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). 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.

The authors have recently proposed the method of rolling indentation over soft tissue to rapidly identify soft tissue properties for localization and detection of tissue abnormalities, with the aim of compensating for the loss of haptics information experienced during robotic-assisted minimally invasive surgery (RMIS). This paper investigates the concept of rolling indentation using finite element modeling. To obtain ground truth data, rolling indentation experiments are conducted on a silicone phantom which contains three simulated tumours. The tissue phantom is modeled as hyperelastic material using ABAQUStrade. The identification of tumours includes two parts: firstly, when the spatial location of tumour is known, identify the tumour's mechanical properties (initial shear modulus); secondly if the mechanical properties of tumour are known, identify the tumour's spatial location. The results show that the proposed method can identify information of tumours accurately and robustly. The identified tumour mechanical properties and tumour locations are in good agreement with experimental measurements.