Flexible Needle Insertion Research Articles

A method for predicting needle insertion deflection in soft tissue based on cutting force identification

The deflection modeling during the insertion of bevel-tipped flexible needles into soft tissues is crucial for robot-assisted flexible needle insertion into specific target locations within the human body during percutaneous biopsy surgery. This paper proposes a mechanical model based on cutting force identification to predict the deflection of flexible needles in soft tissues. Unlike other models, this method does not require measuring Young’s modulus ( E ) and Poisson’s ratio ( ν ) of tissues, which require complex hardware to obtain. In the model, the needle puncture process is discretized into a series of uniform-depth puncture steps. The needle is simplified as a cantilever beam supported by a series of virtual springs, and the influence of tissue stiffness on needle deformation is represented by the spring stiffness coefficient of the virtual spring. By theoretical modeling and experimental parameter identification of cutting force, the spring stiffness coefficients are obtained, thereby modeling the deflection of the needle. To verify the accuracy of the proposed model, the predicted model results were compared with the deflection of the puncture experiment in polyvinyl alcohol (PVA) gel samples, and the average maximum error range predicted by the model was between 0.606 ± 0.167 mm and 1.005 ± 0.174 mm, which showed that the model can successfully predict the deflection of the needle. This work will contribute to the design of automatic control strategies for needles.

Variable Curvature Path Planning for Robot-Assisted Flexible Needle Insertion Based on Improved Bi-RRT Algorithm

Variable Curvature Path Planning for Robot-Assisted Flexible Needle Insertion Based on Improved Bi-RRT Algorithm

Optical Fiber-Based Needle Shape Sensing in Real Tissue: Single Core vs. Multicore Approaches.

Flexible needle insertion procedures are common in minimally-invasive surgeries for diagnosing and treating prostate cancer. Bevel-tip needles provide physicians the capability to steer the needle during long insertions to avoid vital anatomical structures in the patient and reduce post-operative patient discomfort. To provide needle placement feedback to the physician, sensors are embedded into needles for determining the real-time 3D shape of the needle during operation without needing to visualize the needle intra-operatively. Through expansive research in fiber optics, a plethora of bio-compatible, MRI-compatible, optical shape-sensors have been developed to provide real-time shape feedback, such as single-core and multicore fiber Bragg gratings. In this paper, we directly compare single-core fiber-based and multicore fiber-based needle shape-sensing through similarly constructed, four-active area sensorized bevel-tip needles inserted into phantom and ex-vivo tissue on the same experimental platform. In this work, we found that for shape-sensing in phantom tissue, the two needles performed identically with a p-value of 0.164 > 0.05, but in ex-vivo real tissue, the single-core fiber sensorized needle significantly outperformed the multicore fiber configuration with a p-value of 0.0005 < 0.05. This paper also presents the experimental platform and method for directly comparing these optical shape sensors for the needle shape-sensing task, as well as provides direction, insight and required considerations for future work in constructively optimizing sensorized needles.

Diffuse domain approach for flexible needle insertion and relaxation.

Needle insertion simulations play an important role in medical training and surgical planning. Most simulations require boundary conforming meshes, while the diffuse domain approach, currently limited to stiff needles, eliminates the need for meshing geometries. In this article the diffuse domain approach for needle insertion simulations is first extended to the use of flexible needles with bevel needle tips, which are represented by an Euler-Bernoulli beam. The model parameters are tuned and the model is evaluated on a real-world phantom experiment. Second, a new method for the relaxation of the needle-tissue system after the user releases the needle is introduced. The equilibrium state of the system is determined by minimizing the potential energy. The convergence rate of the coupled Laplace equations for solving the Euler-Bernoulli beam is 1.92 0.14 for decreasing cell size. The diffuse penalty method for the application of Dirichlet boundary conditions results in a convergence rate of 0.73 0.21 for decreasing phase field width. The simulated needle deviates on average by 0.29 mm compared to the phantom experiment. The error of the tissue deformation is below 1 mm for 97.5% of the attached markers. Two additional experiments demonstrate the feasibility of the relaxation process. The simulation method presented here is a valuable tool for patient-specific medical simulations using flexible needles without the need for boundary conforming meshing. To the best of the authors' knowledge this is the first work to introduce a relaxation model, which is a major step for simulating accurate needle-tissue positioning during realistic medical interventions.

