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Proceedings Paper

Known-component 3D-2D registration for image guidance and quality assurance in spine surgery pedicle screw placement
Author(s): A. Uneri; J. W. Stayman; T. De Silva; A. S. Wang; G. Kleinszig; S. Vogt; A. J. Khanna; J.-P. Wolinsky; Z. L. Gokaslan; J. H. Siewerdsen
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Paper Abstract

Purpose. To extend the functionality of radiographic / fluoroscopic imaging systems already within standard spine surgery workflow to: 1) provide guidance of surgical device analogous to an external tracking system; and 2) provide intraoperative quality assurance (QA) of the surgical product.

Methods. Using fast, robust 3D-2D registration in combination with 3D models of known components (surgical devices), the 3D pose determination was solved to relate known components to 2D projection images and 3D preoperative CT in near-real-time. Exact and parametric models of the components were used as input to the algorithm to evaluate the effects of model fidelity. The proposed algorithm employs the covariance matrix adaptation evolution strategy (CMA-ES) to maximize gradient correlation (GC) between measured projections and simulated forward projections of components. Geometric accuracy was evaluated in a spine phantom in terms of target registration error at the tool tip (TREx), and angular deviation (TREΦ) from planned trajectory.

Results. Transpedicle surgical devices (probe tool and spine screws) were successfully guided with TREx<2 mm and TREΦ <0.5° given projection views separated by at least >30° (easily accommodated on a mobile C-arm). QA of the surgical product based on 3D-2D registration demonstrated the detection of pedicle screw breach with TREx<1 mm, demonstrating a trend of improved accuracy correlated to the fidelity of the component model employed.

Conclusions. 3D-2D registration combined with 3D models of known surgical components provides a novel method for near-real-time guidance and quality assurance using a mobile C-arm without external trackers or fiducial markers. Ongoing work includes determination of optimal views based on component shape and trajectory, improved robustness to anatomical deformation, and expanded preclinical testing in spine and intracranial surgeries.

Paper Details

Date Published: 18 March 2015
PDF: 7 pages
Proc. SPIE 9415, Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling, 94151F (18 March 2015); doi: 10.1117/12.2082210
Show Author Affiliations
A. Uneri, Johns Hopkins Univ. (United States)
J. W. Stayman, Johns Hopkins Univ. (United States)
T. De Silva, Johns Hopkins Univ. (United States)
A. S. Wang, Johns Hopkins Univ. (United States)
G. Kleinszig, Siemens Healthcare XP Division (Germany)
S. Vogt, Siemens Healthcare XP Division (Germany)
A. J. Khanna, Johns Hopkins Medical Institute (United States)
J.-P. Wolinsky, Johns Hopkins Medical Institute (United States)
Z. L. Gokaslan, Johns Hopkins Medical Institute (United States)
J. H. Siewerdsen, Johns Hopkins Univ. (United States)


Published in SPIE Proceedings Vol. 9415:
Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster; Ziv R. Yaniv, Editor(s)

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