Towards real-time finite-strain anisotropic thermo-visco-elastodynamic analysis of soft tissues for thermal ablative therapy

A new model of electrosurgical tissue damage for neurosurgery simulation

BACKGROUND

Bipolar hemostasis electrocoagulation is a fundamental procedure in neurosurgery. A precise electrocoagulation model is essential to enable realistic visual feedback in virtual neurosurgical simulation. However, existing models lack an accurate description of the heat damage and irreversible tissue deformation caused by electrocoagulation, thus diminishing the visual realism. This work focuses on the electrocoagulation model for neurosurgery simulation.

METHOD

In this paper, a position-based dynamics (PBD) model with a bioheat transfer and damage prediction (BHTDP) method is developed for simulating the deformation of brain tissue caused by electrocoagulation. The presented BTHDP method uses the Arrhenius equation to predict thermal damage of brain tissue. A deformation model with energy and thermal damage constraints is developed to characterize soft tissue deformation during heat absorption before and after thermal injury. Visual effect of damaged brain tissue is re-rendered.

RESULT

To evaluate the accuracy of the proposed method, numerical simulations were conducted and compared with commercial finite element software. The maximum normalized error of the proposed model for predicting midpoint temperature is 10.3 % and the maximum error for predicting the thermal damage is 5.4 %. The contraction effects of heat-exposed anisotropic tissues are also simulated. The results indicate that the presented electrocoagulation model provides stable and realistic visual effects, making it applicable for simulating the electrocoagulation process in virtual neurosurgery.

Thermo-Visco-Elastometry of RF-Wave-Heated and Ablated Flesh Tissues Containing Au Nanoparticles

We report non-contact laser-based Brillouin light-scattering (BLS) spectroscopy measurements of the viscoelastic properties of hyperthermally radiofrequency (RF)-heated and ablated bovine liver and chicken flesh tissues with embedded gold nanoparticles (AuNPs). The spatial lateral profile of the local surface temperature in the flesh samples during their hyperthermia was measured through optical backscattering reflectometry (OBR) using Mg−silica-NP-doped sensing fibers distributed with an RF applicator and correlated with viscoelastic variations in heat-affected and ablated tissues. Substantial changes in the tissue stiffness after heating and ablation were directly related to their heat-induced structural modifications. The main proteins responsible for muscle elasticity were denatured and irreversibly aggregated during the RF ablation. At T > 100 °C, the proteins constituting the flesh further shrank and became disorganized, leading to substantial plastic deformation of biotissues. Their uniform destruction with larger thermal lesions and a more viscoelastic network was attained via AuNP-mediated RF hyperthermal ablation. The results demonstrated here pave the way for simultaneous real-time hybrid optical sensing of viscoelasticity and local temperature in biotissues during their denaturation and gelation during hyperthermia for future applications that involve mechanical- and thermal-property-controlled theranostics.

A new soft tissue deformation model based on Runge-Kutta: Application in lung

Flexible body deformation model is the most critical research in the field of telemedicine, which decides whether the deformation process of tissues and organs can be simulated in real time and realistically. Basically, the improvement of model accuracy often means the loss of real-time performance. In order to effectively balance between accuracy and real-time performance, this paper proposes a new model, which uses the step-variable fourth-order Runge-Kutta method for the first time to solve the relationship problem between the external force and displacement of the nodes in the finite element deformation of the lung. To improve the real-time performance of the model, a one-stage solution optimization algorithm is proposed to optimize the step size selection problem. Finally, an accelerated two-level node update algorithm is proposed to further improve the real-time performance. A lung surgery simulation platform with 3DMax2020 and OpenGL4.5 is built to verify the accuracy, efficiency, realism and applicability of the model. Experimental results show that the proposed lung model can achieve real-world visual reproduction during remote surgery, and exceeds other 13 reference models in real-time performance, with natural deformation effect, high simulation accuracy, which is suitable for modeling normal lung and four types of lungs suffering from diseases.