A new path planning method for bevel-tip flexible needle insertion in 3D space with multiple targets and obstacles

A new path planning method for bevel-tip flexible needle insertion in 3D space with multiple targets and obstacles

Curve Fitting-Based Dynamic Path Planning and Tracking Control for Flexible Needle Insertion

Needle insertion is widely used in modern clinical practice, and flexible needles enable surgeons to adjust the needle insertion path to avoid obstacles and compensate for target drift. To increase the accuracy and safety of the needle insertion procedure, a path planning and tracking control method for flexible needle steering in dynamic environment is proposed in this paper. The path planning method is based on the artificial potential field algorithm and curve fitting algorithm, after several feasible paths with variant curvatures is obtained, they are furtherly optimized based on path length, obstacle clearance and control effort to select the best one. Simulations show that the proposed path planning method performs better than the current constant curvature method and the rapidly-exploring random tree (RRT) based method. By finely tuning the initial planned path, an intraoperative path replanning method is proposed, which are used to compensate for the drift of target and obstacles. Then to ensure the needle is inserted along the planned path, a tracking control method is adopted based on fuzzy logic algorithm. With the proposed intraoperative path planning and tracking control method, the robustness and accuracy of needle insertion in congested environment can be improved, and experiments also show that our proposed method achieves satisfactory insertion safety and targeting accuracy in dynamic environment. The obtained accuracy of 1.57 mm is sufficient for most clinical needle insertion applications.

3-D Path Planning Using Improved RRT* Algorithm for Robot-Assisted Flexible Needle Insertion in Multilayer Tissues

In the field of minimally invasive surgery, flexible needles can avoid blood vessels and organs more flexibly compared to rigid needles. One of the main challenges when using flexible needles to reach lesions is planning a suitable path. Due to the non-holonomic characteristic of the flexible needle dynamics and the tissue deformation caused by the needle tip during the insertion, the accessibility and safety of the needle’s states need to be considered in the path planning stage. In this article, we propose an adaptable algorithm by improving the canonical rapidly exploring random trees* (RRT*) algorithm to compute a path for the flexible needle to reach targets in a layered tissue environment. The improved RRT* algorithm that addresses the motion constraints of the flexible needle renders the computed path comparatively smoother and optimal in some approximation sense. In the proposed algorithm, a strategy of adapting some of its parameters for different tissues during the insertion is developed, which improves the safety of surgeries. Moreover, the path cost used in the algorithm takes the potential fields of surrounding obstacles into account, which is used to deal with the influence of the local movement of tissues during the needle puncture process. Simulations are conducted to verify the effectiveness of the proposed algorithm. The results show that the improved RRT* algorithm generates a smooth and safe path which satisfies the motion constraints of the flexible needle in layered tissue environment.

Coordinated control of a 3DOF cartesian robot and a shape memory alloy-actuated flexible needle for surgical interventions: a non-model-based control method

SummarySuccess of any needle-based medical procedures depends on accurate placement of the needle at the target location. However, accurate targeting and control of flexible self-actuating (active) needle are challenging. We have developed a shape memory alloy-actuated flexible needle steered by a 3D Cartesian robot and performed a comparative study of four, non-model-based, coordinated control methodologies for the combined robot steering and flexible-needle insertion process for surgical interventions. Investigated four controllers are: proportional–integral–derivative (PID), PID with the cubic of positional error term (PID-P3), static PID sliding mode controller, and robust adaptive PID sliding mode controller (RAPID-SMC). Relative efficacies of these controllers are demonstrated by performing experiements using a tissue-mimicking soft material phantom. Results from experiments have reavealed that RAPID-SMC is superior to other three controllers.

Research on Force Analysis and Path Planning of Flexible Needle Puncture Bending Modelling

Through the force analysis of the flexible needle puncture process, the corresponding mechanical model is established, and the main factors that cause the flexible needle bending deformation are analysed, and the bending model of the flexible needle puncture process is initially established. By discretizing the bending model, combined with experimental verification, a relatively complete bending model is obtained. Based on the RRT algorithm, the goal guidance algorithm, the optimal path selection algorithm, etc. are proposed, combined with the bending model of the flexible needle, and an improved RRT algorithm suitable for the flexible needle insertion method is established. Through simulation analysis and combined with experimental verification, it is concluded that path planning based on the improved RRT algorithm can bypass important human organs and soft tissues more flexibly, accurately puncture the target position, and achieve relatively safe surgery.

On the flexible needle insertion into the human liver

In the present research, the navigation of a flexible needle into the human liver in the context of the robotic-assisted intraoperative treatment of the liver tumors, is reported. Cosserat (micropolar) elasticity is applied to describe the interaction between the needle and the human liver. The theory incorporates the local rotation of points and the couple stress (a torque per unit area) as well as the force stress (force per unit area) representing the chiral features of the human liver. To predict the deformation of the needle and the liver, the elastic properties of the human liver have been evaluated. Outcomes reveal that considering smaller deformations of the needle and the liver results in better needle navigation mechanism. The needle geometry can enhance the penetration.

