Skip to main content
SpringerLink
Log in

Needle-tissue interactive mechanism and steering control in image-guided robot-assisted minimally invasive surgery: a review

  • Review Article
  • Published:
Medical & Biological Engineering & Computing Aims and scope Submit manuscript

Abstract

Image-guided robot-assisted minimally invasive surgery is an important medicine procedure used for biopsy or local target therapy. In order to reach the target region not accessible using traditional techniques, long and thin flexible needles are inserted into the soft tissue which has large deformation and nonlinear characteristics. However, the detection results and therapeutic effect are directly influenced by the targeting accuracy of needle steering. For this reason, the needle-tissue interactive mechanism, path planning, and steering control are investigated in this review by searching literatures in the last 10 years, which results in a comprehensive overview of the existing techniques with the main accomplishments, limitations, and recommendations. Through comprehensive analyses, surgical simulation for insertion into multi-layer inhomogeneous tissue is verified as a primary and propositional aspect to be explored, which accurately predicts the nonlinear needle deflection and tissue deformation. Investigation of the path planning of flexible needles is recommended to an anatomical or a deformable environment which has characteristics of the tissue deformation. Nonholonomic modeling combined with duty-cycled spinning for needle steering, which tracks the tip position in real time and compensates for the deviation error, is recommended as a future research focus in the steering control in anatomical and deformable environments.

a Insertion force when the needle is inserted into soft tissue. b Needle deflection model when the needle is inserted into soft tissue [68]. c Path planning in anatomical environments [92]. d Duty-cycled spinning incorporated in nonholonomic needle steering [64]

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
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Abayazid M, Moreira P, Shahriari N, Patil S, Alterovitz R, Misra S (2015) Ultrasound-guided three-dimensional needle steering in biological tissue with curved surfaces. Med Eng Phys 37:145–150

    Article  PubMed  Google Scholar 

  2. Abayazid M, Roesthuis RJ, Reilink R, Misra S (2013) Integrating deflection models and image feedback for real-time flexible needle steering. IEEE Trans Robot 29:542–553

    Article  Google Scholar 

  3. Abayazid M, Vrooijink GJ, Patil S, Alterovitz R, Misra S (2014) Experimental evaluation of ultrasound-guided 3D needle steering in biological tissue. Int J Comput Assist Radiol Surg 9:931–939

    Article  PubMed  PubMed Central  Google Scholar 

  4. Abolhassani N, Patel R, Moallem M (2007) Needle insertion into soft tissue: a survey. Med Eng Phys 29:413–431

    Article  PubMed  Google Scholar 

  5. Abolhassani N, Patel R (2006) Deflection of a flexible needle during insertion into soft tissue. Annual international conference of the IEEE engineering in medicine and biology society, pp 3858–3861

  6. Abolhassani N, Patel RV, Ayazi F (2007) Minimization of needle deflection in robot-assisted prostate brachytherapy. Int J Med Robot Comput Assist Surg 3:140–148

    Article  Google Scholar 

  7. Abolhassani N, Patel R, Moallem M (2006) Control of soft tissue deformation during robotic needle insertion. Minim Invasive Ther Allied Technol 15:165–176

    Article  PubMed  Google Scholar 

  8. Abolhassani N, Patel R, Moallem M (2004) Experimental study of robotic needle insertion in soft tissue. Int Congr 1268:797–802

    Article  Google Scholar 

  9. Abolmaesumi P, Salcudean SE, Zhu WH et al (2002) Image-guided control of a robot for medical ultrasound. IEEE Robot Autom Mag 18:11–23

    Article  Google Scholar 

  10. Adebar TK, Fletcher AE, Okamura AM (2014) 3-D ultrasound-guided robotic needle steering in biological tissue. IEEE Trans Biomed Eng 61:2899–2910

    Article  PubMed  PubMed Central  Google Scholar 

  11. Adebar TK, Greer JD, Laeseke PF, Hwang GL, Okamura AM (2016) Methods for improving the curvature of steerable needles in biological tissue. IEEE Trans Biomed Eng 63:1167–1177

    Article  PubMed  Google Scholar 

  12. Adhami L, Coste-Manière È (2003) Optimal planning for minimally invasive surgical robots. IEEE Robot Autom Mag 19:854–863

    Article  Google Scholar 

  13. Ahn B, Kim J (2009) Efficient soft tissue characterization under large deformations in medical simulations. Int J Precis Eng Manuf 10:115–121

