In minimally invasive surgery, flexible needle insertion is a popular application which has been extensively researched. However, needle steering is challenging for a bevel tip cannula flexible needle due to the nonholonomic constraints and the rebounds of the needle shaft when the needle tip is reoriented. We proposed a novel kinematic model for the bevel tip cannula flexible needle based on bicycle and unicycle models, taking consideration of the deflection of the bevel tip and the rebounds of the needle shaft. Aiming at different types of paths, forward kinematics of the model was analyzed and calculated. Each parameter of the kinematic models was identified based on the experimental data using the least square method. Furthermore, the changing rules of parameters were explored under different angles of the bevel tip. The experimental results show that the errors of the proposed kinematic models are within 2 mm, which is greatly reduced compared to the traditional bicycle or unicycle model, and fulfill a general clinical surgery.

In robot-assisted needle-based medical procedures, insertion motion planning is a crucial aspect. 3D dynamic motion planning for a cannula flexible needle is challenging with regard to the nonholonomic motion of the needle tip, the presence of anatomic obstacles or sensitive organs in the needle path, as well as uncertainties due to the dynamic environment caused by the movements and deformations of the organs. The kinematics of the cannula flexible needle is calculated in this paper. Based on a rapid and robust static motion planning algorithm, referred to as greedy heuristic and reachability-guided rapidly-exploring random trees, a 3D dynamic motion planner is developed by using replanning. Aiming at the large detour problem, the convergence problem and the accuracy problem that replanning encounters, three novel strategies are proposed and integrated into the conventional replanning algorithm. Comparisons are made between algorithms with and without the strategies to verify their validity. Simulations showed that the proposed algorithm can overcome the above-noted problems to realize real-time replanning in a 3D dynamic environment, which is appropriate for intraoperative planning.

Visualization of the surgical needle is critical for an image guided insertion. However, it is difficult to obtain a 3D tip pose of a steerable flexible needle under 2D US images. In this letter, an image processing method is used to extract the needle shaft radial cross-sectional centroid coordinates (NSRCCCs). Based on the NSRCCCs, two methods are proposed to estimate the needle tip pose in real-time, which are based on Rodrigues’ rotation formula, and Fourier expansion with three-terms and linear interpolation algorithm (FEWT&LIA), respectively. In order to validate the methods proposed in this letter, the insertion experiments with different depths are conducted in phantom tissues, and the results show that the mean errors are 0.68 mm and 0.65 mm with using the Rodrigues’ rotation formula based method and the FEWT&LIA based method, respectively, showing clinically acceptable accuracy.

Percutaneous insertion is one of the most common minimally invasive procedures. Compared with traditional straight rigid needles, bevel-tipped flexible needle can generate curved trajectories to avoid obstacles and sensitive organs. However, the nonlinear large deflection problem challenges the bending prediction of the needle, which dramatically influences the surgical success rate. This paper analyzed the mechanism of needle-tissue interaction, and established a mechanics-based model of the needle bending during an insertion. And then, a discretization of the bending model was adopted to accurately predict the large bending of the needle in soft tissue. Insertion experiments were conducted to validate the bending prediction model. The results showed that the large needle bending was predicted with the mean/RMSE/maximumu error of 0.42 mm / 0.26 mm / 1.08 mm, which was clinically acceptable. This proved the rationality and accuracy of the proposed model.

Objective. Due to the limited operating space in the magnetic resonance (MR) environment, there is coupled motion in the insertion mechanism, which not only reduces the flexibility of the robot but also challenges the insertion path planning. Meanwhile, the path planning is also restricted by the bending rule of the flexible needle, thus the bending model of the needle is also essentially built. Approach. This paper proposes a path planner for the flexible needle based on both the coupled motion kinematics of the insertion robot and the bending model of the flexible needle. A kinematic analysis for the coupled motion of insertion robot is performed. And the bending model of flexible needle is established based on the needle-tissue interactions. The position and posture of the needle insertion at the entry point are obtained by the calculation of the target position and the analysis of the bending model. And the rotation or translation coordinates of each robot joint are calculated by the inverse kinematics of the insertion robot. Then the path planning based on the coupled kinematics and the bending model is realized. Main results. The insertion experiments were performed for each target of G ₁ and G ₂. The root mean square errors were 0.83 mm and 0.74 mm, and the maximum errors were 1.1 mm and 0.9 mm for G ₁ and G ₂, respectively. The experimental results show that the effectiveness and accuracy of the path planning can meet the requirements for a general minimally invasive surgery (MIS), so the proposed path planning algorithm is feasible. Significance. This study provides a new solution for the path planning of insertion robots for the MIS. This method can meet the insertion mechanism working within the limited operating space in the MR environment and has a high application value in future clinical medicine.

Flexible needle has a sufficient pliability, which could steer clear of obstacles and correct the deviated path to achieve deep target insertions. It has a tendency of replacing rigid needles. An insertion robot for the flexible needle is one of the important parts of the robot-assisted surgery system. This paper proposed a novel insertion robot for an FBG (Fiber Bragg Grating) embedded cannula flexible needle and conducted puncture control experiments. The insertion robot consisted of a configuration adjustment mechanism and an insertion mechanism, which was compact and with a high insertion accuracy. The forward and inverse kinematics of the robot were calculated and the workspace was simulated using MATLAB/SIMULINK. The simulation results show that the robot has a workspace in size of about 200mm by 110mm by 140mm, which completely covers the required position and posture for the prostate insertion. Then a path tracking controller was designed to adjust the insertion path in real-time, realizing the tracking control of the planned path for the cannula flexible needle. Finally, the experiments were carried out to verify the rationality of the robot structure and the effectiveness of the puncture control in an environment with obstacles. The experimental results showed that the insertion average error was 1.3mm, the maximum error was 1.7mm, and the root mean square error was 0.3mm, fulfilling the insertion accuracy requirements of the clinical prostate surgery. This proved the rationality of the structural design and the high precision of the control.