Shape determination during needle insertion With curvature measurements

The determination of a flexible needle shape during the insertion is an important issue in minimally invasive surgery techniques. This is especially critical when considering conventional surgery procedures where a surgeon usually determines how to proceed needle insertion further based on the current needle trajectory inserted into tissue during biopsy and removal of malignant tissues in the body. In this paper, we propose a new method to determine the shape of a needle that is being inserted, together with the curvature measurement data obtained by fiber Bragg gratings (FBG) sensors inside the needle. This approach can be particularly advantageous to the situations where visual guidance (such as by ultrasound probes) is not easily applicable. The description of a needle shape is based on the elastic rod theory and Lie-group-theoretic approach. We also present the comparison between two different calibration methods, which have an impact on the quality of the results of the proposed method. In order to verify the proposed method, needle trajectories by the model are compared with experimental data obtained by image analysis, which in turn emphasizes the capability of the proposed method.

[1]  Jenny Dankelman,et al.  Error Analysis of FBG-Based Shape Sensors for Medical Needle Tracking , 2014, IEEE/ASME Transactions on Mechatronics.

[2]  Darryl D. Holm,et al.  The Euler–Poincaré Equations and Semidirect Products with Applications to Continuum Theories , 1998, chao-dyn/9801015.

[3]  Gabor Fichtinger,et al.  Real-time tracking of a bevel-tip needle with varying insertion depth: Toward teleoperated MRI-guided needle steering , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  S. Misra,et al.  Three-Dimensional Needle Shape Reconstruction Using an Array of Fiber Bragg Grating Sensors , 2014, IEEE/ASME Transactions on Mechatronics.

[5]  Rajnikant V. Patel,et al.  Deflection of a Flexible Needle during Insertion into Soft Tissue , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[6]  Septimiu E. Salcudean,et al.  Needle steering and motion planning in soft tissues , 2005, IEEE Transactions on Biomedical Engineering.

[7]  Gregory S. Chirikjian,et al.  Robotic Needle Steering: Design, Modeling, Planning, and Image Guidance , 2011 .

[8]  Sarthak Misra,et al.  Integrating Deflection Models and Image Feedback for Real-Time Flexible Needle Steering , 2013, IEEE Transactions on Robotics.

[9]  Carlos Rossa,et al.  A Two-Body Rigid/Flexible Model of Needle Steering Dynamics in Soft Tissue , 2016, IEEE/ASME Transactions on Mechatronics.

[10]  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.

[11]  C.N. Riviere,et al.  Flexible Needle Steering System for Percutaneous Access to Deep Zones of the Brain , 2006, Proceedings of the IEEE 32nd Annual Northeast Bioengineering Conference.

[12]  Allison M. Okamura,et al.  3-D Ultrasound-Guided Robotic Needle Steering in Biological Tissue , 2014, IEEE Transactions on Biomedical Engineering.

[13]  Zhengyou Zhang,et al.  A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Rajnikant V. Patel,et al.  Curvature, Torsion, and Force Sensing in Continuum Robots Using Helically Wrapped FBG Sensors , 2016, IEEE Robotics and Automation Letters.

[15]  Jinwu Qian,et al.  On SDM/WDM FBG sensor net for shape detection of endoscope , 2005, IEEE International Conference Mechatronics and Automation, 2005.

[16]  Russell H. Taylor,et al.  A sub-millimetric, 0.25 mN resolution fully integrated fiber-optic force-sensing tool for retinal microsurgery , 2009, International Journal of Computer Assisted Radiology and Surgery.

[17]  Pierre E. Dupont,et al.  FBG-based shape sensing tubes for continuum robots , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[18]  Robert Rohling,et al.  Hand-held steerable needle device , 2003, IEEE/ASME Transactions on Mechatronics.

[19]  Jin Seob Kim,et al.  Conformational analysis of stiff chiral polymers with end-constraints , 2006, Molecular simulation.

[20]  R. J. Black,et al.  Real-Time Estimation of 3-D Needle Shape and Deflection for MRI-Guided Interventions , 2010, IEEE/ASME Transactions on Mechatronics.

[21]  Gregory S. Chirikjian,et al.  Nonholonomic Modeling of Needle Steering , 2006, Int. J. Robotics Res..

[22]  Carlos Rossa,et al.  A mechanics-based model for simulation and control of flexible needle insertion in soft tissue , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

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