    Article  Google Scholar 

  14. Alterovitz R, Branicky M, Goldberg K (2008) Motion planning under uncertainty for image-guided medical needle steering. Int J Robot Res 27:1361–1374

    Article  Google Scholar 

  15. Alterovitz R, Lim A, Goldberg K et al (2005) Steering flexible needles under Markov motion uncertainty. IEEE/RSJ International conference on intelligent robots and systems, pp 1570–1575

  16. Alterovitz R, Goldberg K, Okamura A (2005) Planning for steerable bevel-tip needle insertion through 2D soft tissue with obstacles. IEEE International conference on robotics and automation, pp 1640–1645

  17. Asadian A, Kermani MR, Patel RV (2012) A novel force modeling scheme for needle insertion using multiple Kalman filters. IEEE Trans Instrum Meas 61:429–438

    Article  Google Scholar 

  18. Asadian A, Kermani MR, Patel RV (2010) A compact dynamic force model for needle-tissue interaction. Annual international conference of the IEEE engineering in medicine and biology society, pp 2292–2295

  19. Azar T, Hayward V (2008) Estimation of the fracture toughness of soft tissue from needle insertion. International Symposium on Biomedical Simulation, pp 166–175

  20. Barbe L, Bayle B, Mathelin MD, Gangi A (2007) Needle insertions modeling: identifiability and limitations. Biomed Signal Process Control 2:191–198

    Article  Google Scholar 

  21. Basafa E, Farahmand F (2011) Real-time simulation of the nonlinear visco-elastic deformations of soft tissues. Int J Comput Assist Radiol Surg 6:297–307

    Article  PubMed  Google Scholar 

  22. Bax JS, Waring CS, Sherebrin S et al (2013) 3D image-guided robotic needle positioning system for small animal interventions. Med Phys 40:113–132

    Article  Google Scholar 

  23. Bax J, Smith D, Bartha L, Montreuil J, Sherebrin S, Gardi L, Edirisinghe C, Fenster A (2011) A compact mechatronic system for 3D ultrasound guided prostate interventions. Med Phys 38:1055–1069

    Article  PubMed  Google Scholar 

  24. Bernardes MC, Adorno BV, Poignet P, Borges GA (2013) Robot-assisted automatic insertion of steerable needles with closed-loop imaging feedback and intraoperative trajectory replanning. Mechatronics 23:630–645

    Article  Google Scholar 

  25. Bickel B, Bächer M, Otaduy MA, Matusik W, Pfister H, Gross M (2009) Capture and modeling of non-linear heterogeneous soft tissue. ACM Trans Graph 28:341–352

    Article  Google Scholar 

  26. Biot MA (1937) Bending of an infinite beam on an elastic foundation. J Appl Mech 59:A1–A7

    Google Scholar 

  27. Butz KD, Griebel AJ, Novak T, Harris K, Kornokovich A, Chiappetta MF, Neu CP (2012) Prestress as an optimal biomechanical parameter for needle penetration. J Biomech 45:1176–1179

    Article  PubMed  Google Scholar 

  28. Cadiere GB, Himpens J, Germay O et al (2001) Feasibility of robotic laparoscopic surgery: 146 cases. World J Surg 25:1467–1477

    PubMed  CAS  Google Scholar 

  29. Carra A, Avila-Vilchis JC (2010) Needle insertion modeling through several tissue layers. International Asia Conference on Informatics in Control, Automation and Robotics, pp 237–240

  30. Chae Y, Um SI, Yi SH, Lee H, Chang DS, Yin CS, Park HJ (2011) Comparison of biomechanical properties between acupuncture and non-penetrating sham needle. Complement Ther Med 19:S8–S12

    Article  PubMed  Google Scholar 

  31. Chentanez N, Alterovitz R, Ritchie D et al (2009) Interactive simulation of surgical needle insertion and steering. ACM Trans Graph 28:88(1)–88(10)

    Article  Google Scholar 

  32. Cleary K, Peters TM (2010) Image-guided interventions: technology review and clinical applications. Annu Rev Biomed Eng 12:119–142

    Article  PubMed  CAS  Google Scholar 

  33. Cowan NJ, Goldberg K, Chirikjian GS, Fichtinger G, Alterovitz R, Reed KB, Kallem V, Park W, Misra S, Okamura AM (2011) Robotic needle steering: design, modeling, planning, and image guidance. In: Rosen J, Hannaford B, Satava RM (eds) Surgical robotics. Springer US, New York, pp 557–582

