基于 ALI 评分的显微吻合术客观技能评估框架。

An objective skill assessment framework for microsurgical anastomosis based on ALI scores.

机构信息

Learning Algorithms and Systems Laboratory (LASA), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.

Department of Neurosurgery, The National Hospital of Denmark, Rigshospitalet, Copenhagen, Denmark.

出版信息

Acta Neurochir (Wien). 2024 Feb 24;166(1):104. doi: 10.1007/s00701-024-05934-1.

Abstract

INTRODUCTION

The current assessment and standardization of microsurgical skills are subjective, posing challenges in reliable skill evaluation. We aim to address these limitations by developing a quantitative and objective framework for accurately assessing and enhancing microsurgical anastomosis skills among surgical trainees. We hypothesize that this framework can differentiate the proficiency levels of microsurgeons, aligning with subjective assessments based on the ALI score.

METHODS

We select relevant performance metrics from the literature on laparoscopic skill assessment and human motor control studies, focusing on time, instrument kinematics, and tactile information. This information is measured and estimated by a set of sensors, including cameras, a motion capture system, and tactile sensors. The recorded data is analyzed offline using our proposed evaluation framework. Our study involves 12 participants of different ages ([Formula: see text] years) and genders (nine males and three females), including six novice and six intermediate subjects, who perform surgical anastomosis procedures on a chicken leg model.

RESULTS

We show that the proposed set of objective and quantitative metrics to assess skill proficiency aligns with subjective evaluations, particularly the ALI score method, and can effectively differentiate novices from more proficient microsurgeons. Furthermore, we find statistically significant disparities, where microsurgeons with intermediate level of skill proficiency surpassed novices in both task speed, reduced idle time, and smoother, briefer hand displacements.

CONCLUSION

The framework enables accurate skill assessment and provides objective feedback for improving microsurgical anastomosis skills among surgical trainees. By overcoming the subjectivity and limitations of current assessment methods, our approach contributes to the advancement of surgical education and the development of aspiring microsurgeons. Furthermore, our framework emerges to precisely distinguish and classify proficiency levels (novice and intermediate) exhibited by microsurgeons.

摘要

简介

当前对显微手术技能的评估和标准化是主观的,这给可靠的技能评估带来了挑战。我们旨在通过开发一种定量和客观的框架来解决这些局限性,以准确评估和提高外科受训者的显微吻合技能。我们假设该框架可以区分显微外科医生的熟练程度,与基于 ALI 评分的主观评估相一致。

方法

我们从腹腔镜技能评估和人类运动控制研究的文献中选择相关的性能指标,重点关注时间、器械运动学和触觉信息。这些信息由一组传感器(包括摄像机、运动捕捉系统和触觉传感器)进行测量和估计。使用我们提出的评估框架离线分析记录的数据。我们的研究涉及 12 名不同年龄([Formula: see text] 岁)和性别的参与者(9 名男性和 3 名女性),包括 6 名新手和 6 名中级参与者,他们在鸡腿模型上进行手术吻合程序。

结果

我们表明,一组用于评估技能熟练程度的客观和定量指标与主观评估,特别是 ALI 评分方法,相一致,可以有效地将新手与更熟练的显微外科医生区分开来。此外,我们发现存在统计学上的显著差异,具有中级技能熟练程度的显微外科医生在任务速度、减少空闲时间以及更平稳、更短暂的手部位移方面均优于新手。

结论

该框架能够准确评估技能,并为提高外科受训者的显微吻合技能提供客观反馈。通过克服当前评估方法的主观性和局限性,我们的方法有助于外科教育的发展和有抱负的显微外科医生的培养。此外,我们的框架还能够精确区分和分类显微外科医生表现出的熟练程度(新手和中级)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52b3/11408545/79b6325fb43f/701_2024_5934_Fig1_HTML.jpg

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