ICube CNRS UMR7357, Strasbourg University, 2-4, rue Boussingault, 67000 Strasbourg, France; IHU, Institute of image-guided surgery, Strasbourg, France.
Department of hand surgery, Strasbourg University Hospitals, FMTS, 1, avenue Molière, 67200 Strasbourg, France.
Orthop Traumatol Surg Res. 2023 Oct;109(6):103564. doi: 10.1016/j.otsr.2023.103564. Epub 2023 Jan 24.
INTRODUCTION: In order to be used naturally and widely, an artificial intelligence algorithm of phase detection in surgical videos presupposes an expert consensus defining phases. OBJECTIVES: The aim of the present study was to seek consensus in defining the various phases of a surgical technique in wrist traumatology. METHODS: Three thousand two hundred and twenty-nine surgeons were sent a video showing anterior plate fixation of the distal radius and a questionnaire on the number of phases they distinguished and the visual cues signaling the beginning of each phase. Three experimenters predefined the number of phases (5: installation, approach, fixation, verification, closure) and sub-phases (3a: introduction of plate; 3b: positioning distal screws; 3c: positioning proximal screws) and the cues signaling the beginning of each. The numbers of the responses per item were collected. RESULTS: Only 216 (6.7%) surgeons opened the questionnaire, and 100 answered all questions (3.1%). Most respondents claimed 5/5 expertise. Number of phases identified ranged between 3 and 10. More than two-thirds of respondents identified the same phase cue as defined by the 3 experimenters in most cases, except for "verification" and "positioning proximal screws". DISCUSSION: Surgical procedures comprise a succession of phases, the beginning or end of which can be defined by a precise visual cue on video, either beginning with the appearance of the cue or the disappearance of the cue defining the preceding phase. CONCLUSION: These cues need to be defined very precisely before attempting manual annotation of surgical videos in order to develop an artificial intelligence algorithm. LEVEL OF EVIDENCE: II.
简介:为了实现自然和广泛的应用,手术视频中的相位检测人工智能算法需要专家共识来定义相位。 目的:本研究旨在寻求在腕关节创伤学中定义手术技术各阶段的共识。 方法:向 3229 名外科医生发送了一段展示桡骨远端前路钢板固定的视频和一份问卷,询问他们区分的阶段数以及每个阶段开始的视觉提示。三位实验者预先定义了阶段数(5 个:安装、入路、固定、验证、关闭)和亚阶段(3a:引入钢板;3b:定位远端螺钉;3c:定位近端螺钉)以及每个阶段开始的提示。收集每个项目的响应数量。 结果:只有 216 名(6.7%)外科医生打开了问卷,100 名(3.1%)回答了所有问题。大多数受访者声称有 5/5 专业知识。识别的阶段数在 3 到 10 之间。超过三分之二的受访者在大多数情况下识别出与三位实验者定义的相同的阶段提示,除了“验证”和“定位近端螺钉”。 讨论:手术过程包括一系列阶段,其开始或结束可以通过视频上的精确视觉提示来定义,要么从提示出现开始,要么从定义前一阶段的提示消失开始。 结论:在尝试手动注释手术视频以开发人工智能算法之前,这些提示需要非常精确地定义。 证据水平:II 级。
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