    Chapter  Google Scholar 

  34. Dehghan E, Salcudean SE (2009) Needle insertion parameter optimization for brachytherapy. IEEE Trans Robot 25:303–315

    Article  Google Scholar 

  35. Dehghan E, Salcudean SE (2007) Needle insertion point and orientation optimization in non-linear tissue with application to brachytherapy. IEEE International conference on robotics and automation, pp 2267–2272

  36. Dimaio SP, Salcudean SE (2005) Interactive simulation of needle insertion models. IEEE Trans Biomed Eng 52:1167–1179

    Article  PubMed  Google Scholar 

  37. Dimaio SP, Salcudean SE (2005) Needle steering and motion planning in soft tissues. IEEE Trans Biomed Eng 52:965–974

    Article  PubMed  Google Scholar 

  38. Dimaio SP, Salcudean SE (2003) Needle insertion modeling and simulation. IEEE Robot Autom Mag 19:864–875

    Article  Google Scholar 

  39. Duindam V, Xu JJ, Alterovitz R, Sastry S, Goldberg K (2009) 3D motion planning algorithms for steerable needles using inverse kinematics. Int J Robot Res 57:535–549

    Google Scholar 

  40. Duindam V, Alterovitz R, Sastry S et al (2008) Screw-based motion planning for bevel-tip flexible needles in 3D environments with obstacles. IEEE International Conference on Robotics and Automation, pp 2483–2488

  41. Engh JA, Podnar G, Kondziolka D et al (2006) Toward effective needle steering in brain tissue. Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp 559–562

  42. Fisher T, Hamed A, Vartholomeos P, Masamune K, Tang G, Ren H, Tse ZTH (2014) Intraoperative magnetic resonance imaging-conditional robotic devices for therapy and diagnosis. Proc Inst Mech Eng Part H-J Eng Med 228:303–318

    Article  Google Scholar 

  43. Gao DD, Lei Y, Zheng HJ (2012) Needle steering for robot-assisted insertion into soft tissue: a survey. Chin J Mech Eng 25:629–638

    Article  Google Scholar 

  44. Glozman D, Shoham M (2007) Image-guided robotic flexible needle steering. IEEE Trans Robot 23:459–467

    Article  Google Scholar 

  45. Gokgol C, Basdogan C, Canadinc D (2012) Estimation of fracture toughness of liver tissue: experiments and validation. Med Eng Phys 34:882–891

    Article  PubMed  Google Scholar 

  46. Goksel O, Dehghan E, Salcudean SE (2009) Modeling and simulation of flexible needles. Med Eng Phys 31:1069–1078

    Article  PubMed  Google Scholar 

  47. Groves RB, Coulman SA, Birchall JC, Evans SL (2012) Quantifying the mechanical properties of human skin to optimize future microneedle device design. Comput Methods Biomech Biomed Eng 15:73–82

    Article  CAS  Google Scholar 

  48. Haddadi A, Hashtrudizaad K (2011) Development of a dynamic model for bevel-tip flexible needle insertion into soft tissues. Annual international conference of the IEEE engineering in medicine and biology society, pp 7478–7482

  49. Jahya A, Van Der Heijden F, Misra S (2012) Observations of three-dimensional needle deflection during insertion into soft tissue. IEEE International conference on biomedical robotics and biomechatronics, pp 1205–1210

  50. Jee T, Komvopoulos K (2014) Skin viscoelasticity studied in vitro by microprobe-based techniques. J Biomech 47:553–559

    Article  PubMed  CAS  Google Scholar 

  51. Jiang S, Li P, Yu Y, Liu J, Yang ZY (2014) Experimental study of needle-tissue interaction forces: effect of needle geometries, insertion methods and tissue characteristics. J Biomech 47:3344–3353

    Article  PubMed  Google Scholar 

  52. Jiang S, Liu XY, Bai S, Yang Z (2010) The potential field-based trajectory planning of needle invasion in soft tissue. J Biomed Eng 27:790–794

    Google Scholar 

  53. Jiang S, Liu S, Feng WH (2011) PVA hydrogels properties for biomedical application. J Mech Behav Biomed Mater 4:1228–1233

    Article  PubMed  CAS  Google Scholar 

  54. Kataoka H, Washio T, Audette M et al (2001) A model for relations between needle deflection, force, and thickness on needle penetration. Proc Med Image Comput Comput Assist Interv 2208:966–974

