An accurate assessment of surgical operation skills is essential for improving the vascular intervention surgical outcome and the performance of endovascular surgery robots. In existing studies, subjective and objective assessments of surgical operation skills use a variety of indicators, such as the operation speed and operation smoothness. However, the vascular conditions of particular patients have not been considered in the assessment, leading to deviations in the evaluation. Therefore, in this paper, an operation skills assessment method including the vascular difficulty level index for catheter insertion at the aortic arch in endovascular surgery is proposed. First, the model describing the difficulty of the vascular anatomical structure is established with characteristics of different aortic arch branches based on machine learning. Afterwards, the vascular difficulty level is set as an objective index combined with operating characteristics extracted from the operations performed by surgeons to evaluate the surgical operation skills at the aortic arch using machine learning. The accuracy of the assessment improves from 86.67 to 96.67% after inclusion of the vascular difficulty as an evaluation indicator to more objectively and accurately evaluate skills. The method described in this paper can be adopted to train novice surgeons in endovascular surgery, and for studies of vascular interventional surgery robots.

Operation skill assessment with vascular difficulty for vascular interventional surgery

准确评估手术操作技能对于改善血管介入手术的结果和血管内手术机器人的性能至关重要。在现有研究中，对手术操作技能的主观和客观评估都使用各种指标，例如手术速度和手术的顺畅程度。但是，评估过程中未考虑特定患者的血管状况，从而导致评估结果出现偏差。因此，本文提出了一种在血管内手术中包括在主动脉弓处插入导管的血管难易程度指数的操作技能评估方法。首先，基于机器学习，建立具有不同主动脉弓分支特征的描述血管解剖结构困难的模型。此后，将血管难易程度设置为客观指标，并结合从外科医生进行的手术中提取的手术特征，以使用机器学习评估主动脉弓的手术操作技能。将血管困难纳入评估指标以更加客观，准确地评估技能后，评估的准确性从86.67提高到96.67％。本文介绍的方法可用于在血管内手术中培训新手外科医生，以及用于血管介入手术机器人的研究。将血管困难纳入评估指标以更加客观，准确地评估技能后，评估的准确性从86.67提高到96.67％。本文介绍的方法可用于在血管内手术中培训新手外科医生，以及用于血管介入手术机器人的研究。将血管困难纳入评估指标以更加客观，准确地评估技能后，评估的准确性从86.67提高到96.67％。本文介绍的方法可用于在血管内手术中培训新手外科医生，以及用于血管介入手术机器人的研究。

血管介入手术中血管困难的操作技能评估