A Fast Krylov Subspace-based Method for Multi-physics Modeling of Electrosurgical Cutting of Soft Tissue
نویسنده
چکیده
In electrosurgery radiofrequency (RF, 300 KHz—3 MHz) alternating current (AC) is used to raise intracellular temperature in order to achieve cutting or coagulation of soft tissue [1]. The type of tissue effect (e.g. cutting or coagulation) is dependent on many factors, such as activation time and electrosurgical waveform properties. Thus, modeling electrosurgical procedure in soft tissue is concerned with the behavior of deformable tissue within electromagnetic field under combined electric, thermal, or mechanical loadings. Furthermore, the Joule heating generated from the electromagnetic wave induces pressure changes on the cellular level due to evaporation of water, which leads to rupture of cellular wall resulting in very precise cutting and fragmentation of the tissue. Despite wide popularity of electrosurgery, the effects of cellular level mechanisms on the electro-thermo-mechanical damage of soft tissue have not been adequately understood. We have developed a multi-physics model to investigate the effects of cellular level mechanisms on the electro-thermo-mechanical response of RF activated soft tissue. Cellular level micromechanical model has been incorporated into the tissue level continuum model to accurately determine the thermodynamic states such as temperature and pressure. The micromechanical model based equation of state (EOS) provides the additional pressure arising from evaporation of intracellular and cellular water by absorbing heat due to Joule heating. A linear elastic material model is used to describe the deviatoric response of the tissue. A level set approach [2] is used to capture the interfacial evolution of tissue fracture (i.e. cutting) based on Griffith’s fracture criterion [3]. A multi-physics based finite element model is developed to simulate the electrosurgical cutting of soft tissue. The coupled governing equations for current, temperature, deformation, and level set parameter fields are solved iteratively using Krylov subspace based iterative solver (e.g. GMRES). Not having to explicitly compute and store the finite element stiffness matrix of the coupled system reduces storage requirements, and computational complexities and costs compared to efforts based on explicit formation of stiffness matrix. The computational efficiency of the Krylov subspace based iterative solver is enhanced using a matrix-free block-preconditioner [4]. The model is shown to capture the characteristics of RF activated soft tissue deformation, temperature and fracture interface evolution.
منابع مشابه
Semi-Blind Channel Estimation based on subspace modeling for Multi-user Massive MIMO system
Channel estimation is an essential task to fully exploit the advantages of the massive MIMO systems. In this paper, we propose a semi-blind downlink channel estimation method for massive MIMO system. We suggest a new modeling for the channel matrix subspace. Based on the low-rankness property, we have prposed an algorithm to estimate the channel matrix subspace. In the next step, using o...
متن کاملRobust and efficient preconditioned Krylov spectral solvers for computing the ground states of fast rotating and strongly interacting Bose-Einstein condensates
We consider the Backward Euler SPectral (BESP) scheme proposed in [10] for computing the stationary states of Bose-Einstein Condensates (BECs) through the Gross-Pitaevskii equation. We show that the fixed point approach introduced in [10] fails to converge for fast rotating BECs. A simple alternative approach based on Krylov subspace solvers with a Laplace or Thomas-Fermi preconditioner is give...
متن کاملEvaluation of Soft Tissue Sarcoma Tumors Electrical Conductivity Anisotropy Using Diffusion Tensor Imaging for Numerical Modeling on Electroporation
Introduction: There is many ways to assessing the electrical conductivity anisotropyof a tumor. Applying the values of tissue electrical conductivity anisotropyis crucial in numerical modeling of the electric and thermal field distribution in electroporationtreatments. This study aims to calculate the tissues electrical conductivityanisotropy in patients with sarcoma tumors using diffusion tens...
متن کاملPreconditioned Generalized Minimal Residual Method for Solving Fractional Advection-Diffusion Equation
Introduction Fractional differential equations (FDEs) have attracted much attention and have been widely used in the fields of finance, physics, image processing, and biology, etc. It is not always possible to find an analytical solution for such equations. The approximate solution or numerical scheme may be a good approach, particularly, the schemes in numerical linear algebra for solving ...
متن کاملAn Approach in Radiation Therapy Treatment Planning: A Fast, GPU-Based Monte Carlo Method
Introduction: An accurate and fast radiation dose calculation is essential for successful radiation radiotherapy. The aim of this study was to implement a new graphic processing unit (GPU) based radiation therapy treatment planning for accurate and fast dose calculation in radiotherapy centers. Materials and Methods: A program was written for parallel runnin...
متن کامل