Needle-Tissue Interaction and Deflection Modeling of Flexible Needle Insertion in Soft Tissue
A. Asadian1,2, R.V. Patel1,2,3, and M. Kermani1
1 Department of Electrical and Computer Engineering, University of Western Ontario, Canada
2 Canadian Surgical Technologies & Advanced Robotics (CSTAR), London, Ontario, Canada
3 Department of Surgery, University of Western Ontario, Canada
Abstract
The reliability of needle insertion in robot-assisted percutaneous therapies can be enhanced if accurate models are available for needle-tissue interaction. The use of a long flexible needle requires modeling of the generated curved trajectory when the needle is inserted into soft tissue. Finding a feasible model is important in surgical simulators for use in training novice clinicians or in path planning for needle guidance.
We have developed a needle deflection model using beam theory and a Green's-function approach. To this end, the tissue resistive force is modeled by adding virtual lateral springs along the needle shaft. The effective cutting force at the tip is included by introducing its resultant sub-boundary conditions to the partial differential equations. The impact of friction is also considered by incorporating a moving distributed force in the beam segments. In needle insertion, when the needle is very flexible, translational friction plays a key role in needle flexing. In order to characterize frictional effects, a distributed version of the LuGre model has been adopted. However, tissue deformation, which is a complex and inevitable phenomenon, has to be taken into account to correct the friction-velocity cycle. We have shown that a high-gain observer can approximately compensate or the axial velocity of the tissue with respect to the moving needle.
To get an insight into the mechanism of needle insertion, we have
separately investigated needle-tissue interactions. While the nature
of this problem is complex, the use of multiple Kalman filters
provides an adaptable means for capturing the force evolution. In
this study, the axial force is modeled using a nonlinear dynamic
structure that includes puncture, cutting, and friction forces.
Sequential extended Kalman filtering is also employed for estimation
in a mathematically efficient manner. To evaluate the performance of
the modeling schemes, experiments were conducted on artificial
phantoms and animal tissue.
Related Publications
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Ali Asadian, Mehrdad R. Kermani, and Rajni V. Patel, "A Novel Force Modeling Scheme for Needle Insertion using Multiple Kalman Filters," IEEE Transactions on Instrumentation and Measurement, vol. 61, no. 2, 2012, pp. 429-438.
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Ali Asadian, Mehrdad R. Kermani, and Rajni V. Patel, "An Analytical Model for Deflection of Flexible Needles During Needle Insertion," IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), pp. 2551-2556, USA, Sep. 2011.
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Ali Asadian, Rajni V. Patel, and Mehrdad R. Kermani, "A Distributed Model for Needle-Tissue Friction in Percutaneous Interventions," IEEE Int. Conf. on Robotics and Automation (ICRA), pp. 1896-1901, China, May 2011.
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Ali Asadian, Mehrdad R. Kermani, and Rajni V. Patel, "Robot-Assisted Needle Steering Using a Control Theoretic Approach," Journal of Intelligent and Robotic Systems (Springer Verlag), vol. 62, no. 3-4, 2011, pp. 397-418.
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Ali Asadian, Mehrdad R. Kermani, and Rajni V. Patel, "A Compact Dynamic Force Model for Tissue-Needle Interaction," 32nd Annual Int. Conf. of IEEE Engineering in Medicine and Biology Society (EMBS), pp. 2292-2295, Argentina, Aug. 2010.
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Ali Asadian, Mehrdad R. Kermani, and Rajni V. Patel, "Accelerated Needle Steering Using the Partitioned Value Iteration," IEEE American Control Conf. (ACC), pp. 2785-2790, USA, Jun. 2010.
Links
http://www.eng.uwo.ca/people/rpatel/Research/NeedleSteering/Needle.html