This paper investigates the use of inverse finite-element modeling (IFEM)-based methods for tissue parameter identification using a rolling indentation probe for surgical palpation. An IFEM-based algorithm is proposed for tissue parameter identification through uniaxial indentation. IFEM-based algorithms are also created for locating and identifying the properties of an embedded tumor through rolling indentation of the soft tissue. Two types of parameter identification for the tissue tumor are investigated (1) identifying the stiffness (μ) of a tumor at a known depth and (2) estimating the depth of the tumor (D) with known mechanical properties. The efficiency of proposed methods has been evaluated through silicone and porcine kidney experiments for both uniaxial indentation and rolling indentation. The results show that both of the proposed IFEM methods for uniaxial indentation and rolling indentation have good robustness and can rapidly converge to the correct results. The tissue properties estimated using the developed method are generic and in good agreement with results obtained from standard material tests. The estimation error of μ through uniaxial indentation is below 3 % for both silicone and kidney; the estimation error of μ for the tumor through rolling indentation is 7-9 %. The estimation error of D through rolling indentation is 1-2 mm.
We describe a novel approach for demonstrate of a wheel-rolling tissue deformation as well as the abnormalities tissue depth evaluation using a rolling finite element model (RFEM). Since a wheeled probe which is capable of performing rolling tissue indentation has been proven to be a promising device to rapid conduct soft tissue property identification for localization and documentation of the abnormalities within the tissue, with the aim of compensating the loss of haptic and tactile feedback experienced during robotic-assisted minimally invasive surgery (MIS) [3, 4, 5]. To implement such a device requires a good understanding of the dynamics of the wheel-tissue rolling interaction and relationship between the tissue internal structure and the corresponding tissue reaction force. In this paper we propose the RFEM of the dynamic interaction between a wheeled probe and a soft tissue sample using ABAQUS finite element analysis software package. The aim of this work is to more precisely locate abnormalities depth within soft tissues using RFEM and aid surgeons better in the decision of resection during MIS through the understanding of dynamics of wheel-tissue rolling interaction. The soft tissue was modelled as a nonlinear hyperelastic material with geometrical nonlinearity and the modelling parameters were calibrated using experimental data from standard tests. The purposed RFEM consists of simulations of wheel-tissue rolling indentations on a silicone phantom with varied tissue internal structure and also running on a biological tissue such as a porcine kidney. The results show that the proposed method can predicted the wheel-tissue interaction force of the rolling indentation with a good agreement results and the documentary from empirical equation of RFEM can identify the simulated tumors depth accurately.
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