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Proceedings Paper

Evaluation of nonholonomic needle steering using a robotic needle driver
Author(s): Emmanuel Wilson; Jeinan Ding; Craig Carignan; Karthik Krishnan; Rick Avila; Wes Turner; Dan Stoianovici; David Yankelevitz; Filip Banovac; Kevin Cleary
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Paper Abstract

Accurate needle placement is a common need in the medical environment. While the use of small diameter needles for clinical applications such as biopsy, anesthesia and cholangiography is preferred over the use of larger diameter needles, precision placement can often be challenging, particularly for needles with a bevel tip. This is due to deflection of the needle shaft caused by asymmetry of the needle tip. Factors such as the needle shaft material, bevel design, and properties of the tissue penetrated determine the nature and extent to which a needle bends. In recent years, several models have been developed to characterize the bending of the needle, which provides a method of determining the trajectory of the needle through tissue. This paper explores the use of a nonholonomic model to characterize needle bending while providing added capabilities of path planning, obstacle avoidance, and path correction for lung biopsy procedures. We used a ballistic gel media phantom and a robotic needle placement device to experimentally assess the accuracy of simulated needle paths based on the nonholonomic model. Two sets of experiments were conducted, one for a single bend profile of the needle and the second set of tests for double bending of the needle. The tests provided an average error between the simulated path and the actual path of 0.8 mm for the single bend profile and 0.9 mm for the double bend profile tests over a 110 mm long insertion distance. The maximum error was 7.4 mm and 6.9 mm for the single and double bend profile tests respectively. The nonholonomic model is therefore shown to provide a reasonable prediction of needle bending.

Paper Details

Date Published: 23 February 2010
PDF: 13 pages
Proc. SPIE 7625, Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling, 762523 (23 February 2010); doi: 10.1117/12.844479
Show Author Affiliations
Emmanuel Wilson, Georgetown Univ. Medical Ctr. (United States)
Jeinan Ding, Georgetown Univ. Medical Ctr. (United States)
Craig Carignan, Georgetown Univ. Medical Ctr. (United States)
Karthik Krishnan, Kitware, Inc. (United States)
Rick Avila, Kitware, Inc. (United States)
Wes Turner, Kitware, Inc. (United States)
Dan Stoianovici, The Johns Hopkins Univ. (United States)
David Yankelevitz, Weill-Cornell Medical Ctr. (United States)
Filip Banovac, Georgetown Univ. Medical Ctr. (United States)
Kevin Cleary, Georgetown Univ. Medical Ctr. (United States)

Published in SPIE Proceedings Vol. 7625:
Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; Michael I. Miga, Editor(s)

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