胸腰椎椎弓根螺钉置入路径规划数据集标注及质量控制专家共识

Expert Consensus on Data Annotation and Quality Control for Trajectory Planning of Thoracolumbar Pedicle Screw Placement

  • 摘要: 近年来,结合人工智能(artificial intelligence,AI)技术开发的椎弓根螺钉置入手术机器人系统展现出极大的潜力,可提升术前路径规划的精度与效率,优化手术安全性。该类人工智能辅助规划系统能通过精准计算螺钉入点、止点及路径,有效避免伤害重要解剖结构,辅助医生制定合理的手术方案。然而,系统算法性能和临床适用性很大程度上依赖于具有高质量标注结果的数据集。为规范相关数据集建设,中国食品药品检定研究院联合相关单位制订专家共识,旨在为椎弓根螺钉置入路径规划数据集的建设提供标准化指导。

     

    Abstract: In recent years, pedicle screw placement robotic systems developed with the integration of artificial intelligence (AI) technologies have demonstrated great potential to improve the accuracy and efficiency of preoperative trajectory planning and to enhance surgical safety. Such AI-assisted planning systems can precisely calculate the entry point, end point, and trajectory of screws, thereby effectively avoiding injury to critical anatomical structures and assisting surgeons in developing optimal surgical strategies. However, the performance of the underlying algorithms and their clinical applicability largely depend on datasets with high-quality annotations. To standardize the construction of such datasets, the National Institutes for Food and Drug Control (NIFDC), together with relevant institutions, has formulated this expert consensus, which aims to provide standardized guidance for the development of pedicle screw trajectory planning datasets.

     

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