    Google Scholar 

  55. Kim S, Chung J, Yi BJ, Kim YS (2010) An assistive image-guided surgical robot system using O-arm fluoroscopy for pedicle screw insertion: preliminary and cadaveric study. Neurosurgery 67:1757–1767

    Article  PubMed  Google Scholar 

  56. Kobayashi Y, Hamano R, Watanabe H, Hong J, Toyoda K, Hashizume M, Fujie MG (2013) Use of puncture force measurement to investigate the conditions of blood vessel needle insertion. Med Eng Phys 35:684–689

    Article  PubMed  Google Scholar 

  57. Lehmann T, Tavakoli M, Usmani N, Sloboda R (2013) Force-sensor-based estimation of needle tip deflection in brachytherapy. J Sens 2013:1–10. https://doi.org/10.1155/2013/263153

    Article  Google Scholar 

  58. Leyendeeker JR, Dodd GD (2001) Minimally invasive techniques for the treatment of liver tumors. Semin Liver Dis 21:283–291

    Article  Google Scholar 

  59. Li P, Jiang S, Liang D, Yang ZY, Yu Y, Wang W (2017) Modeling of path planning and needle steering with path tracking in anatomical soft tissues for minimally invasive surgery. Med Eng Phys 41:35–45

    Article  PubMed  Google Scholar 

  60. Li P, Jiang S, Yang J et al (2014) A combination method of artificial potential field and improved conjugate gradient for trajectory planning for needle insertion into soft tissue. J Med Biol Eng 34:568–573

    Article  Google Scholar 

  61. Li P, Jiang S, Yu Y, Yang J, Yang Z (2015) Biomaterial characteristics and application of silicone rubber and PVA hydrogels mimicked in organ groups for prostate brachytherapy. J Mech Behav Biomed Mater 49:220–234

    Article  PubMed  CAS  Google Scholar 

  62. Mahvash M, Dupont PE (2010) Mechanics of dynamic needle insertion into a biological material. IEEE Trans Biomed Eng 57:934–943

    Article  PubMed  Google Scholar 

  63. Majewicz A, Marra SP, Van Vledder MG et al (2012) Behavior of tip-steerable needles in ex vivo and in vivo tissue. IEEE Trans Biomed Eng 59:2705–2715

    Article  PubMed  PubMed Central  Google Scholar 

  64. Majewicz A, Siegel JJ, Stanley AA et al (2014) Design and evaluation of duty-cycling steering algorithms for robotically-driven steerable needles. IEEE International conference on robotics and automation, pp 5883–5888

  65. Maurin B, Barbe L, Bayle B et al (2004) In vivo study of forces during needle insertions. Scientific Workshop on Medical Robotics Navigation and Visualization, pp 14–21

  66. Minhas D, Engh JA, Riviere CN (2009) Testing of neurosurgical needle steering via duty-cycled spinning in brain tissue in vitro. Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp 258–261

  67. Minhas DS, Engh JA, Fenske MM (2007) Modeling of needle steering via duty-cycled spinning. Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp 2756–2759

  68. Misra S, Reed KB, Schafer BW, Ramesh KT, Okamura AM (2010) Mechanics of flexible needles robotically steered through soft tissue. Int J Robot Res 29:1640–1660

    Article  CAS  Google Scholar 

  69. Misra S, Reed KB, Schafer BW et al (2009) Observations and models for needle-tissue interactions. IEEE International Conference on Robotics and Automation, pp 2687–2692

  70. Misra S, Macura KJ, Ramesh KT, Okamura AM (2009) The importance of organ geometry and boundary constraints for planning of medical interventions. Med Eng Phys 31:195–206

    Article  PubMed  CAS  Google Scholar 

  71. Misra S, Ramesh KT, Okamura AM (2008) Modeling of tool-tissue interactions for computer-based surgical simulation: a literature review. Presence Teleop Virt Environ 17:463–491

    Article  Google Scholar 

  72. Misra S, Reed KB, Douglas AS et al (2008) Needle-tissue interaction forces for bevel-tip steerable needles. IEEE International Conference on Biomedical Robotics and Biomechatronics, pp 224–231

  73. Mousavi SR, Khalaji I, Naini AS et al (2012) Statistical finite element method for real-time tissue mechanics analysis. Comput Methods Biomech Biomed Eng 15:595–608

    Article  Google Scholar 

  74. Neubach Z, Shoham M (2010) Ultrasound-guided robot for flexible needle steering. IEEE Trans Biomed Eng 57:799–805

    Article  PubMed  Google Scholar 

  75. Okamura AM, Simone C, O'Leary MD (2004) Force modeling for needle insertion into soft tissue. IEEE Trans Biomed Eng 51:1707–1716

