Estimation Equation of Needle Deflection Based on Dynamics Model in Robot-Assisted Percutaneous Surgery

2011 ◽  
Vol 317-319 ◽  
pp. 633-637
Author(s):  
Wen Zhong Ma ◽  
Dong Mei Wu ◽  
Zhi Jiang Du
Keyword(s):  
Soft Tissue ◽  
Needle Insertion ◽  
Experimental Result ◽  
Percutaneous Surgery ◽  
Dynamics Model ◽  
Robot Assisted ◽  
Needle Deflection ◽  
Reference Strategy

Aimed to robot-assisted percutaneous surgery, we present an estimation equation to calculate the deflection at needle tip based on dynamics model in this paper. According to the equation, we can use the needle loads to calculate the estimation deflection of needle tip, during needle insertion into soft tissue. Finally, verifying experiments of estimation equation were carried out on a liver. The experimental result shows that the error of equation proposed is small and acceptable. This equation can be used to estimate deflection and direction of needle tip, and can also provide a reference strategy in robot-assisted percutaneous surgery

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

2016 ◽  
Vol 11 (1) ◽  
Author(s):  
Shan Jiang ◽  
Xingji Wang
Keyword(s):  
Soft Tissue ◽  
Kinematic Model ◽  
Needle Insertion ◽  
Winkler Foundation ◽  
Nonlinear Characteristics ◽  
Deformation Control ◽  
Needle Deflection ◽  
Iteration Cycle ◽  
Foundation Model ◽  
Sensitivity Studies

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.

A MECHANICS-BASED MODEL FOR SIMULATING THE NEEDLE DEFLECTION IN TRANSVERSE ISOTROPIC TISSUE FOR A PERCUTANEOUS PUNCTURE

2019 ◽  
Vol 19 (06) ◽  
pp. 1950060 ◽  
Author(s):  
WANYU LIU ◽  
ZHIYONG YANG ◽  
SHAN JIANG
Keyword(s):  
Needle Insertion ◽  
Robot Assisted ◽  
Insertion Depth ◽  
Interaction Forces ◽  
Percutaneous Puncture ◽  
Needle Deflection ◽  
Isotropic Elasticity ◽  
Transverse Isotropic ◽  
Radioactive Seeds ◽  
Medical Needle

During the percutaneous puncture for robot-assisted brachytherapy, a medical needle is usually inserted into fiber-structured soft tissue which has transverse isotropic elasticity, such as muscle and skin, to deliver radioactive seeds that kill cancer cells. To place the radioactive seeds more accurately, it is necessary to assess the effect of the transverse isotropic elasticity on the needle deflection. A mechanics-based model for simulating the needle deflection in transverse isotropic tissue is developed in this paper. The anisotropic needle–tissue interaction forces are estimated and used as inputs to drive the model for simulating needle deflections for different insertion orientation angles. Automatic insertion experiments were performed on a single-layered porcine muscle at five different insertion orientation angles. The results show that the maximum difference in the tip deflection for the different insertion orientation angles is 2.99[Formula: see text]mm when the insertion depth is 50[Formula: see text]mm. The maximum simulated error of the needle axis deflection is 0.62[Formula: see text]mm for all insertion orientation angles. The developed model can successfully simulate the needle deflections inside transverse isotropic tissue for different insertion orientation angles. This work is useful for predicting and compensating for the deflection error for automatic needle insertion.

Simulation for Needle Deflection and Soft Tissue Deformation in Needle Insertion

2010 ◽  
Vol 139-141 ◽  
pp. 889-892
Author(s):  
De Dong Gao ◽  
Hao Jun Zheng
Keyword(s):  
Finite Element ◽  
Soft Tissue ◽  
Three Dimensional ◽  
Needle Insertion ◽  
Tissue Deformation ◽  
Spring Model ◽  
Ansys Software ◽  
Soft Tissue Deformation ◽  
Needle Deflection ◽  
Element Method

Needle deflection and soft tissue deformation are the most important factors that affect accuracy in needle insertion. Based on the quasi-static thinking and needle forces, an improved virtual spring model and a finite element method are presented to analyze needle deflection and soft tissue deformation when a needle is inserted into soft tissue. According to the spring model, the trajectory of the needle tip is calculated with MATLAB using different parameters. With the superposed element method, the two and three dimensional quasi-static finite element models are created to simulate the dynamic process of soft tissue deformation using ANSYS software. The two methods will be available for steering the flexible needle to hit the target and avoid the obstacles precisely in the robot-assisted needle insertion.

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

2016 ◽  
Vol 138 (12) ◽  
Author(s):  
Dedong Gao ◽  
Yong Lei ◽  
Bin Lian ◽  
Bin Yao
Keyword(s):  
Soft Tissue ◽  
Interaction Model ◽  
Ccd Camera ◽  
Coupling Model ◽  
Needle Insertion ◽  
Medical Procedure ◽  
Tissue Deformation ◽  
Friction Forces ◽  
Needle Deflection ◽  
Insertion Procedure

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.

