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Proceedings Paper

Miniature C-arm simulator using wireless accelerometer based tracking
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Paper Abstract

C-Arm positioning for interventional spine procedures can often be associated with a steep learning curve. The current training standards involve using real X-rays on cadavers or via apprenticeship-based programs. To help limit excess radiation exposure, several radiation-free training systems have been proposed in the literature but there lacks a hands-on, cost-effective simulator that does not require access to a physical C-Arm. In order to expand the accessibility of radiation-free C-Arm training, we have developed a 10:1 scaled down C-Arm simulator using 3D-printed parts and wireless accelerometers for tracking. We generated Digitally Reconstructed Radiographs (DRRs) in real-time using a 1-dimensional transfer function operating on a ray-traced projection of a patient CT scan. To evaluate the efficacy of the system as a training tool, we conducted a user study in which anesthesiology and orthopedic residents were evaluated on the accuracy of their C-Arm placement for three standard views used in spinal injection procedures. Both the experimental group and control group were given the same evaluation task with the experimental group receiving 5 minutes of training on the system using real-time DRRs and a standardized two page curriculum on proper image acquisition. The experimental group achieved an angular error of 4.76±1.66° which was lower than the control group at 6.88±3.67° and the overall feedback of the system was positive based on a Likert scale questionnaire filled out by each participant. The results indicate that our system has high potential for improving C-Arm placement in interventional spine procedures and we plan to conduct a follow-up study to evaluate the long-term training capabilities of the simulator.

Paper Details

Date Published: 16 March 2020
PDF: 9 pages
Proc. SPIE 11315, Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling, 1131502 (16 March 2020); doi: 10.1117/12.2547388
Show Author Affiliations
Daniel R. Allen, Western Univ. (Canada)
Robarts Research Institute (Canada)
John Moore, Robarts Research Institute (Canada)
Abigayel Joschko, London Health Sciences Ctr. (Canada)
Collin Clarke, London Health Sciences Ctr. (Canada)
Terry M. Peters, Western Univ. (Canada)
Robarts Research Institute (Canada)
Elvis C. S. Chen, Western Univ. (Canada)
Robarts Research Institute (Canada)

Published in SPIE Proceedings Vol. 11315:
Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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