HyperMSM: A new MSM variant for efficient simulation of dynamic soft-tissue deformations

BACKGROUND AND OBJECTIVE

Fast, accurate, and stable simulation of soft tissue deformation is a challenging task. Mass-Spring Model (MSM) is one of the popular methods used for this purpose for its simple implementation and potential to provide fast dynamic simulations. However, accurately simulating a non-linear material within the mass-spring framework is still challenging. The objective of the present study is to develop and evaluate a new efficient hyperelastic Mass-Spring Model formulation to simulate the Neo-Hookean deformable material, called HyperMSM.

METHODS

Our novel HyperMSM formulation is applicable for both tetrahedral and hexahedral mesh configurations and is compatible with the original projective dynamics solver. In particular, the proposed MSM variant includes springs with variable rest-lengths and a volume conservation constraint. Two applications (transtibial residual limb and the skeletal muscle) were conducted.

RESULTS

Compared to finite element simulations, obtained results show RMSE ranges of [2.8%-5.2%] and [0.46%-5.4%] for stress-strain and volumetric responses respectively for strains ranging from -50% to +100%. The displacement error range in our transtibial residual limb simulation is around [0.01mm-0.7 mm]. The RMSE range of relative nodal displacements for the skeletal psoas muscle model is [0.4%-1.7%].

CONCLUSIONS

Our novel HyperMSM formulation allows hyperelastic behavior of soft tissues to be described accurately and efficiently within the mass-spring framework. As perspectives, our formulation will be enhanced with electric behavior toward a multi-physical soft tissue mass-spring modeling framework. Then, the coupling with an augmented reality environment will be performed.

Thermomechanical Modeling of Laser Ablation Therapy of Tumors: Sensitivity Analysis and Optimization of Influential Variables

In cancer treatment, laser ablation is a promising technique used to induce localized thermal damage. Different variables influence the temperature distribution in the tissue and the resulting therapy efficacy; thus, the optimal therapy settings are required for obtaining the desired clinical outcome. In this work, thermomechanical modeling of contactless laser ablation was implemented to analyze the sensitivity of independent variables on the optimal treatment conditions. The Finite Element Method was utilized to solve the governing equations, i.e., the bioheat, mechanical deformation, and the Navier-Stokes equations. Validation of the model was evaluated by comparing experimental and simulated temperatures, which indicated high accuracy for estimating temperature. In particular, the results showed that the model is capable of estimating temperature with a good correlation factor (R=0.98) and low Mean Absolute Error (3.9 C). A sensitivity analysis based on laser irradiation time, power, beam distribution, and the blood vessel depth on temperature distribution and fraction of necrotic tissue was performed. Based on the most significant variables i.e., laser irradiation time and power, an optimization process was performed. This resulted into an indication of the optimal therapy settings for achieving maximum procedure efficiency i.e., the required fraction of necrotic tissue within the target volume, constituted by tumor and safety margins around it.

Influence of temperature-dependent acoustic and thermal parameters and nonlinear harmonics on the prediction of thermal lesion under HIFU ablation

According to the traditional method of high intensity focused ultrasound (HIFU) treatment, the acoustic and thermal characteristic parameters of constant temperature (room temperature or body temperature) are used to predict thermal lesion. Based on the nonlinear spherical beam equation (SBE) and Pennes bio-heat transfer equation, and a new acoustic-thermal coupled model is proposed. The constant and temperature-dependent acoustic and thermal characteristic parameters are used to predict thermal lesion, and the predicted lesion area are compared with each other. Moreover, the relationship between harmonic amplitude ratio (P₂/P₁) and thermal lesion is studied. Combined with the known experimental data of acoustic and thermal characteristic parameters of biological tissue and data fitting method, the relationship between acoustic and thermal characteristic parameters and temperature is obtained; and the thermal lesion simulation calculation is carried out by using the acoustic and thermal characteristic parameters under constant temperature and temperature- dependent acoustic and thermal characteristic parameters, respectively. The simulation results show that under the same irradiation condition, the thermal lesion predicted by temperature-dependent acoustic and thermal characteristic parameters is larger than that predicted by traditional method, and the thermal lesion increases with the decrease of harmonic amplitude ratio.