Toward Perception-based Anticipation of Cortical Breach During K-wire Fixation of the Pelvis

MEDICAL IMAGING 2022: PHYSICS OF MEDICAL IMAGING(2022)

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摘要
Intraoperative imaging using C-arm X-ray systems enables percutaneous management of fractures by providing real-time visualization of tool to tissue relationships. However, estimating appropriate positioning of surgical instruments, such as K-wires, relative to safe bony corridors is challenging due to the projective nature of X-ray images: tool pose in the plane containing the principal ray is difficult to assess, necessitating the acquisition of numerous views onto the anatomy. This task is especially demanding in complex anatomy, such as the superior pubic ramus of the pelvis, and results in high cognitive load and repeat attempts even in experienced trauma surgeons. A perception-based algorithm that interprets interventional radiographs during internal fixation to infer the likelihood of cortical breach especially early on, when the wire has not been advanced might reduce both the amount of X-rays acquired for verification and the likelihood of repeat attempts. In this manuscript, we present first steps towards developing such an algorithm. We devise a strategy for in silico collection and annotation of X-ray images suitable for detecting cortical breach of a K-wire in the superior pubic ramus, including those with visible fractures. Beginning with minimal manual annotations of correct trajectories, we randomly perturb entry and exit points and project the 3D scene using a physics-based forward model to obtain a large number of 2D X-ray images with and without cortical breach. We report baseline results for anticipating cortical breach at various K-wire insertion depths, achieving an AUROC score of 0.68 for 50% insertion. Code and data are available at github.com/benjamindkilleen/cortical-breach-detection.
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关键词
Robotic surgery,computer-assisted interventions,simulation,X-ray,deep learning
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