Skip to main content

Advertisement

SpringerLink
Log in

Simulation and experimental studies in needle–tissue interactions

  • Original Research
  • Published:
Journal of Clinical Monitoring and Computing Aims and scope Submit manuscript

Abstract

This work aims to introduce a new needle insertion simulation to predict the deflection of a bevel-tip needle inside soft tissue. The development of such a model, which predicts the steering behavior of the needle during needle-tissue interactions, could improve the performance of many percutaneous needle-based procedures such as brachytherapy and thermal ablation, by means of the virtual path planning and training systems of the needle toward the target and thus reducing possible incidents of complications in clinical practices. The Arbitrary–Lagrangian–Eulerian (ALE) formulation in LS-DYNA software was used to model the solid–fluid interactions between the needle and tissue. Since both large deformation and fracture of the continuum need to be considered in this model, applying ALE method for fluid analysis was considered a suitable approach. A 150 mm long needle was used to bend within the tissue due to the interacting forces on its asymmetric bevel tip. Three experimental cases of needle steering in a soft phantom were performed to validate the simulation. An error measurement of less than 10 % was found between the predicted deflection by the simulations and the one observed in experiments, validating our approach with reasonable accuracy. The effect of the needle diameter and its bevel tip angle on the final shape of the needle was investigated using this model. To maneuver around the anatomical obstacles of the human body and reach the target location, thin sharp needles are recommended, as they would create a smaller radius of curvature. The insertion model presented in this work is intended to be used as a base structure for path planning and training purposes for future studies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Podder TK, Dicker AP, Hutapea P, Yu Y. A novel curvilinear approach for prostate seed implantation. J Med Phys. 2012;39:1887–92. doi:10.1118/1.3694110.

    Article  Google Scholar 

  2. Engh JA, Podnar G, Kondziolka D, Riviere CN. Toward effective needle steering in brain tissue. In: IEEE EMBS 28th annual international conference, New York City, NY; 2006, p. 559–62

  3. Crouch JR, Schneider CM, Wainer J, Okamura AM. A velocity-dependent model for needle insertion in soft tissue. Med Image Comput Comput Assist Interv. 2005;8:624–32. doi:10.1007/11566489_77.

    PubMed  Google Scholar 

  4. Reed BKB, Majewicz A, Kallem V, Alterovitz R, Goldberg K, Cowan NJ, Okamura AM. Robot-assisted needle steering. IEEE Robot Autom Mag. 2011;18:35–46. doi:10.1109/MRA.2011.942997.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Webster RJ, Romano JM, Member S, Cowan NJ. Mechanics of precurved-tube continuum robots. Robot IEEE Trans. 2009;25:67–78. doi:10.1109/TRO.2008.2006868.

    Article  Google Scholar 

  6. Wedlick TR, Okamura AM. Characterization of pre-curved needles for steering in tissue. Annu Int Conf IEEE Eng Med Biol Soc. 2009;. doi:10.1109/IEMBS.2009.5333407.

    Google Scholar 

  7. Swaney PJ, Burgner J, Gilbert HB, WebsterIII RJ. A flexure-based steerable needle: high curvature with reduced tissue damage. IEEE Trans Biomed Eng. 2013;60:906–9. doi:10.1109/TBME.2012.2230001.

    Article  PubMed  Google Scholar 

  8. Datla NV, Konh B, Koo J, Daniel WC, Yu Y, Dicker AP, Podder TK, Darvish K, Hutapea P. Polyacrylamide phantom for self-actuating needle–tissue interaction studies. Med Eng Phys. 2014;36:140–5. doi:10.1016/j.medengphy.2013.07.004.

    Article  PubMed  Google Scholar 

  9. Datla NV, Konh B, Honarvar M, Podder TK, Dicker AP, Yu Y, Hutapea P. A model to predict deflection of bevel-tipped active needle advancing in soft tissue. Med Eng Phys. 2013;36:258–93. doi:10.1016/j.medengphy.2013.11.006.

    Google Scholar 

  10. Konh B, Datla NV, Hutapea P. Feasibility of SMA wire actuation for an active steerable cannula. J Med Device. 2014;10(1115/1):4029557. doi:10.1115/1.4029557.