Position Control of Needle Tip Based on Physical Properties of Liver and Force Sensor

2006 ◽  
Vol 18 (2) ◽  
pp. 167-176 ◽  
Author(s):  
Yo Kobayashi ◽  
◽  
Jun Okamoto ◽  
Masakatsu G. Fujie ◽  
Keyword(s):  
Robot Control ◽  
Position Control ◽  
Force Sensor ◽  
Needle Insertion ◽  
Experimental Result ◽  
Medical Procedures ◽  
Needle Deflection ◽  
Model Based ◽  
Liver Model ◽  
Organ Model

Medical procedures such as RFA and cryosurgery require needle insertion, which is difficult because it can easily result in organs being deformed and displaced. In addition, Because deflection occurs more easily with thin needles, needle deflection must be considered. We developed an intelligent robot for needle insertion, incorporating visual feedback, force control, and organ-model-based control. Two experiments were evaluating hepatic properties for organ-model-based robot control. And a dynamic viscoelastic test was done to show dynamic hepatic properties as a differential equation. Their nonlinearity was supported by a creep test. And, this paper shows the deflection correction with (a) the force sensor only, (b) liver model only, (c) both force sensor and liver model is done to control the position of the needle tip. The experimental result shows that using (c) gives optimal effectiveness among the proposed approaches.

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

10.5772/64199 ◽  
2016 ◽  
Vol 13 (3) ◽  
pp. 121 ◽  
Author(s):  
Yan-Jiang Zhao ◽  
Wen-Qiang Wu ◽  
Yong-De Zhang ◽  
Rui-Xue Wang ◽  
Jing-Chun Peng ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Motion Planning ◽  
Needle Insertion ◽  
Robot Assisted ◽  
Dynamic Motion ◽  
Dynamic Motion Planning

STUDY OF THE TARGETING ERROR FOR PERCUTANEOUS NEEDLE INSERTION INTO SOFT PHANTOM MATERIAL

2016 ◽  
Vol 16 (02) ◽  
pp. 1650005 ◽  
Author(s):  
XINGJI WANG ◽  
SHAN JIANG
Keyword(s):  
Soft Tissue ◽  
Interaction Model ◽  
Needle Insertion ◽  
Uniaxial Tensile ◽  
Fe Model ◽  
Target Displacement ◽  
Uniaxial Tensile Strength ◽  
Needle Deflection ◽  
Two Factors ◽  
Insertion Process

Percutaneous needle insertion is widely used in minimally invasive procedures, in which the flexible needle is steered to reach a specific target inside the human body. The targeting error is due to a combination of flexible needle deflection and target displacement in soft tissue and only a very limited number of studies have focused on both two factors. This paper presents a targeting error calculation method which incorporates an energy-based needle deflection model into a soft tissue finite-element (FE) model. The needle insertion process is discretized into several increments on the basis of the quasi-static method. Needle deflection in each step is obtained by the needle-soft tissue interaction model which is applied into the FE model as the displacement input. A 2D-planar FE model is used to model the target displacement by imposing needle distribution forces and needle deflection at different steps on the appointed reference nodes. The soft tissue is modeled as a non-linear hyperelastic material with geometrical non-linearity. Uniaxial tensile strength tests are utilized to determine the soft tissue parameters. Needle targeting experiments are conducted to validate the simulation results. Results show that the proposed method can predict the needle targeting errors while the averaged prediction error stays below 0.4[Formula: see text]mm. At last, we conduct different experiments to compensate the obtained targeting error and thus, reaching preferable effects.

Needle Tracking and Deflection Prediction for Robot-Assisted Needle Insertion Using 2D Ultrasound Images

2016 ◽  
Vol 01 (01) ◽  
pp. 1640001 ◽  
Author(s):  
Michael Waine ◽  
Carlos Rossa ◽  
Ron Sloboda ◽  
Nawaid Usmani ◽  
Mahdi Tavakoli
Keyword(s):  
Interaction Model ◽  
Needle Insertion ◽  
Steering System ◽  
Target Area ◽  
Ultrasound Images ◽  
Tissue Deformation ◽  
Robot Assisted ◽  
Needle Deflection ◽  
The Us ◽  
2D Ultrasound

In many types of percutaneous needle insertion surgeries, tissue deformation and needle deflection can create significant difficulties for accurate needle placement. In this paper, we present a method for automatic needle tracking in 2D ultrasound (US) images, which is used in a needle–tissue interaction model to estimate current and future needle tip deflection. This is demonstrated using a semi-automatic needle steering system. The US probe can be controlled to follow the needle tip or it can be stopped at an appropriate position to avoid tissue deformation of the target area. US images are used to fully parameterize the needle-tissue model. Once the needle deflection reaches a pre-determined threshold, the robot rotates the needle to correct the tip’s trajectory. Experimental results show that the final needle tip deflection can be estimated with average accuracies between 0.7[Formula: see text]mm and 1.0[Formula: see text]mm for insertions with and without rotation. The proposed method provides surgeons with improved US feedback of the needle tip deflection and minimizes the motion of the US probe to reduce tissue deformation of the target area.

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