Real-time artificial intelligence-based needle tracking for ultrasound-guided regional anesthesia training: a pilot prospective randomized controlled trial.

IF 2.6 3区 医学 Q2 ANESTHESIOLOGY
Misato Kurota, Kai Kubota, Tatsuya Hayasaka, Hiroaki Toyama
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引用次数: 0

Abstract

Background: Proper needle visualization is a major technical challenge for novices learning ultrasound-guided regional anesthesia (UGRA). We developed a 'You Only Look Once version 5' (YOLOv5)-based system that records quantitative needle trajectory data and delivers real-time visual and auditory feedback to support training. This pilot study aimed to explore whether short-term use of the real-time feedback system improved puncture safety and whether needle oscillation amplitude, a system-derived trajectory-based metric, could serve as an objective indicator of technical proficiency in UGRA training.

Methods: Twenty-three medical students with no UGRA experience were randomized into control (n = 12) and YOLOv5 feedback (n = 11) groups. Participants performed three in-plane punctures of increasing difficulty on phantoms: sagittal (puncture A), coronal (puncture B), and transverse (puncture C). Each included watching an instructional video, a 5-minute practice (with feedback for the YOLOv5 group or without for the control group), and a test puncture without feedback. The outcomes were needle tip disappearance frequency compared between the control and YOLOv5 feedback groups and needle oscillation amplitude - the maximum lateral deviation from the ideal insertion line, automatically recorded by the system - compared between punctures classified as safe and unsafe by an independent blinded assessor.

Results: Needle tip disappearance frequency did not differ between the control and YOLOv5 feedback groups across all approaches (puncture A: median, 0 vs. 0, P = 0.933; puncture B: 0 vs. 1, P = 0.246; puncture C: 1 vs. 2, P = 0.463). Only puncture C yielded both safe and unsafe punctures, enabling comparative analysis of the needle oscillation amplitude. Participants performing safe punctures (Level 1, n = 9) exhibited significantly smaller needle oscillation amplitudes (136.0 ± 32.1 pixels) than those performing unsafe punctures (Level 3, n = 12, 230.5 ± 85.4 pixels; P = 0.003).

Conclusions: This pilot study identified needle oscillation amplitude as a candidate objective proficiency metric in UGRA training, with preliminary evidence differentiating safe from unsafe punctures. Short-term training with the current prototype did not produce measurable improvements in puncture safety. However, the usability challenges encountered with this feedback system provided foundational insights for developing an optimized trajectory-based feedback system.

Trial registration: UMIN Clinical Trials Registry (UMIN000055602), registered October 1, 2024.

超声引导区域麻醉训练中基于人工智能的实时针头跟踪:一项前瞻性随机对照试验。
背景:对于超声引导区域麻醉(UGRA)的新手来说,正确的针头可视化是一个主要的技术挑战。我们开发了一个基于“You Only Look Once version 5”(YOLOv5)的系统,该系统可以记录定量的针轨迹数据,并提供实时的视觉和听觉反馈,以支持培训。本试点研究旨在探讨短期使用实时反馈系统是否能提高穿刺安全性,以及针头振荡幅度(一种基于系统衍生轨迹的度量)是否可以作为UGRA培训中技术熟练程度的客观指标。方法:23名没有UGRA经历的医学生随机分为对照组(n = 12)和YOLOv5反馈组(n = 11)。参与者对幻影进行了三次难度越来越大的平面穿刺:矢状面(穿刺A)、冠状面(穿刺B)和横向(穿刺C)。每个测试包括观看一段教学视频,5分钟的练习(YOLOv5组有反馈,对照组没有反馈),以及一个没有反馈的穿刺测试。结果是比较对照组和YOLOv5反馈组的针尖消失频率,以及由独立盲法评估者将针尖振荡幅度(系统自动记录的与理想插入线的最大横向偏差)划分为安全和不安全的穿刺之间的比较。结果:在所有入路中,针尖消失频率在对照组和YOLOv5反馈组之间没有差异(穿刺A:中位数,0 vs. 0, P = 0.933;穿刺B: 0 vs. 1, P = 0.246;穿刺C: 1 vs. 2, P = 0.463)。只有C穿刺产生了安全和不安全的穿刺,可以对针振荡幅度进行比较分析。进行安全穿刺的受试者(1级,n = 9)的针头振荡幅度(136.0±32.1像素)明显小于进行不安全穿刺的受试者(3级,n = 12, 230.5±85.4像素;P = 0.003)。结论:该初步研究确定针头振荡幅度作为UGRA训练的候选客观熟练度指标,并有初步证据区分安全与不安全穿刺。使用目前的原型进行短期培训并没有在穿刺安全性方面产生可测量的改善。然而,该反馈系统遇到的可用性挑战为开发优化的基于轨迹的反馈系统提供了基础见解。试验注册:UMIN临床试验注册(UMIN000055602),注册于2024年10月1日。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Anesthesiology
BMC Anesthesiology ANESTHESIOLOGY-
CiteScore
3.50
自引率
4.50%
发文量
349
审稿时长
>12 weeks
期刊介绍: BMC Anesthesiology is an open access, peer-reviewed journal that considers articles on all aspects of anesthesiology, critical care, perioperative care and pain management, including clinical and experimental research into anesthetic mechanisms, administration and efficacy, technology and monitoring, and associated economic issues.
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