Controlling the Error on Target Motion through Real-time Mesh Adaptation: Applications to Deep Brain Stimulation

We present an error-controlled mesh refinement procedure for needle insertion simulation and apply it to the simulation of electrode implantation for deep brain stimulation, including brain shift. Our approach enables to control the error in the computation of the displacement and stress fields around the needle tip and needle shaft by suitably refining the mesh, whilst maintaining a coarser mesh in other parts of the domain. We demonstrate through academic and practical examples that our approach increases the accuracy of the displacement and stress fields around the needle without increasing the computational expense. This enables real-time simulations. The proposed methodology has direct implications to increase the accuracy and control the computational expense of the simulation of percutaneous procedures such as biopsy, brachytherapy, regional anesthesia, or cryotherapy and can be essential to the development of robotic guidance.Comment: 21 pages, 14 figure

Robotics-Assisted Needle Steering for Percutaneous Interventions: Modeling and Experiments

Needle insertion and guidance plays an important role in medical procedures such as brachytherapy and biopsy. Flexible needles have the potential to facilitate precise targeting and avoid collisions during medical interventions while reducing trauma to the patient and post-puncture issues. Nevertheless, error introduced during guidance degrades the effectiveness of the planned therapy or diagnosis. Although steering using flexible bevel-tip needles provides great mobility and dexterity, a major barrier is the complexity of needle-tissue interaction that does not lend itself to intuitive control. To overcome this problem, a robotic system can be employed to perform trajectory planning and tracking by manipulation of the needle base. This research project focuses on a control-theoretic approach and draws on the rich literature from control and systems theory to model needle-tissue interaction and needle flexion and then design a robotics-based strategy for needle insertion/steering. The resulting solutions will directly benefit a wide range of needle-based interventions. The outcome of this computer-assisted approach will not only enable us to perform efficient preoperative trajectory planning, but will also provide more insight into needle-tissue interaction that will be helpful in developing advanced intraoperative algorithms for needle steering. Experimental validation of the proposed methodologies was carried out on a state of-the-art 5-DOF robotic system designed and constructed in-house primarily for prostate brachytherapy. The system is equipped with a Nano43 6-DOF force/torque sensor (ATI Industrial Automation) to measure forces and torques acting on the needle shaft. In our setup, an Aurora electromagnetic tracker (Northern Digital Inc.) is the sensing device used for measuring needle deflection. A multi-threaded application for control, sensor readings, data logging and communication over the ethernet was developed using Microsoft Visual C 2005, MATLAB 2007 and the QuaRC Toolbox (Quanser Inc.). Various artificial phantoms were developed so as to create a realistic medium in terms of elasticity and insertion force ranges; however, they simulated a uniform environment without exhibiting complexities of organic tissues. Experiments were also conducted on beef liver and fresh chicken breast, beef, and ham, to investigate the behavior of a variety biological tissues

Real-time Error Control for Surgical Simulation

Objective: To present the first real-time a posteriori error-driven adaptive finite element approach for real-time simulation and to demonstrate the method on a needle insertion problem. Methods: We use corotational elasticity and a frictional needle/tissue interaction model. The problem is solved using finite elements within SOFA. The refinement strategy relies upon a hexahedron-based finite element method, combined with a posteriori error estimation driven local $h$-refinement, for simulating soft tissue deformation. Results: We control the local and global error level in the mechanical fields (e.g. displacement or stresses) during the simulation. We show the convergence of the algorithm on academic examples, and demonstrate its practical usability on a percutaneous procedure involving needle insertion in a liver. For the latter case, we compare the force displacement curves obtained from the proposed adaptive algorithm with that obtained from a uniform refinement approach. Conclusions: Error control guarantees that a tolerable error level is not exceeded during the simulations. Local mesh refinement accelerates simulations. Significance: Our work provides a first step to discriminate between discretization error and modeling error by providing a robust quantification of discretization error during simulations.Comment: 12 pages, 16 figures, change of the title, submitted to IEEE TBM

Respiratory Compensated Robot for Liver Cancer Treatment: Design, Fabrication, and Benchtop Characterization

