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Proceedings Paper

Improved intraoperative imaging in spine surgery: clinical translation of known-component 3D image reconstruction on the O-arm system
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Paper Abstract

Intraoperative imaging systems are seeing an increased role in support of surgical guidance and quality assurance in the operating room for interventional approaches. However, image quality sufficient to detect complications and provide quantitative assessment of the surgical product are often confounded by image noise and artifacts. In this work, we translated a 3D image reconstruction method (referred to as “Known-Component Reconstruction,” KC-Recon) for the first time to clinical studies with the aim of resolving both limitations. KC-Recon builds upon an optimization-based reconstruction method to reduce noise and incorporates a model of surgical instruments in the image to reduce artifacts. The first clinical pilot study involved 17 spine surgery patients imaged using the O-arm before and after spinal instrumentation. Imaging performance was evaluated in terms of low-contrast soft-tissue visibility, the ability to assess screw placement within bone margins, and the potential to image at lower radiation doses. Depending on the imaging task, dose reduction up to an order of magnitude appeared feasible while maintaining soft-tissue visibility. KC-Recon also yielded ~30% reduction in blooming artifact about the screw shafts and ~60% higher tissue homogeneity at the screw tips, providing clearer depiction of pedicle and vertebral body for assessment of potential breaches. Overall, the method offers a promising means to reduce patient dose in image-guided procedures, extend the use of cone-beam CT to soft-tissue surgeries, provide a valuable check against complications in the operating room (cf., post-operative CT), and serve as a basis for quantitative evaluation of quality of the surgical construct.

Paper Details

Date Published: 8 March 2019
PDF: 8 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 1095103 (8 March 2019); doi: 10.1117/12.2513777
Show Author Affiliations
X. Zhang, Johns Hopkins Univ. (United States)
A. Uneri, Johns Hopkins Univ. (United States)
J. W. Stayman, Johns Hopkins Univ. (United States)
C. C. Zygourakis, Johns Hopkins Medicine (United States)
S. F. Lo, Johns Hopkins Medicine (United States)
N. Theodore, Johns Hopkins Medicine (United States)
J. H. Siewerdsen, Johns Hopkins Univ. (United States)
The Johns Hopkins Hospital (United States)

Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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