    Google Scholar 

  11. Honarvar M, Datla NV, Konh B, Podder TK, Dicker AP, Yu Y, Hutapea P. Study of unrecovered strain and critical stresses in one-way shape memory Nitinol. Mater Eng Perform. 2014;23:2885–93. doi:10.1007/s11665-014-1077-6.

    Article  CAS  Google Scholar 

  12. Konh B, Honarvar M, Hutapea P. Design optimization study of a shape memory alloy active needle for biomedical applications. J Med Eng Phys. 2015;37:469–77. doi:10.1016/j.medengphy.2015.02.013.

    Article  Google Scholar 

  13. Ryu SC, Quek ZF, Koh JS, Renaud P, Black RJ, Moslehi B, Daniel BL, Cho KJ, Cutkosky MR. Design of an optically controlled MR-compatible active needle. IEEE Trans Robot. 2015;31:1–11. doi:10.1109/TRO.2014.2367351.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Ayvali E, Desai JP. Pulse width modulation-based temperature tracking for feedback control of a shape memory alloy actuator. J Intell Mater Syst Struct. 2014;25:720–30. doi:10.1177/1045389X13502576.

    Article  PubMed  Google Scholar 

  15. van de Berg NJ, van Gerwen DJ, Dankelman J, van den Dobbelsteen JJ. Design choices in needle steering—a review. Mechatron IEEE/ASME Trans. 2015;20:2172–83. doi:10.1109/TMECH.2014.2365999.

    Article  Google Scholar 

  16. Abolhassani N, Patel R, Moallem M. Needle insertion into soft tissue: a survey. Med Eng Phys. 2007;29:413–31. doi:10.1016/j.medengphy.2006.07.003.

    Article  PubMed  Google Scholar 

  17. van Gerwen DJ, Dankelman J, van den Dobbelsteen JJ. Needle–tissue interaction forces—a survey of experimental data. Med Eng Phys. 2012;34:665–80. doi:10.1016/j.medengphy.2012.04.007.

    Article  PubMed  Google Scholar 

  18. Alterovitz R, Goldhere K, Berkeley UC. Needle insertion and radioactive seed implantation in human tissues: simulation and sensitivity analysis’. In: Robot Autom 2003 Proceedings ICRA’03 IEEE Int Conf 2003; 2:1793–9. doi:10.1109/ROBOT.2003.1241854.

  19. DiMaio SP, Salcudean SE. Interactive simulation of needle insertion models. IEEE Trans Biomed Eng. 2005;52:1167–79. doi:10.1109/TBME.2005.847548.

    Article  PubMed  Google Scholar 

  20. Nienhuys H-W, van der Stappen AF. A computational technique for interactive needle insertions in 3D nonlinear material. In: Robot autom 2004 proceedings ICRA’04 2004 IEEE int conf 2004; 2:2061–67. doi:10.1109/ROBOT.2004.1308127.

  21. Misra S, Reed KB, Schafer BW, Ramesh KT, Okamura AM. Mechanics of flexible needles robotically steered through soft tissue. Int J Rob Res. 2010;29:1640–60. doi:10.1177/0278364910369714.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Okamura AM, Simone C, O’Leary M. Force modeling for needle insertion into soft tissue. Biomed Eng IEEE Trans. 2004;51:1707–16. doi:10.1109/TBME.2004.831542.

    Article  Google Scholar 

  23. Roesthuis RJ, Abayazid M, Misra S. Mechanics-based model for predicting in-plane needle deflection with multiple bends. In: 2012 4th IEEE RAS EMBS int conf biomed robot biomechatronics 2004; p. 69–74. doi:10.1109/BioRob.2012.6290829.

  24. Webster RJ. Nonholonomic modeling of needle steering. Int J Rob Res. 2006;25:509–25. doi:10.1177/0278364906065388.

    Article  Google Scholar 

  25. Kataoka H, Washio T, Audette M, Mizuhara K. A model for relations between needle deflection, force, and thickness on needle penetration. Med image Comput Comput Interv. 2001;. doi:10.1007/3-540-45468-3_115.

