Qualitative and Quantitative Assessment of Invasive Surgery Skill Based on a Custom Training Simulator.
Qualitative and Quantitative Assessment of Invasive Surgery Skill Based on a Custom Training Simulator.
复制标题
DOI：
10.1177/15266028231179865
复制
发表时间：
2023-06
期刊：
影响因子：
--
通讯作者：
Shichao Liang;Long Li;Bin Yang;Panpan Yuan;Shilong Li;Yue Shi;F. Gao;Yiming Deng;L. Jiao;Duanduan Chen
中科院分区：
文献类型：
--
作者：
Shichao Liang;Long Li;Bin Yang;Panpan Yuan;Shilong Li;Yue Shi;F. Gao;Yiming Deng;L. Jiao;Duanduan Chen
介入操作的定性和定量评估是评价血管内外科技能培训的重要组成部分。我们为血管内性能培训建立了一个具有定性和定量指标的定制模拟器。方法：模拟器包括体外硅胶体模、模拟循环回路、视觉模块、力传感模块以及用于图像和力数据后处理的定制软件。专家组（n=4）、新手组（n=6）和试验组（n=4）分别执行了将导丝输送至颈动脉靶位置的两项任务。从专家组和新手组中提取的7个具有显著差异的特征被应用于使用支持向量机（SVM）的定性评估和使用马氏距离（MD）的定量评估。结果在干预过程中，专家组和新手组的运动学和力数据存在显著差异。专家组完成任务1的时间中位数为26.88秒，新手组为63.36秒。专家和新手的最大速度分别为32.79和7.43 cm/s。此外，分类结果表明，任务1和任务2的定性评估的准确率分别为96.67%和90%。在定量数据方面，住院医师在两个任务上的得分均高于生物医学工程专业的个体（任务1为70.06±5.30 vs 41.81±6.58，p=0.001）。结论：所提出的血管内介入技能培训模拟器提供了介入性能技能的定性和定量指标，可能是未来介入手术培训的有用工具。临床影响该模拟器包括体外硅胶体模、模拟循环回路、视觉模块、力传感模块以及用于图像和力数据后处理的定制软件。七个介入性能特征用于使用支持向量机进行定性评估和使用马氏距离进行定量评估。根据观察结果，我们得出结论，该血管内介入技能培训模拟器提供了介入性能的定性和定量指标，可能是未来手术培训的有用工具。
PURPOSE Qualitative and quantitative assessment of interventional performance is a vital component in the evaluation of endovascular surgery skill training. We established a custom simulator with qualitative and quantitative metrics for endovascular performance training. METHODS The simulator included an in vitro silicone phantom, mock circulation loop, visual module, force-sensing module, and custom software for image and force data postprocessing. Two tasks to deliver the guidewire to the target location of the carotid artery were conducted by the expert (n=4), novice (n=6), and test (n=4) groups. Seven features with significant differences extracted from the expert and novice groups were applied for qualitative assessment using the support vector machine (SVM) and quantitative assessment using the Mahalanobis distance (MD). RESULTS Significant differences were observed in kinematic and force data between experts and novices during the intervention procedure. The median value of finished time for task 1 was 26.88 seconds for experts and 63.36 seconds for novices. The maximum speed for experts and novices was 32.79 and 7.43 cm/s, respectively. Moreover, the classified results depicted that the accuracy of qualitative assessment for task 1 and task 2 was 96.67% and 90%, respectively. As for the quantitative data, the residents had higher scores than individuals majored in biomedical engineering at 2 tasks (70.06±5.30 vs 41.81±6.58 for task 1, p=0.001). CONCLUSIONS The proposed endovascular intervention skill training simulator provides qualitative and quantitative metrics on intervention performance skills and may be a useful tool in future interventional surgical training. CLINICAL IMPACT This simulator comprised an in-vitro silicone phantom, mock circulation loop, visual module, force-sensing module, and custom software for image and force data post-processing. Seven interventional performance features were used for qualitative assessment using the support vector machine and quantitative assessment using the Mahalanobis Distance. From the observations, we conclude that this endovascular intervention skill training simulator provides qualitative and quantitative metrics on intervention performance and may be a useful tool in future surgical training.