    Article  PubMed  Google Scholar 

  76. Oldfield MJ, Dini D, Jaiswal T, Baena FRY (2013) The significance of rate dependency in blade insertions into a gelatin soft tissue phantom. Tribol Int 63:226–234

    Article  CAS  Google Scholar 

  77. Park YL, Elayaperumal S, Daniel B, Ryu SC, Shin M, Savall J, Black RJ, Moslehi B, Cutkosky MR (2010) Real-time estimation of 3-D needle shape and deflection for MRI-guided interventions. IEEE-ASME Trans Mechatron 15:906–915

    PubMed  PubMed Central  Google Scholar 

  78. Park W, Kim JS, Zhou Y et al (2005) Diffusion-based motion planning for a nonholonomic flexible needle model. IEEE International Conference on Robotics and Automation, pp 4600–4605

  79. Patil S, Burgner J, Webster RJ, Alterovitz R (2014) Needle steering in 3-D via rapid replanning. IEEE Trans Robot 30:853–864

    Article  PubMed  PubMed Central  Google Scholar 

  80. Patil S, Alterovitz R (2010) Interactive motion planning for steerable needles in 3D environments with obstacles. IEEE International Conference on Biomedical Robotics and Biomechatronics, pp 893–899

  81. Podder TK, Sherman J, Clark DP et al (2005) Evaluation of robotic needle insertion in conjunction with in vivo manual insertion in the operating room. IEEE International Workshop on Robot and Human Interactive Communication, pp 66–72

  82. Qin XF (2015) Deep insertion of long slender needle into deformable tissue and the application for prostate brachytherapy. North Carolina State University, Raleigh

    Google Scholar 

  83. Qin J, Pang WM, Chui YP, Wong TT, Heng PA (2010) A novel modeling framework for multilayered soft tissue deformation in virtual orthopedic surgery. J Med Syst 34:261–271

    Article  PubMed  Google Scholar 

  84. Reed KB, Majewicz A, Kallem V, Alterovitz R, Goldberg K, Cowan N, Okamura A (2011) Robot-assisted needle steering. IEEE Robot Autom Mag 18:35–46

    Article  PubMed  PubMed Central  Google Scholar 

  85. Roesthuis RJ, Kemp M, Van Den Dobbelsteen JJ et al (2014) Three-dimensional needle shape reconstruction using an array of fiber bragg grating sensors. IEEE-ASME Trans Mechatron 19:1115–1126

    Article  Google Scholar 

  86. Roesthuis RJ, Abayazid M, Misra S (2012) Mechanics-based model for predicting in-plane needle deflection with multiple bends. IEEE International Conference on Biomedical Robotics and Biomechatronics, pp 69–74

  87. Roesthuis RJ, Van Veen YRJ, Jahya A et al (2011) Mechanics of needle-tissue interaction. IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 2557–2563

  88. Seitel A, Engel M, Sommer CM, Radeleff BA, Essert-Villard C, Baegert C, Fangerau M, Fritzsche KH, Yung K, Meinzer HP, Maier-Hein L (2011) Computer-assisted trajectory planning for percutaneous needle insertions. Med Phys 38:3246–3259

    Article  PubMed  Google Scholar 

  89. Sergi PN, Jensen W, Micera S, Yoshida K (2012) In vivo interactions between tungsten microneedles and peripheral nerves. Med Eng Phys 34:747–755

    Article  PubMed  Google Scholar 

  90. Siegel RL, Miller KD, Jemal A (2016) Cancer statistics, 2016. CA-Cancer J Clin 66:10–29

    Article  Google Scholar 

  91. Simone C, Okamura AM (2003) Modeling of needle insertion forces for robot-assisted percutaneous therapy. IEEE International Conference on Robotics and Automation, pp 2085–2091

  92. Sun W, Alterovitz R (2014) Motion planning under uncertainty for medical needle steering using optimization in belief space. IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 1775–1781

  93. Swaney PJ, Burgner J, Gilbert HB, Webster RJ (2013) A flexure-based steerable needle: high curvature with reduced tissue damage. IEEE Trans Biomed Eng 60:906–909

    Article  PubMed  Google Scholar 

  94. Van Den Berg NJ, Van Gerwen DJ, Dankelman J, Van Den Dobbelsteen JJ (2014) Design choices in needle steering—a review. IEEE-ASME Trans Mechatron 20:2172–2183

