Needle-based procedures are commonly performed during minimally invasive surgery for treatment and diagnosis. Accurate needle tip placement is important for the success of the procedures. Misplacement of the needle tip might cause unsuccessful treatment or misdiagnosis. Robot-assisted needle insertion systems have been developed in order to steer flexible bevel-tipped needles. However, current systems depend on the information of maximum needle curvature, which is estimated by performing prior insertions. This work presents a new three-dimensional flexible needle steering system which integrates an optimal steering control, ultrasound-based needle tracking system, needle deflection model, online needle curvature estimation and offline curvature estimation based on biomechanics properties. The online and the offline curvature estimations are used to update the steering control in real time. The system is evaluated by experiments in gelatin phantoms and biological tissues (chicken breast tissues). The average targeting error in gelatin phantoms is 0.42 ± 0.17 mm, and in biological tissues is 1.63 ± 0.29 mm. The system is able to accurately steer a flexible needle in multi-layer phantoms and biological tissues without performing prior insertions to estimate the maximum needle curvature.
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Abayazid, M., R. J. Roesthuis, R. Reilink, and S. Misra. Integrating deflection models and image feedback for real-time flexible needle steering. IEEE Trans. Robot. 29:542–553, 2013.
Abayazid, M., G. Vrooijink, S. Patil, R. Alterovitz, and S. Misra. Experimental evaluation of ultrasound-guided 3D needle steering in biological tissue. Int. J. CARS 9:931–939, 2014.
Abolhassani, N., R. Patel, and M. Moallem. Needle insertion into soft tissue: a survey. Med. Eng. Phys. 29:413–431, 2007.
Abolhassani, N. and R. V. Patel. Deflection of a flexible needle during insertion into soft tissue. In: 28th Annual International Conference of IEEE Engineering in Medicine and Biology Society (EMBS), USA, 2006, pp. 3858–3861.
Asadian, A., M. R. Kermani, and R. V. Patel. An analytical model for deflection of flexible needles during needle insertion. In: Intelligent Robots and Systems (IROS), 2011, pp. 2551–2556.
Bernardes, M. C., B. V. Adorno, P. Poignet, and G. A. Borges. Robot-assisted automatic insertion of steerable needles with closed-loop imaging feedback and intraoperative trajectory replanning. Mechatronics 23:630–645, 2013.
Chun, H. Y., M. T. Kim, H. C. Jung, K. Ko, and K. G. Kim. Experimental study on needle insertion force for breast. World Congr. Med. Phys. Biomed. Eng. 39:2182–2183, 2013. doi:10.1007/978-3-642-29305-4_572.
Cowan, N. J., K. Goldberg, G. S. Chirikjian, G. Fichtinge, R. Alterovitz, K. B. Reed, V. Kallem, W. Park, S. Misra, and A. M. Okamura. Robotic needle steering: design, modeling, planning, and image guidance. In: Surgical Robotics—Systems, Applications, and Visions, edited by J. Rosen, B. Hannaford, and R. Satava. New York: Springer, 2011, pp. 557–582.
DiMaio, S. P., and S. E. Salcudean. Needle insertion modeling and simulation. IEEE Trans. Robot. Autom. 19:864–875, 2003.
Eichelberger, L. E., M. O. Koch, J. K. Daggy, T. M. Ulbright, J. N. Eble, and L. Cheng. Predicting tumor volume in radical prostatectomy specimens from patients with prostate cancer. Am. J. Clin. Pathol. 120:386–391, 2003.
Engh, J., G. Podnar, D. Kondziolka, and C. Riviere. Toward effective needle steering in brain tissue. In: IEEE EMBS Annual International Conference, 2006, pp. 559–562.
Fung, Y. C. Biomechanics: Mechanical Properties of Living Tissue. New York: Springer, 1993.
Gefen, A., and B. Dilmoney. Mechanics of the normal woman’s breast. Technol. Health Care 15:259–271, 2007.
Glozman, D., and M. Shoham. Image-guided robotic flexible needle steering. IEEE Trans. Rob. 23:459–467, 2007.
Majewicz, A., S. P. Marra, M. G. van Vledder, L. MingDe, M. A. Choti, D. Y. Song, and A. M. Okamura. Behavior of tip-steerable needles in ex vivo and in vivo tissue. IEEE Trans. Biomed. Eng. 59:2705–2715, 2012.
