Miniature C-arm simulator using wireless accelerometer based tracking

Daniel R. Allen; John Moore; Abigayel Joschko; Collin Clarke; Terry M. Peters; Elvis C. S. Chen

doi:10.1117/12.2547388

16 March 2020 Miniature C-arm simulator using wireless accelerometer based tracking

Daniel R. Allen, John Moore, Abigayel Joschko, Collin Clarke, Terry M. Peters, Elvis C. S. Chen

Proceedings Volume 11315, Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling; 1131502 (2020) https://doi.org/10.1117/12.2547388
Event: SPIE Medical Imaging, 2020, Houston, Texas, United States

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.

Conference Presentation

Citation Download Citation

Daniel R. Allen, John Moore, Abigayel Joschko, Collin Clarke, Terry M. Peters, and Elvis C. S. Chen "Miniature C-arm simulator using wireless accelerometer based tracking", Proc. SPIE 11315, Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling, 1131502 (16 March 2020); https://doi.org/10.1117/12.2547388

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