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death in the world. Radiofrequency ablation (RFA) is an effective method for treating tumors less than 5 cm. However, manually placing the RFA needle at the site of the tumor is challenging due to the complicated respiratory induced motion of the liver. This paper presents the design, fabrication, and benchtop characterization of a patient mounted, respiratory compensated robotic needle insertion platform to perform percutaneous needle interventions. The robotic platform consists of a 4-DoF dual-stage cartesian platform used to control the pose of a 1-DoF needle insertion module. The active needle insertion module consists of a 3D printed flexible fluidic actuator capable of providing a step-like, grasp-insert-release actuation that mimics the manual insertion procedure. Force characterization of the needle insertion module indicates that the device is capable of producing 22.6 ± 0.40 N before the needle slips between the grippers. Static phantom targeting experiments indicate a positional error of 1.14 ± 0.30 mm and orientational error of 0.99° ± 0.36°. Static ex-vivo porcine liver targeting experiments indicate a positional error of 1.22 ± 0.31 mm and orientational error of 1.16° ± 0.44°. Dynamic targeting experiments with the proposed active motion compensation in dynamic phantom and ex-vivo porcine liver show 66.3% and 69.6% positional accuracy improvement, respectively. Future work will continue to develop this platform with the long-term goal of applying the system to RFA for HCC

Energy shaping control for robotic needle insertion

This work investigates the use of energy shaping control to reduce deflection in slender beams with tip load and actuation at the base. The ultimate goal of this research is a buckling avoidance strategy for robotic-assisted needle insertion. To this end, the rigid-link model of a flexible beam actuated at the base and subject to tip load is proposed, and an energy shaping approach is employed to construct a nonlinear controller that accounts for external forces. A comparative simulation study highlights the benefits of the proposed approach over a linear control baseline and a simplified nonlinear control

A Novel Flexible and Steerable Probe for Minimally Invasive Soft Tissue Intervention

Current trends in surgical intervention favour a minimally invasive (MI) approach, in which complex procedures are performed through increasingly small incisions. Specifically, in neurosurgery, there is a need for minimally invasive keyhole access, which conflicts with the lack of maneuverability of conventional rigid instruments. In an attempt to address this fundamental shortcoming, this thesis describes the concept design, implementation and experimental validation of a novel flexible and steerable probe, named “STING” (Soft Tissue Intervention and Neurosurgical Guide), which is able to steer along curvilinear trajectories within a compliant medium. The underlying mechanism of motion of the flexible probe, based on the reciprocal movement of interlocked probe segments, is biologically inspired and was designed around the unique features of the ovipositor of certain parasitic wasps. Such insects are able to lay eggs by penetrating different kinds of “host” (e.g. wood, larva) with a very thin and flexible multi-part channel, thanks to a micro-toothed surface topography, coupled with a reciprocating “push and pull” motion of each segment. This thesis starts by exploring these foundations, where the “microtexturing” of the surface of a rigid probe prototype is shown to facilitate probe insertion into soft tissue (porcine brain), while gaining tissue purchase when the probe is tensioned outwards. Based on these findings, forward motion into soft tissue via a reciprocating mechanism is then demonstrated through a focused set of experimental trials in gelatine and agar gel. A flexible probe prototype (10 mm diameter), composed of four interconnected segments, is then presented and shown to be able to steer in a brain-like material along multiple curvilinear trajectories on a plane. The geometry and certain key features of the probe are optimised through finite element models, and a suitable actuation strategy is proposed, where the approach vector of the tip is found to be a function of the offset between interlocked segments. This concept of a “programmable bevel”, which enables the steering angle to be chosen with virtually infinite resolution, represents a world-first in percutaneous soft tissue surgery. The thesis concludes with a description of the integration and validation of a fully functional prototype within a larger neurosurgical robotic suite (EU FP7 ROBOCAST), which is followed by a summary of the corresponding implications for future work

A Novel Bio-Inspired Insertion Method for Application to Next Generation Percutaneous Surgical Tools

