Toward a Miniaturized Needle Steering System With Path Planning for Obstacle Avoidance

Percutaneous intervention is among the preferred diagnostic and treatment options in surgery today. Recently, a biologically inspired needle steering system was proposed, where a novel “programmable bevel” is employed to control the tip angle as a function of the offset between interlocked needle segments. The new device, codenamed soft tissue intervention and neurosurgical guide (STING), can steer along arbitrary curvilinear trajectories within a compliant medium, and be controlled by means of an embedded position sensor. In this study, we provide details of our latest attempt to miniaturize the STING, with the design and manufacture of a 4-mm outer diameter (OD) two-part prototype that includes unique features, such as a bespoke trocar and insertion mechanism, which ensure that the segments do not come apart or buckle during the insertion process. It is shown that this prototype can steer around tight bends (down to a radius of curvature of ~70 mm), a performance which is comparable to the best systems in this class. With the need to comply with the specific mechanical constraints of STING, this paper also introduces a novel path planner with obstacle avoidance, which can produce a differentiable trajectory that satisfies constraints on both the maximum curvature of the final trajectory and its derivative. In vitro results in gelatin for the integrated prototype and path planner demonstrate accurate 2-D trajectory following (0.1 mm tracking error, with 0.64 mm standard deviation), with significant scope for future improvements.

[1]  Daniele Dini,et al.  Detailed finite element modelling of deep needle insertions into a soft tissue phantom using a cohesive approach , 2013, Computer methods in biomechanics and biomedical engineering.

[2]  Philip A Starr,et al.  Risk Factors for Hemorrhage during Microelectrode-guided Deep Brain Stimulator Implantation for Movement Disorders , 2005, Neurosurgery.

[3]  Seong-Young Ko,et al.  Closed-Loop Planar Motion Control of a Steerable Probe With a “Programmable Bevel” Inspired by Nature , 2011, IEEE Transactions on Robotics.

[4]  Satoshi Kagami,et al.  Continuous Curvature Trajectory Generation with Obstacle Avoidance for Car-Like Robots , 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

[5]  Daniel Glozman,et al.  Image-Guided Robotic Flexible Needle Steering , 2007, IEEE Transactions on Robotics.

[6]  Kenneth Y. Goldberg,et al.  Motion Planning Under Uncertainty for Image-guided Medical Needle Steering , 2008, Int. J. Robotics Res..

[7]  V. Kallem,et al.  Integrated planning and image-guided control for planar needle steering , 2008, 2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

[8]  Seong-Young Ko,et al.  Trajectory following for a flexible probe with state/input constraints: An approach based on model predictive control , 2012, Robotics Auton. Syst..

[9]  L. Dubins On Curves of Minimal Length with a Constraint on Average Curvature, and with Prescribed Initial and Terminal Positions and Tangents , 1957 .

[10]  Septimiu E. Salcudean,et al.  Needle Steering and Model-Based Trajectory Planning , 2003, MICCAI.

[11]  Laurent D. Cohen,et al.  Fast extraction of minimal paths in 3D images and applications to virtual endoscopy , 2001, Medical Image Anal..

[12]  Jin Seob Kim,et al.  Diffusion-Based Motion Planning for a Nonholonomic Flexible Needle Model , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[13]  Yan Pailhas,et al.  Path Planning for Autonomous Underwater Vehicles , 2007, IEEE Transactions on Robotics.

[14]  D. Minhas,et al.  Percutaneous Intracerebral Navigation by Duty-Cycled Spinning of Flexible Bevel-Tipped Needles , 2010, Neurosurgery.

[15]  Ron Alterovitz,et al.  Interactive motion planning for steerable needles in 3D environments with obstacles , 2010, 2010 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

[16]  Pierre E. Dupont,et al.  Design and Control of Concentric-Tube Robots , 2010, IEEE Transactions on Robotics.

[17]  D. Caleb Rucker,et al.  A model for concentric tube continuum robots under applied wrenches , 2010, 2010 IEEE International Conference on Robotics and Automation.

[18]  G. Dogangil,et al.  A review of medical robotics for minimally invasive soft tissue surgery , 2010, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[19]  Laurent D. Cohen,et al.  Global Minimum for Active Contour Models: A Minimal Path Approach , 1997, International Journal of Computer Vision.

[20]  Gregory S. Chirikjian,et al.  Steering flexible needles under Markov motion uncertainty , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[21]  Yonghua Chen,et al.  Magnetic force aided compliant needle navigation and needle performance analysis , 2007, 2007 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[22]  L Frasson,et al.  STING: a soft-tissue intervention and neurosurgical guide to access deep brain lesions through curved trajectories , 2010, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[23]  Robert J. Webster,et al.  Planning active cannula configurations through tubular anatomy , 2010, 2010 IEEE International Conference on Robotics and Automation.

[24]  Robert J. Webster,et al.  Toward robotic needle steering in lung biopsy: a tendon-actuated approach , 2011, Medical Imaging.

[25]  Rajni V. Patel,et al.  Needle insertion into soft tissue: a survey. , 2007, Medical engineering & physics.

[26]  S. Shankar Sastry,et al.  3D Motion Planning Algorithms for Steerable Needles Using Inverse Kinematics , 2008, WAFR.

[27]  Seong-Young Ko,et al.  Smooth path planning for a biologically-inspired neurosurgical probe , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[28]  A. Kelly,et al.  TRAJECTORY GENERATION FOR CAR-LIKE ROBOTS USING CUBIC CURVATURE POLYNOMIALS , 2001 .