurate understanding of the complex processes of ion interaction with matter, as it is the calculation the relative dose & range of these ions in matter. In the present study we used FLUKA as a numerical Monte Carlo simulations code for simulating the interaction of Carbon Ions beams of potential medical interest with water target as rough models for soft tissue. Results: The depth dose deposition of Carbon ions beam with Energies of 135MeV/u and 195MeV/u in water were simulated and the results were compared with GEANT4 simulation code. Conclusion: The results shows good agreement between FLUKA and GEANT4 and the Experimental data.

Poroelastic Modeling of Highly Hydrated Collagen Hydrogels: Experimental Results vs. Numerical Simulation With Custom and Commercial Finite Element Solvers.

This study presents a comparison between the performances of two Finite Element (FE) solvers for the modeling of the poroelastic behavior of highly hydrated collagen hydrogels. Characterization of collagen hydrogels has been a widespread challenge since this is one of the most used natural biomaterials for Tissue Engineering (TE) applications. V-Biomech® is a free custom FE solver oriented to soft tissue modeling, while Abaqus® is a general-purpose commercial FE package which is widely used for biomechanics computational modeling. Poroelastic simulations with both solvers were compared to two experimental protocols performed by Busby et al. (2013) and Chandran and Barocas (2004), also using different implementations of the frequently used Neo-Hookean hyperelastic model. The average differences between solvers outputs were under 5% throughout the different tests and hydrogel properties. Thus, differences were small enough to be considered negligible and within the variability found experimentally from one sample to another. This work demonstrates that constitutive modeling of soft tissues, such as collagen hydrogels can be achieved with either V-Biomech or Abaqus standard options (without user-subroutine), which is important for the biomechanics and biomaterials research community. V-Biomech has shown its potential for the validation of biomechanical characterization of soft tissues, while Abaqus' versatility is useful for the modeling and analysis of TE applications where other complex phenomena may also need to be captured.

Chemomechanical models for soft tissues based on the reconciliation of porous media and swelling polymer theories

AbstractThe interstitial fluid plays an important role for the deformability of soft biological tissues. While its high bulk modulus is often taken as an argument for tissue incompressibility, its ability to move through the interstitial space and across the boundary permits reversible changes of tissue volume through fluid exchange with the environment, which in turn is affected by the osmotic activity of the tissue constituents. Such coupled phenomena of fluid flow and deformation are characteristic both for hydrated biological tissues and swelling polymers, typically treated within the theory of porous media and chemoelasticity, respectively. In this contribution, the two theories are reconciled for biphasic materials with incompressible constituents and an inviscid liquid phase. Based on this analogy, and starting from the chemoelastic approach, a lean theoretical framework for the modelling of biphasic chemomechanical effects in soft biological tissues is presented. It provides access to fluid flux, variations in chemical potential and osmotic pressure in addition to stress and strain in the tissue. The framework is exemplified in application to arterial tissue, modifying and complementing an established monophasic, incompressible model, and the benefits of the alternative chemomechanical representation are illustrated in numerical examples.

Syntheses and X-ray crystal structures of a family of dinuclear silver(I)pyrazolates: Assessment of their antibacterial efficacy against P. aeruginosa with a soft tissue and skin infection model

Five new dinuclear silver(I) complexes, namely [Ag2(μ-4-Cl-pz)2(PPh3)4] (1), [Ag2(μ-4-Cl-pz)2(PPh3)3] (2), [Ag2(μ-4-NO2-pz)2(PPh3)4] (3), [Ag2(μ-4-NO2-pz)2(PPh3)3] (4) and [Ag2(μ-4-Cl-pz)2(PTA)4] (5) (where pz = pyrazolate and PTA = 1, 3, 5-triazaphosphaadamantane) have been synthesized and structurally characterized. The coordination geometry of both silver centers in complexes 1, 3 and 5 is distorted tetrahedral, while in case of complexes 2 and 4, one of the Ag centers resides in a trigonal planar environment. The two μ-pyrazolates act as bridges between two Ag atoms. Complex 5 is highly soluble in water and exhibits strong antimicrobial actions against a Gram-negative nosocomial pathogen Pseudomonas aeruginosa. The zone of bacterial clearance by complex 5 in SSTI (soft tissue and skin infection) model is found to be comparable to that by silver nitrate.

Investigating energy deposition within cell populations using Monte Carlo simulations

In this work, we develop multicellular models of healthy and cancerous human soft tissues, which are used to investigate energy deposition in subcellular targets, quantify the microdosimetric spread in a population of cells, and determine how these results depend on model details. Monte Carlo (MC) tissue models combining varying levels of detail on different length scales are developed: microscopically-detailed regions of interest (>1500 explicitly-modelled cells) are embedded in bulk tissue phantoms irradiated by photons (20 keV–1.25 MeV). Specific energy (z; energy imparted per unit mass) is scored in nuclei and cytoplasm compartments using the EGSnrc user-code egs_chamber; specific energy mean, , standard deviation, , and distribution, , are calculated for a variety of macroscopic doses, D. MC-calculated are compared with normal distributions having the same mean and standard deviation. For ∼mGy doses, there is considerable variation in energy deposition (microdosimetric spread) throughout a cell population: e.g. for 30 keV photons irradiating melanoma with 7.5 μm cell radius and 3 μm nuclear radius, for nuclear targets is , and the fraction of nuclei receiving no energy deposition, fz=0, is 0.31 for a dose of 10 mGy. If cobalt-60 photons are considered instead, then decreases to , and fz=0 decreases to 0.036. These results correspond to randomly arranged cells with cell/nucleus sizes randomly sampled from a normal distribution with a standard deviation of 1 μm. If cells are arranged in a hexagonal lattice and cell/nucleus sizes are uniform throughout the population, then decreases to and for 30 keV and cobalt-60, respectively; fz=0 decreases to 0.25 and 0.000 94 for 30 keV and cobalt-60, respectively. Thus, specific energy distributions are sensitive to cell/nucleus sizes and their distributions: variations in specific energy deposited over a cell population are underestimated if targets are assumed to be uniform in size compared with more realistic variation in target size. Bulk tissue dose differs from for nuclei (cytoplasms) by up to () across all cell/nucleus sizes, bulk tissues, and incident photon energies, considering a 50 mGy dose level. Overall, results demonstrate the importance of microdosimetric considerations at low doses, and indicate the sensitivity of energy deposition within subcellular targets to incident photon energy, dose level, elemental compositions, and microscopic tissue model.

Realizing Multilayered Soft Tissue Model Using Multithreading in Python

Interactive Virtual Reality based surgical simulators are gaining popularity where an inexperienced surgeon can practice the surgery irrespective of time and cost which is an effective way in medical training. In order to guarantee the real time performance, a multi-threading technique is applied to the model in different languages. This results in increased utilization of the processor resources and high update rate is achieved with a realistic rendering of the proposed graphics model for the virtual reality simulation. This paper presents a comparative analysis of the model’s performance using multithreading process. This is based on addition of matrices of the 3D model simulation with large dimensions in C and python programming languages implementations.