Design of Insertion Mechanism with Friction Wheels for Cannula Flexible Needle Based on TRIZ

Background: Flexible needle insertion is one of the minimally invasive surgeries, which takes advantage of the lateral force acted on the bevel tip to make the needle shaft bend when inserted into the tissue. The bending makes the needle avoid the obstacles (like bones, veins, nerves, etc.) in order to reach the target. However, the traditional flexible needle neither can change its curvature of the path, nor can realize a precise control because of the torsional friction between the needle and the tissue. Hence, a cannula flexible needle was proposed to overcome the drawbacks, which consists of a cannula and a stylet. Also, there is a need of an insertion mechanism for the cannula flexible needle in robot-assisted surgery. Objective: The aim of this paper is to innovatively design an insertion mechanism with friction wheels for the cannula flexible needle, which is used as an end-effector in robot-assisted surgery system. The mechanism is supposed to realize the coordinated driving of the cannula and the stylet in order to achieve variable curvatures of paths. Methods: Making references of the patents and research papers on needle insertion mechanisms, and based on the requirement of degree of freedom for the cannula flexible needle insertion, the insertion mechanism for the cannula flexible needle is designed by using the TRIZ theory. The conflicts matrix analysis, the invention principles and the substance-field analysis are used to innovatively design the driving scheme and the synchronous motion mechanism. Results and Conclusion: In this paper, the concrete structure design of the insertion mechanism for the cannula flexible needle is achieved, which is compact and simple. The friction coefficient between the needle and the wheels, and the pretightening force between both wheels are calculated through the data from experiments. The insertion accuracy of friction wheel mechanism is tested and analyzed through experimentation. The results show that the maximum placement error of the needle executed by the insertion mechanism is less than 0.5 mm, which meets the demands of surgical operations.

Dynamic Path Planning for Bevel-Tip Flexible Needle Insertion into Soft Tissue Based on a Real-Time Finite Element Model

This paper presents a novel dynamic path planning methodology for needle steering into the soft tissue. A real-time finite element model is used to simulate the procedure of a flexible needle into the homogeneous soft tissue, which provides the dynamic deformation information for the path planning. The relationship between needle base and tip is formulated as the transformations of homogeneous matrix with quasi-static assumptions. Based on the reachability of the flexible needle, the real-time motions of obstacles and target are considered through the dynamic needle-tissue interactions. A testbed including a XY linear stage, one rotator, and a CCD camera is constructed, and the experiments are designed to validate the proposed method. The 23G PTC needle was inserted into the PVA phantom with markers, and the CCD camera was utilized to record the needle trajectories and motions of target and obstacles. The targeting errors between the experimental and planned paths are less than 1.20 mm, and the distance from the obstacle to needle is not smaller than 1.16 mm. The results demonstrate that the proposed algorithm is effective for online planning the paths in the needle-tissue interactive environment.

Simulation of Coupling Process of Flexible Needle Insertion into Soft Tissue Based on ABAQUS

In order to get to the desired target inside the body, it is essential to investigate the needle-tissue coupling process and calculate the tissue deformation. A cantilever beam model is presented to predicting the deflection and bending angle of flexible needle by analyzing the distribution of the force on needle shaft during the procedure of needle insertion into soft tissue. Furthermore, a finite element (FE) coupling model is proposed to simulate the needle-tissue interactive process. The plane and spatial models are created to relate the needle and tissue nodes. Combined with the cantilever beam model and the finite element needle-tissue coupling model, the simulation of needle-tissue interaction was carried out by the ABAQUS software. The comparing experiments are designed to understand the needle-tissue interactions, by which the same points in the experiments and simulation are compared and analyzed. The results show that the displacements in x and z directions in the simulation can accord with the experiments, and the deformation inside the tissue mainly occurs in the axial direction. The study is beneficial to the robotassisted and virtual needle insertion procedure, and to help the physicians to predict the inside tissue deformation during the treatments.

Robot-assisted flexible needle insertion using universal distributional deep reinforcement learning.