Minhas, D. S., J. A. Engh, M. M. Fenske, and C. N. Riviere. Modeling of needle steering via duty-cycled spinning. In: IEEE EMBS Annual International Conference, 2007, pp. 5432–5435.
Misra, S., K. T. Ramesh, and A. M. Okamura. Modeling of tool-tissue interactions for computer-based surgical simulation: a literature review. Presence Teleop. Virt. 17:463–491, 2008.
Misra, S., K. B. Reed, B. W. Schafer, K. T. Ramesh, and A. M. Okamura. Mechanics of flexible needles robotically steered through soft tissue. Int. J. Robot. Res. 23:1640–1660, 2010.
Moreira, P., S. Patil, R. Alterovitz, and S. Misra. Needle steering in biological tissue using ultrasound-based online curvature estimation. In: IEEE International Conference on Robotics Automation, 2014, pp. 4368–4373.
Nightingale, K., S. McAleavey, and G. Trahey. Shear-wave generation using acoustic radiation force: in vivo and ex vivo results. Ultrasound Med. Biol. 29:1715–1723, 2003.
Pacchierotti, C., M. Abayazid, S. Misra, and D. Prattichizzo. Teleoperation of steerable flexible needles by combining kinesthetic and vibratory feedback. IEEE Trans. Haptics, 1–1, 2014. doi:10.1109/TOH.2014.2360185.
Patil, S., J. Burgner, R. J. Webster, and R. Alterovitz. Needle steering in 3-D via rapid replanning. IEEE Trans. Robot. 30:853–864, 2014. doi:10.1109/TRO.2014.2307633.
Podder, T. K., D. P. Clark, J. Sherman, D. Fuller, E. M. Messing, D. J. Rubens, J. G. Strang, Y. D. Zhang, W. O’Dell, W. S. Ng, and Y. Yu. Effects of tip geometry of surgical needles: an assessment of force and deflection. In: European Medical and Biological Engineering Conference (EMBEC), 2005.
Robert, A. L. G., G. Chagnon, I. Bricault, P. Cinquin, and A. Moreau-Gaudry. A generic three-dimensional static force distribution basis for a medical needle inserted into soft tissue. J. Mech. Behav. Biomed. Mater. 28:156–170, 2013.
Roesthuis, R. J., M. Kemp, J. J. van den Dobbelsteen, and S. Misra. Three-dimensional needle shape reconstruction using an array of fiber bragg grating sensors. IEEE/ASME Trans. Mechatron. 19:1115–1126, 2014.
Sadjadi, H., K. Hashtrudi-Zaad, and G. Fichtinger. Fusion of electromagnetic trackers to improve needle deflection estimation: simulation study. IEEE Trans. Biomed. Eng. 60:2706–2715, 2013. doi:10.1109/TBME.2013.2262658.
van Veen, Y. R. J., A. Jahya, and S. Misra. Macroscopic and microscopic observations of needle insertion into gels. Proc. Inst. Mech. Eng. [H] 226:441–449, 2012.
Vrooijink, G. J., M. Abayazid, S. Patil, R. Alterovitz, and S. Misra. Needle path planning and steering in a three-dimensional non-static environment using two-dimensional ultrasound images. Int. J. Robot. Res. 33:1361–1374, 2014.
Webster, III, R. J., J. S. Kim, N. J. Cowan, G. S. Chirikjian, and A. M. Okamura. Nonholonomic modeling of needle steering. Int. J. Robot. Res. 25:509–525, 2006.
Yaniv, Z., P. Cheng, E. Wilson, T. Popa, D. Lindisch, E. Campos-Nanez, H. Abeledo, V. Watson, K. Cleary, and F. Banovac. Needle-based interventions with the image-guided surgery toolkit (IGSTK): from phantoms to clinical trials. IEEE Trans. Biomed. Eng. 57:922–933, 2010.
Associate Editor Xiaoxiang Zheng oversaw the review of this article.
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Moreira, P., Misra, S. Biomechanics-Based Curvature Estimation for Ultrasound-guided Flexible Needle Steering in Biological Tissues. Ann Biomed Eng 43, 1716–1726 (2015). https://doi.org/10.1007/s10439-014-1203-5
- Minimally invasive surgery
- Needle steering
- Needle-tissue interaction model
- Flexible needle deflection
- Needle curvature estimation