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Proceedings Paper

Automatic definition of surgical trajectories and acceptance window in pelvic trauma surgery using deformable registration
Author(s): R. Han; B. Ramsay; T. De Silva; J. Goerres; A. Uneri; M. Ketcha; M. Jacobson; N. Sheth; S. Vogt; G. Kleinszig; G. Osgood; J. H. Siewerdsen
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Paper Abstract

Purpose: Pelvic screw insertion for percutaneous fixation is a challenging surgical procedure that requires interpretation of complex 3D anatomy from 2D fluoroscopic images. Extensive surgical training is needed and trial and error often occurs in device placement, causing extended fluoroscopy time and increased radiation dose. A system is reported for automatic definition of acceptable surgical trajectories to facilitate guidance and quality assurance in a manner consistent with surgical workflow.

Methods: An atlas was constructed with segmented pelvis shapes containing standard reference trajectories for screw placement. A statistical shape model computed from the atlas is used for deformable registration to the patient’s preoperative CT (without segmentation). By transferring the reference trajectories and surrounding acceptance windows (i.e., volumetric corridors of acceptable device placement) from the atlas, the system automatically computes reliable Kwire and screw trajectories for guidance (overlay in fluoroscopy) and QA.

Results: A leave-one-out analysis was performed to evaluate the accuracy or registration and overlay. The registration achieved average surface registration accuracy of 1.82 ± 0.39 mm. Automatically determined trajectories conformed within acceptable cortical bone margins, maintaining 3.75 ± 0.68 mm distance from cortex in narrow bone corridors and demonstrating accurate registration and surgical trajectory definition without breaching cortex.

Conclusions: The framework proposed in this work allows for multi-atlas based automatic planning of surgical trajectory without tracker or manual segmentation. The planning information can be further used to facilitate intraoperative guidance and post-operatively quality assurance in a manner consistent with surgical workflow.

Paper Details

Date Published: 13 March 2018
PDF: 7 pages
Proc. SPIE 10576, Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 105761N (13 March 2018); doi: 10.1117/12.2292927
Show Author Affiliations
R. Han, Johns Hopkins Univ. (United States)
B. Ramsay, Johns Hopkins Univ. (United States)
T. De Silva, Johns Hopkins Univ. (United States)
J. Goerres, Johns Hopkins Univ. (United States)
A. Uneri, Johns Hopkins Univ. (United States)
M. Ketcha, Johns Hopkins Univ. (United States)
M. Jacobson, Johns Hopkins Univ. (United States)
N. Sheth, Johns Hopkins Univ. (United States)
S. Vogt, Siemens Healthineers (Germany)
G. Kleinszig, Siemens Healthineers (Germany)
G. Osgood, Johns Hopkins Hospital (United States)
J. H. Siewerdsen, Johns Hopkins Univ. (United States)


Published in SPIE Proceedings Vol. 10576:
Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Robert J. Webster, Editor(s)

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