Flexible needle insertion is an important minimally invasive surgery approach for biopsy and radio-frequency ablation. This approach can minimize intraoperative trauma and improve postoperative recovery. We propose a new path planning framework using multi-goal deep reinforcement learning to overcome the difficulties in uncertain needle-tissue interactions and enhance the robustness of robot-assisted insertion process. This framework utilizes a new algorithm called universal distributional Q-learning (UDQL) to learn a stable steering policy and perform risk management by visualizing the learned Q-value distribution. To further improve the robustness, universal value function approximation is leveraged in the training process of UDQL to maximize generalization and connect to diagnosis by adapting fast re-planning and transfer learning. Computer simulation and phantom experimental results show our proposed framework can securely steer flexible needles with high insertion accuracy and robustness. The framework also improves robustness by providing distribution information to clinicians for diagnosis and decision making during surgery. Compared with previous methods, the proposed framework can perform multi-target needle insertion through single insertion point qunder continuous state space model with higher accuracy and robustness.

3D Motion Planning for Flexible Needle Insertion Based on Rapidly-Exploring Random Trees with Environment-Adaptive Sampling and Central Angle Control

3D Motion Planning for Flexible Needle Insertion Based on Rapidly-Exploring Random Trees with Environment-Adaptive Sampling and Central Angle Control

Kinematic model and its parameter identification for cannula flexible needle insertion into soft tissue

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.

Robust path planning for flexible needle insertion using Markov decision processes.

Flexible needle has the potential to accurately navigate to a treatment region in the least invasive manner. We propose a new planning method using Markov decision processes (MDPs) for flexible needle navigation that can perform robust path planning and steering under the circumstance of complex tissue-needle interactions. This method enhances the robustness of flexible needle steering from three different perspectives. First, the method considers the problem caused by soft tissue deformation. The method then resolves the common needle penetration failure caused by patterns of targets, while the last solution addresses the uncertainty issues in flexible needle motion due to complex and unpredictable tissue-needle interaction. Computer simulation and phantom experimental results show that the proposed method can perform robust planning and generate a secure control policy for flexible needle steering. Compared with a traditional method using MDPs, the proposed method achieves higher accuracy and probability of success in avoiding obstacles under complicated and uncertain tissue-needle interactions. Future work will involve experiment with biological tissue in vivo. The proposed robust path planning method can securely steer flexible needle within soft phantom tissues and achieve high adaptability in computer simulation.

Modeling and Simulation of Flexible Needle Insertion Into Soft Tissue Using Modified Local Constraints

Needle insertion is a widely used medical procedure in various minimally invasive surgeries. The estimation of the coupled needle deflection and tissue deformation during the needle insertion procedure is crucial to the success of the surgery. In this work, a novel needle deflection–tissue deformation coupling model is proposed for flexible needle insertion into soft tissue. Based on the assumption that the needle deflection is small comparing to the length of the insertion, the needle–tissue interaction model is developed based on the modified local constraint method, where the interactive forces between the needle and the tissue are balanced through integration of needle–force and tissue–force relationships. A testbed is constructed and the experiments are designed to validate the proposed method using artificial phantom with markers. Based on the experimental analysis, the cutting and friction forces are separated from the force–time curves and used as the inputs into the proposed model. The trajectories of the markers inside the soft tissue are recorded by a CCD camera to compare with the simulation trajectories. The errors between the experimental and simulation trajectories are less than 0.8 mm. The results demonstrate that the proposed method is effective to model the needle insertion procedure.

Mechanics-Based Interactive Modeling for Medical Flexible Needle Insertion in Consideration of Nonlinear Factors

A mechanics-based model of flexible needle insertion into soft tissue is presented in this paper. Different from the existing kinematic model, a new model has been established based on the quasi-static principle, which also incorporates the dynamics of needle motions. In order to increase the accuracy of the model, nonlinear characteristics of the flexible needle and the soft tissue are both taken into account. The nonlinear Winkler foundation model and the modified Euler–Bernoulli theory are applied in this study, providing a theoretical framework to study insertion and deformation of needles. Galerkin method and iteration cycle analysis are applied in solving a series of deformation control equations to obtain the needle deflection. The parameters used in the mechanics-based model are obtained from the needle force and needle insertion experiment. Sensitivity studies show that the model can respond reasonably to changes in response to variations in different parameters. A 50 mm needle insertion simulation and a 50 mm corresponding needle insertion experiment are conducted to prove the validity of the model. At last, a study on different needle tip bevel demonstrates that the mechanics-based model can precisely predict the needle deflection when more than one parameter is changed. The solution can also be used in optimizing trajectory of the needle tip, enabling the needle to reach the target without touching important physiological structures such as blood vessels with the help of dynamic trajectory planning.

3D Dynamic Motion Planning for Robot-Assisted Cannula Flexible Needle Insertion into Soft Tissue

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.