The use of minimally invasive techniques can dramatically improve patient outcome from neurosurgery, with less risk, faster recovery, and better cost effectiveness when compared to conventional surgical intervention. To achieve this, innovative surgical techniques and new surgical instruments have been developed. Nevertheless, the simplest and most common interventional technique for brain surgery is needle insertion for either diagnostic or therapeutic purposes. The work presented in this thesis shows a new approach to needle insertion into soft tissue, focussing on soft tissue-needle interaction by exploiting microtextured topography and the unique mechanism of a reciprocating motion inspired by the ovipositor of certain parasitic wasps. This thesis starts by developing a brain-like phantom which I was shown to have mechanical properties similar to those of neurological tissue during needle insertion. Secondly, a proof-of-concept of the bio-inspired insertion method was undertaken. Based on this finding, the novel method of a multi-part probe able to penetrate a soft substrate by reciprocal motion of each segment is derived. The advantages of the new insertion method were investigated and compared with a conventional needle insertion in terms of needle-tissue interaction. The soft tissue deformation and damage were also measured by exploiting the method of particle image velocimetry. Finally, the thesis proposes the possible clinical application of a biologically-inspired surface topography for deep brain electrode implantation. As an adjunct to this work, the reciprocal insertion method described here fuelled the research into a novel flexible soft tissue probe for percutaneous intervention, which is able to steer along curvilinear trajectories within a compliant medium. Aspects of this multi-disciplinary research effort on steerable robotic surgery are presented, followed by a discussion of the implications of these findings within the context of future work

On the Application of Mechanical Vibration in Robotics-Assisted Soft Tissue Intervention

Mechanical vibration as a way of transmitting energy has been an interesting subject to study. While cyclic oscillation is usually associated with fatigue effect, and hence a detrimental factor in failure of structures and machineries, by controlled transmission of vibration, energy can be transferred from the source to the target. In this thesis, the application of such mechanical vibration in a few surgical procedures is demonstrated. Three challenges associated with lung cancer diagnosis and treatment are chosen for this purpose, namely, Motion Compensation, tumor targeting in lung Needle Insertion and Soft Tissue Dissection: A robotic solution is proposed for compensating for the undesirable oscillatory motion of soft tissue (caused by heart beat and respiration) during needle insertion in the lung. An impedance control strategy based on a mechanical vibratory system is implemented to minimize the tissue deformation during needle insertion. A prototype was built to evaluate the proposed approach using: 1) two Mitsubishi PA10-7C robots, one for manipulating the macro part and the other for mimicking the tissue motion, 2) one motorized linear stage to handle the micro part, and 3) a Phantom Omni haptic device for remote manipulation. Experimental results are given to demonstrate the performance of the motion compensation system. A vibration-assisted needle insertion technique has been proposed in order to reduce needle–tissue friction. The LuGre friction model is employed as a basis for the study and the model is extended and analyzed to include the impact of high-frequency vibration on translational friction. Experiments are conducted to evaluate the role of insertion speed as well as vibration frequency on frictional effects. In the experiments conducted, an 18 GA brachytherapy needle was vibrated and inserted into an ex-vivo soft tissue sample using a pair of amplified piezoelectric actuators. Analysis demonstrates that the translational friction can be reduced by introducing a vibratory low-amplitude motion onto a regular insertion profile, which is usually performed at a constant rate. A robotics-assisted articulating ultrasonic surgical scalpel for minimally invasive soft tissue cutting and coagulation is designed and developed. For this purpose, the optimal design of a Langevin transducer with stepped horn profile is presented for internal-body applications. The modeling, optimization and design of the ultrasonic scalpel are performed through equivalent circuit theory and verified by finite element analysis. Moreover, a novel surgical wrist, compatible with the da Vinci® surgical system, with decoupled two degrees-of-freedom (DOFs) is developed that eliminates the strain of pulling cables and electrical wires. The developed instrument is then driven using the dVRK (da Vinci® research kit) and the Classic da Vinci® surgical system

下腹部を対象とした極細針によるCTガイド下高正確度穿刺プランニング

早大学位記番号:新8149早稲田大

A mechanics-based model for simulation and control of flexible needle insertion in soft tissue

AbstractIn needle-based medical procedures, beveled-tip exible needles are steered inside soft tissue with the aim of reaching pre-dened target locations. The efciency of needle-based interventions depends on accurate control of the needle tip. This paper presents a comprehensive mechanics-based model for simulation of planar needle insertion in soft tissue. The proposed model for needle deection is based on beam theory, works in real-time, and accepts the insertion velocity as an input that can later be used as a control command for needle steering. The model takes into account the effects of tissue deformation, needle-tissue friction, tissue cutting force, and needle bevel angle on needle deection. Using a robot that inserts a exible needle into a phantom tissue, various experiments are conducted to separately identify different subsets of the model parameters. The validity of the proposed model is veried by comparing the simulation results to the empirical data. The results demonstrate the accuracy of the proposed model in predicting the needle tip deection for different insertion velocities. I