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Template for MR Visualization and Needle Targeting

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Abstract

To improve the targeting accuracy and reduce procedure time in magnetic resonance imaging (MRI)-guided procedures, a 3D-printed flexible template was developed. The template was printed using flexible photopolymer resin FLFLGR02 in Form 2 printer® (Formlabs, Inc., Somerville, MA). The flexible material gives the template a unique advantage by allowing it to make close contact with human skin and provide accurate insertion with the help of the newly developed OncoNav software. At the back of the template, there is a grid comprised of circular containers filled with contrast agent. At the front of the template, the guide holes between the containers provide space and angular flexibility for needle insertion. MRI scans are initially used to identify tumor position as well as the template location. The OncoNav software then pre-selects a best guide hole for targeting a specific lesion and suggests insertion depth for the physician A phantom study of 13 insertions in a CT scanner was carried out for assessing needle placement accuracy. The mean total distance error between planned and actual insertion is 2.7 mm, the maximum error was 4.78 mm and standard deviation was 1.1 mm. The accuracy of the OncoNav-assisted and template-guided needle targeting is comparable to the robot-assisted procedure. The proposed template is a low-cost, quickly-deployable and disposable medical device. The presented technology will be further evaluated in prostate cancer patients to quantify its accuracy in needle biopsy.

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Acknowledgments

This study was supported in part by the National Institutes of Health (NIH) Bench-to-Bedside Award, the National Science Foundation (NSF) I-Corps Team Grants (1617340) and (1836894), NSF REU Site Program 1359095, the UGA-AU Inter-institutional Seed Funding, the American Society for Quality Dr. Richard J. Schlesinger Grant, the PHS Grant UL1TR000454 from the Clinical and Translational Science Award Program, the NIH National Center for Advancing Translational Sciences, and NIH Center for Interventional Oncology and the NIH Intramural Research Program.

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Authors and Affiliations

  1. School of Electrical and Computer Engineering, University of Georgia, Athens, GA, USA

    Rui Li & Zion T. H. Tse

  2. Center for Interventional Oncology, National Institutes of Health, Bethesda, MD, USA

    Sheng Xu, Ivane Bakhutashvili & Bradford Wood

  3. Molecular Imaging Program, National Cancer Institute, Bethesda, MD, USA

    Ismail B. Turkbey & Peter Choyke

  4. Urologic Oncology Branch, National Cancer Institute, Bethesda, MD, USA

    Peter Pinto

  5. 3T Technologies, LLC, Marietta, GA, USA

    Zion T. H. Tse

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  1. Rui Li
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  2. Sheng Xu
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Correspondence to Zion T. H. Tse.

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Associate Editor Michael Gower oversaw the review of this article.

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Li, R., Xu, S., Bakhutashvili, I. et al. Template for MR Visualization and Needle Targeting. Ann Biomed Eng 47, 524–536 (2019). https://doi.org/10.1007/s10439-018-02167-z

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