    Article  Google Scholar 

  95. Van Gerwen DJ, Dankelman J, Van Den Dobbelsteen JJ (2012) Needle-tissue interaction forces—a survey of experimental data. Med Eng Phys 34:665–680

    Article  PubMed  Google Scholar 

  96. Van Veen YR, Jahya A, Misra S (2012) Macroscopic and microscopic observations of needle insertion into gels. Proc Inst Mech Eng Part H-J Eng Med 226:441–449

    Article  Google Scholar 

  97. Vrooijink GJ, Abayazid M, Patil S, Alterovitz R, Misra S (2014) Needle path planning and steering in a three-dimensional non-static environment using two-dimensional ultrasound images. Int J Robot Res 33:1361–1374

    Article  Google Scholar 

  98. Wang JJ, Li XP, Zheng JJ, Sun D (2014) Dynamic path planning for inserting a steerable needle into a soft tissue. IEEE-ASME Trans Mechatron 19:549–558

    Article  Google Scholar 

  99. Webster RJ, Jones BA (2010) Design and kinematic modeling of constant curvature continuum robots: a review. Int J Robot Res 29:1661–1683

    Article  Google Scholar 

  100. Webster RJ, Kim JS, Cowan NJ et al (2006) Nonholonomic modeling of needle steering. Int J Robot Res 25:509–525

    Article  Google Scholar 

  101. Wood NA, Shahrour K, Ost MC, Riviere CN (2010) Needle steering system using duty-cycled rotation for percutaneous kidney access. Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp 5432–5435

  102. Wood NA, Lehocky CA, Riviere CN (2013) Algorithm for three-dimensional control of needle steering via duty-cycled rotation. IEEE International Conference on Mechatronics, pp 237–241

  103. Xie Y, Sun D, Tse HYG, Liu C, Cheng SH (2011) Force sensing and manipulation strategy in robot-assisted microinjection on zebrafish embryos. IEEE-ASME Trans Mechatron 16:1002–1010

    Article  Google Scholar 

  104. Xie Y, Sun D, Liu C et al (2009) A force control approach to a robot-assisted cell microinjection system. Int J Robot Res 29:1222–1232

    Article  Google Scholar 

  105. Xu J, Duindam V, Alterovitz R et al (2009) Planning fireworks trajectories for steerable medical needles to reduce patient trauma. IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 4517–4522

  106. Yamaguchi S, Tsutsui K, Satake K, Morikawa S, Shirai Y, Tanaka HT (2014) Dynamic analysis of a needle insertion for soft materials: arbitrary Lagrangian-Eulerian-based three-dimensional finite element analysis. Comput Biol Med 53:42–47

    Article  PubMed  Google Scholar 

  107. Yan K, Podder T, Li L, Joseph J, Rubens DR, Messing EM, Liao L, Yu Y (2009) A real-time prostate cancer detection technique using needle insertion force and patient-specific criteria during percutaneous intervention. Med Phys 36:3356–3362

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  108. Yoshida K, Lewinsky I, Nielsen M, Hylleberg M (2007) Implantation mechanics of tungsten microneedles into peripheral nerve trunks. Med Biol Eng Comput 45:413–420

    Article  PubMed  Google Scholar 

  109. Zhang YD, Zhao YJ, Tu F et al (2011) A review on path planning of flexible needle. J Harbin Univ Sci Technol 16:7–11

    CAS  Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge the financial support from the National Natural Science Foundation of the People’s Republic of China (No. 51775368), Key Technology and Development Program of Tianjin Municipal Science and Technology Commission (No. 14ZCDZGX00490).

Author information

Authors and Affiliations

  1. Centre for Advanced Mechanisms and Robotics, School of Mechanical Engineering, Tianjin University, No. 135, Yaguan Road, Jinnan District, Tianjin City, 300354, China

    Pan Li, Zhiyong Yang & Shan Jiang

Authors
  1. Pan Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhiyong Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shan Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shan Jiang.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

For this type of study, formal consent is not required.

Electronic supplementary material

ESM 1

(DOCX 64 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, P., Yang, Z. & Jiang, S. Needle-tissue interactive mechanism and steering control in image-guided robot-assisted minimally invasive surgery: a review. Med Biol Eng Comput 56, 931–949 (2018). https://doi.org/10.1007/s11517-018-1825-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11517-018-1825-0

Keywords

Search

Navigation