    Google Scholar 

  26. Abolhassani N, Patel R. Deflection of a flexible needle during insertion into soft tissue. In: Eng Med Biol Soc 2006 EMBS’06 28th Annu Int Conf IEEE 2006; p. 3858–61.

  27. Podder TK, Clark D, Sherman J, Fuller D, Messing E, Rubens D, Strang J, Brasacchio L, Liao WSN, Yu Y. In Vivo motion and force measurement of surgical needle intervention during prostate brachytherapy. J Med Phys. 2006;33:2915–22.

    Article  Google Scholar 

  28. Majewicz A, Wedlick TR, Reed KB, Okamura AM. Evaluation of robotic needle steering in ex vivo tissue. IEEE Int Conf Robot Autom. 2010;2010:2068–73. doi:10.1109/ROBOT.2010.5509873.

    PubMed  PubMed Central  Google Scholar 

  29. Oldfield M, Dini D, Giordano G, Rodriguez y Baena F. Detailed finite element modelling of deep needle insertions into a soft tissue phantom using a cohesive approach. Comput Methods Biomech Biomed Eng. 2013;16:530–43. doi:10.1080/10255842.2011.628448.

    Article  Google Scholar 

  30. Kataoka H, Noda S, Yokota H, Takagi S, Himeno R, Okazawa S. Simulations of needle insertion by using a Eulerian hydrocode FEM and the experimental validations. Med Image Comput Comput Interv. 2008;. doi:10.1007/978-3-540-85990-1-67.

    Google Scholar 

  31. Yamaguchi S, Tsutsui K, Satake K, Morikawa S, Shirai Y, Tanaka HT. Dynamic analysis of a needle insertion for soft materials: arbitrary Lagrangian–Eulerian-based three-dimensional finite element analysis. Comput Biol Med. 2014;53:42–7. doi:10.1016/j.compbiomed.2014.07.012.

    Article  PubMed  Google Scholar 

  32. Hirt CW, Amsden AA, Cook JL. An arbitrary Lagrangian–Eulerian computing method for all flow speeds. J Comput Phys. 1974;14:227–53. doi:10.1016/0021-9991(74)90051-5.

    Article  Google Scholar 

  33. LSTC. LS-DYNA Theory Manual Version 970. r:6030. Livernire Software Technology Corporation (LSTC), Livermore, CA.

  34. Ahn BM, Kim J, Ian L, Rha KH, Kim HJ. Mechanical property characterization of prostate cancer using a minimally motorized indenter in an ex vivo indentation experiment. Urology. 2010;76:1007–11. doi:10.1016/j.urology.2010.02.025.

    Article  PubMed  Google Scholar 

  35. Shergold OA, Fleck NA. Experimental investigation into the deep penetration of soft solids by sharp and blunt punches, with application to the piercing of skin. J Biomech Eng. 2005;127:838–48. doi:10.1115/1.1992528.

    Article  PubMed  Google Scholar 

  36. Oliver WC, Pharr GM. An improved technique for determining hardness and elastic modulus using load and displacement sensing indentation experiments. J Mater Res. 1992;7:1564–83. doi:10.1557/JMR.1992.1564.

    Article  CAS  Google Scholar 

  37. Hertz HR. On the contact of rigid elastic solids and on hardness. New York, NY: McMillan; 1882.

    Google Scholar 

Download references

Acknowledgments

This study was funded by the Department of Defense CDMRP Prostate Cancer Research Program (Grant # W81XWH-11-1-0398).

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Temple University, 1947 N. 12th Street, Philadelphia, PA, 19122, USA

    Bardia Konh, Mohammad Honarvar, Kurosh Darvish & Parsaoran Hutapea

  2. Department of Mechanical Engineering, University of Hawaii at Manoa, Honolulu, HI, 96822, USA

    Bardia Konh

Authors
  1. Bardia Konh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohammad Honarvar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kurosh Darvish
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Parsaoran Hutapea
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Parsaoran Hutapea.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Konh, B., Honarvar, M., Darvish, K. et al. Simulation and experimental studies in needle–tissue interactions. J Clin Monit Comput 31, 861–872 (2017). https://doi.org/10.1007/s10877-016-9909-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10877-016-9909-6

Keywords

Search

Navigation