A Two-Body Rigid/Flexible Model of Needle Steering Dynamics in Soft Tissue

Khadem, Mohsen; Rossa, Carlos; Usmani, Nawaid; Sloboda, Ron S.; Tavakoli, Mahdi

doi:10.1109/tmech.2016.2549505

Cited by 61 publications

(23 citation statements)

References 24 publications

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“…Then, the geometric phase of the parametrized family is determined by (8). Solving (8) for (φ * , θ * ), one can calculate the desired path in the base that will produce the desired geometric phase (0, y d , z d ). Solution of (8) and the corresponding selected closed path is given in the second row of Table. 1.…”

Section: Step 2: Stabilization To a Pointmentioning

confidence: 99%

“…Modeling and control of robotic needle steering has been widely studied [1,8,14,19]. Park et al developed a nonholonomic unicycle-like model to describe needle deflection in firm tissue [14].…”

Section: Introductionmentioning

confidence: 99%

“…Webster et al extended this idea and developed a kinematics-based model generalizing the unicycle model [19]. Several research groups have used classical beam theories to develop models of needle deflection [8,17]. The nonholonomic unicycle model [19] is commonly used for needle steering.…”

Section: Introductionmentioning

confidence: 99%

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Geometric control of 3D needle steering in soft-tissue

et al. 2019

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In this paper, a 3D automated needle steering system is presented that can enhance the performance of needle-based procedures. The system comprises a nonholonomic needle steering model and a nonlinear controller for 3D needle steering. First, a reduced-order needle steering model is presented. Next, a geometric reduction procedure is carried out to present the nonlinear control system in a transformed format. Finally, the transformed model is used to design a two-step controller. The controller first stabilizes the system on an equilibrium manifold of the system and later employs a switching law to stabilize it on an equilibrium point in the manifold. The former performs insertion of the needle up to a desired depth and the latter performs retraction/insertion motion that guides the needle toward a desired point at the given depth. Validation experiments are performed on a phantom and ex-vivo animal tissues and the results are compared with manual needle insertions performed by skilled surgeons. The mean error of our 3D needle steering system is 60% less than manual needle insertions.

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Section: Step 2: Stabilization To a Pointmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Geometric control of 3D needle steering in soft-tissue

et al. 2019

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“…The steering mechanisms are classified into seven different categories: base manipulation [7], duty-cycled bevel tip (with and without pre-curve) [8, 9, 10, 11], pre-curved stylet [12], active cannula [13,14], programmable bevel tip [4,15,16], tendon actuated tip [17,18] and most recently, optically controlled needle [19]. Finite element analysis [21,22], beam theory [23,24] and spring foundations [25] have all been used to derive deflection models for steerable needles. Specifically, Oldfield et al [20] considered the deflection of the programmable bevel-tip needle design, but the analysis is restricted to 2D.…”

Section: Needle Steeringmentioning

confidence: 99%

Modelling the Deformation of Biologically Inspired Flexible Structures for Needle Steering

Watts

Secoli

Baena

2018

Mechanism, Machine, Robotics and Mechatronics Sciences

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Recent technical advances in minimally invasive surgery have been enabled by the development of new medical instruments and technologies. To date, the vast majority of mechanisms used within a clinical context are rigid, contrasting with the compliant nature of biological tissues. The field of robotics has seen an increased interest in flexible and compliant systems, and in this paper we investigate the behaviour of deformable multi-segment structures, which take their inspiration from the ovipositor design of parasitic wood wasps. These configurable structures have been shown to steer through highly compliant substrates, potentially enabling percutaneous access to the most delicate of tissues, such as the brain. The model presented here sheds light on how the deformation of the unique structure is related to its shape, and allows comparison between different potential designs. A finite element study is used to evaluate the proposed model, which is shown to provide a good fit (root-mean-square deviation 0.2636mm for 4-segment case). The results show that both 3-segment and 4-segment designs are able to achieve deformation in all directions, however the magnitude of deformation is more consistent in the 4segment case.

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“…According to the Galerkin-Bubnov method [25], beam deflection can be approximated as the sum of n candidate shape functions (eigenfunctions), each of which represents a mode of vibration. The deflection v(d, z) of a needle at a point z along its shaft and, for a given insertion depth d in our case, can be defined as [26], [27] v…”

Section: Needle-tissue Interaction Modelmentioning

confidence: 99%