Robotic Needle Steering: Design, Modeling, Planning, and Image Guidance

Cowan, Noah J.; Goldberg, Ken; Chirikjian, Gregory S.; Fichtinger, Gabor; Alterovitz, Ron; Reed, Kyle B.; Kallem, Vinutha; Park, Wooram; Misra, Sarthak; Okamura, Allison M.

doi:10.1007/978-1-4419-1126-1_23

Cited by 91 publications

(97 citation statements)

References 71 publications

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“…A growing body of research has been reported on motion planning for steering needles [23] [24] [25]. The objective is to steer a flexible needle with curvature constraints through tissue to internal targets by exploiting asymmetries at the needle tip.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

An algorithm for computing customized 3D printed implants with curvature constrained channels for enhancing intracavitary brachytherapy radiation delivery

Garg

Patil

Siauw

et al. 2013

2013 IEEE International Conference on Automation Science and Engineering (CASE)

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Abstract-Brachytherapy is a widely-used treatment modality for cancer in many sites in the body. In brachytherapy, small radioactive sources are positioned proximal to cancerous tumors. An ongoing challenge is to accurately place sources on a set of dwell positions to sufficiently irradiate the tumors while limiting radiation damage to healthy organs and tissues. In current practice, standardized applicators with internal channels are inserted into body cavities to guide the sources. These standardized implants are one-size-fits-all and are prone to shifting inside the body, resulting in suboptimal dosages. We propose a new approach that builds on recent results in 3D printing and steerable needle motion planning to create customized implants containing customized curvature-constrained internal channels that fit securely, minimize air gaps, and precisely guide radioactive sources through printed channels. When compared with standardized implants, customized implants also have the potential to provide better coverage: more potential source dwell positions proximal to tumors. We present an algorithm for computing curvature-constrained channels based on rapidly-expanding randomized trees (RRT). We consider a prototypical case of OB/GYN cervical and vaginal cancer with three treatment options: standardized ring implant (current practice), customized implant with linear channels, and customized implant with curved channels. Results with a twoparameter coverage metric suggest that customized implants with curved channels can offer significant improvement over current practice.

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Section: Related Workmentioning

confidence: 99%

“…It is also important that channels do not intersect. We build on prior work by Patil et al [24] which uses rapidly exploring random trees (RRT) [28] for planning curvature constrained paths for steerable needles [25].…”

Section: Related Workmentioning

confidence: 99%

An algorithm for computing customized 3D printed implants with curvature constrained channels for enhancing intracavitary brachytherapy radiation delivery

Garg

Patil

Siauw

et al. 2013

2013 IEEE International Conference on Automation Science and Engineering (CASE)

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“…Robotic needle steering is an emerging technology which utilizes motorized manipulators and medical images to steer a flexible needle tip to reach specified anatomical regions [1,2]. Accurate needle tip placement is a critical issue in robotic needle steering because the performance of the needle-assisted interventions is determined by the amount of deviation between the needle tip and its target [3].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Needle Deflection in Layered Soft Tissue for Robotic Needle Steering

Lee

Kim

2015

Intelligent Autonomous Systems 13

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Precise needle tip placement is important in robotic needle steering but it is challenging to estimate the behavior of the flexible needle when it interacts with the soft tissue. Numerous studies have been focused on a needle deflection model in homogeneous tissue. However, human soft tissues generally have layered structure which has various mechanical properties and geometries. In this paper, we proposed a needle deflection model in a layered elastic medium considering variable needletissue interaction forces such as friction of needle surface, needle tip force, and lateral stiffness of soft tissue. For validation, needle steering experiment was performed to a layered tissue phantom and porcine meat which has a skin layer and muscle layer. Using the forces measured from the needle base in the experiment, the needle tip position was simulated. The simulated needle tip trajectory was then compared to the measured needle tip trajectory. The average needle tip estimation error was 1.78 ± 0.84 mm for tissue phantom and 1.85 ± 0.73 mm for porcine tissue. The proposed model could be applied to the robotic needle steering in layered tissue.

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“…In addition, the motion of the needle is subject to uncertainty due to tissue inhomogeneity, tissue deformation, needle torsion, etc. [7,23]. To address this issue, we follow the suggestion of Kallem [13] that a path with a smaller curvature 0 ≤ κ < κ 0 is small-time locally trackable and that this can be achieved using duty-cycled spinning of the needle during insertion.…”

Section: Introductionmentioning

confidence: 99%

LQG-Based Planning, Sensing, and Control of Steerable Needles

Berg

Patil

Alterovitz

et al. 2010

Springer Tracts in Advanced Robotics

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This paper presents a technique for planning and controlling bevel-tip steerable needles towards a target location in 3-D anatomy under the guidance of partial, noisy sensor feedback. Our approach minimizes the probability that the needle intersects obstacles such as bones and sensitive organs by (1) explicitly taking into account motion uncertainty and sensor types, and (2) allowing for efficient optimization of sensor placement. We allow for needle trajectories of arbitrary curvature through duty-cycled spinning of the needle, which is believed to make a needle path small-time locally "trackable" [13]. This enables us to use LQG control to guide the needle along the path. For a given path and sensor placement, we show that a priori probability distributions of the needle state can be estimated in advance. Our approach then plans a set of candidate paths and sensor placements and selects the pair for which the estimated uncertainty is least likely to cause intersections with obstacles. We demonstrate the performance of our approach in a modeled prostate cancer treatment environment.

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Robotic Needle Steering: Design, Modeling, Planning, and Image Guidance

Cited by 91 publications

References 71 publications

An algorithm for computing customized 3D printed implants with curvature constrained channels for enhancing intracavitary brachytherapy radiation delivery

An algorithm for computing customized 3D printed implants with curvature constrained channels for enhancing intracavitary brachytherapy radiation delivery

Estimation of Needle Deflection in Layered Soft Tissue for Robotic Needle Steering

LQG-Based Planning, Sensing, and Control of Steerable Needles

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