Fast computation of soft tissue thermal response under deformation based on fast explicit dynamics finite element algorithm for surgical simulation

Abstract

Background and Objectives: During thermal heating surgical procedures such as electrosurgery, thermal ablative treatment and hyperthermia, soft tissue deformation due to surgical tool-tissue interaction and patient movement can affect the distribution of thermal energy induced. Soft tissue temperature must be obtained from the deformed tissue for precise delivery of thermal energy. However, the classical Pennes bio-heat transfer model can handle only the static non-moving state of tissue. In addition, in order to enable a surgeon to visualize the simulated results immediately, the solution procedure must be suitable for real-time thermal applications.Methods: This paper presents a formulation of bio-heat transfer under the effect of soft tissue deformation for fast or near real-time tissue temperature prediction, based on fast explicit dynamics finite element algorithm (FED-FEM) for transient heat transfer. The proposed thermal analysis under deformation is achieved by transformation of the unknown deformed tissue state to the known initial static state via a mapping function. The appropriateness and effectiveness of the proposed formulation are evaluated on a realistic virtual human liver model with blood vessels to demonstrate a clinically relevant scenario of thermal ablation of hepatic cancer.Results: For numerical accuracy, the proposed formulation can achieve a typical 10 −3 level of normalized relative error at nodes and between 10 −4 and 10 −5 level of total errors for the simulation, by comparing solutions against the commercial finite element analysis package. For computation time, the proposed formulation under tissue deformation with anisotropic temperature-dependent properties consumes 2.518 × 10 −4 for one element thermal loads computation, compared to 2.237 × 10 −4 for the formulation without deformation which is 0.89 times of the former. Comparisons with three other formulations for isotropic and temperature-independent properties are also presented.Conclusions: Compared to conventional methods focusing on numerical accuracy, convergence and stability, the proposed formulation focuses on computational performance for fast tissue thermal analysis. Compared to the classical Pennes model that handles only the static state of tissue, the proposed formulation can achieve fast thermal analysis on deformed states of tissue and can be applied in addition to tissue deformable models for nonlinear heating analysis at even large deformation of soft tissue, leading to great translational potential in dynamic tissue temperature analysis and thermal dosimetry computation for computer-integrated medical education and personalized treatment.

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A Real-time Cutting Model Based on Finite Element and Order Reduction

“…In order to verify the accuracy of the model proposed in this paper, the standard modeling software ANSYS was used to establish a reference model [16], we compared the standard mean square deviations of the nodal displacements of the three models relative to the reference model under the same force conditions. These three models are the model proposed in this paper, the co-rotating finite element model [17], and the finite element model based on neural network [18].…”

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

“…We employ a transformation of system configurations to achieve bioheat computation on deformed soft tissues [53]. The mapping function for deformations 𝛺 0 → 𝛺 𝑡 can be defined by…”

“…To achieve fast and accurate numerical solutions, we develop solution procedures based on the (i) fast explicit dynamics finite element algorithm [55] for transient bioheat computation [56] under soft tissue deformations [53] and the (ii) total Lagrangian explicit dynamics finite element algorithm [57] for biomechanics computation of large-strain soft tissue deformations. The proposed formulation has not been evidenced in previous works.…”