A Finite Element Method Simulation of the Interaction of Intestinal Tissue and Tissue Attachment Mechanism1

Abstract

In recent years, the demand of in vivo robotic capsule in bio-imaging has experienced a huge amount of growth [1]. After 20 years of development, researchers are looking to expand the application potential of robotic capsule to a higher stage. Multifunctional capsules which could locomote along the gastrointestinal tract, adhere to the tissue, record physical data, and deliver drugs have been designed and studied by many research groups. Practically, all the functions above were realized through manipulating nearby tissue in certain way. A major issue concerning those tissue manipulation procedures is trauma. Our previous work presented a type of tissue attachment mechanism (TAM) inspired by tapeworm scolex which could attach a biosensor to the target intestinal tissue and maintain its position up to 6 days [2]. The TAM system includes a sucker with vacuum chamber and several needles integrated onto the sucker. When the TAM arrives at the ideal position, a slight vacuum is generated at the sucker surface. The suction function of the vacuum aspirates a small amount of tissue into the sucker to be grasped by the needles, and then, it facilitates long-term attachment by fixing the tissue on those needles. In this method, the efficiency and rate of success depend on how deep the tissue could be aspirated into the sucker; the more tissue in the sucker, the higher chance needle could attach to the tissue firmly. But higher vacuum pressure also may cause more serious damage to the tissue. To better understand this procedure and find the equilibrium of efficiency and safety, a numerical model is needed to study and predict the tissue behavior under different loading.Typical soft tissue like the small intestine is nonlinear, anisotropic, viscoelastic material. To model the behavior of this kind of material through any analytical model is almost impossible and inaccurate. On the other hand, FEM could provide a better approximation of biotissue behavior due to its excellent nonlinear ordinary differential equation (ODE)/partial differential equation (PDE) solving ability that has been used to simulate tissue behavior for a long time. The goal of this work is to address this problem by simulating the deformation process of tissue under different vacuum pressures using FEM commercial software. The deformation trend and stress and strain distribution would help us optimize the TAM structure and minimize the possible damage to the tissue. As a methodology development work, we believe the method shown in this work may also be applied in other tissue manipulation procedure analysis.The first step to simulate the tissue behavior is always to define the materials properties properly. Hyperelasticity (stress increase nonlinearly with strain) of intestine tissue was shown in both uniaxial and biaxial tensile test, and clear viscoelasticity was exhibit in relaxation test. For the hyperelasticity, the uniaxial and biaxial tensile test data were collected from our previous work [3]; Marlow, second-order polynomial and Ogden model were applied in abaqus to fit those data. For the viscoelasticity, a five-element viscoelasticity model was applied to descript the viscoelastic properties, and the tissue stress–strain relationship was interpreted into a time-dependent pony serious in abaqus [4]. The tissue was considered as isotropic materials in this work.Simulations with 2D models were more computationally efficient. In this work, a 2D tissue deformation model was set up as shown in Fig. 1. A flat 2D rectangular part was set as intestinal tissue and a hemisphere structure under it replicates the sucker.The TAM was treated as rigid body in the simulation because of its relatively high hardness and small deformation during the test. Needles were not considered in both 2D and 3D simulations due to the difficulties of setting contact conditions and the crack properties of tissue in simulation. The needles will be added in future work.Before the simulation st