Suppr超能文献

实时人工智能辅助颈动脉支架置入术:初步经验

Real time artificial intelligence assisted carotid artery stenting: a preliminary experience.

作者信息

Sakakura Yuya, Kono Kenichi, Fujimoto Takeshi

机构信息

Department of Neurosurgery, NTT Medical Center Tokyo, Tokyo, Japan

Department of Neurosurgery, Showa University Fujigaoka Hospital, Kanagawa, Japan.

出版信息

J Neurointerv Surg. 2025 Mar 17;17(4):410-414. doi: 10.1136/jnis-2024-021600.

Abstract

BACKGROUND

Neurointerventionalists must pay close attention to multiple devices on multiple screens simultaneously, which can lead to oversights and complications. Artificial intelligence (AI) has potential application in recognizing and monitoring these devices on fluoroscopic imaging.

METHODS

We report out preliminary experience with a real time AI assistance software, Neuro-Vascular Assist (iMed technologies, Tokyo, Japan), in six patients who underwent carotid artery stenting. This software provides real time assistance during endovascular procedures by tracking wires, guiding catheters, and embolic protection devices. The software provides notification when devices move out of a predefined region of interest or off the screen during the procedure. Efficacy, safety, and accuracy of the software were evaluated.

RESULTS

The software functioned well without problems and was easily used. Mean number of notifications per procedure was 21.0. The mean numbers of true positives, false positives, and false negatives per procedure were 17.2, 3.8, and 1.2, respectively. Precision and recall were 82% and 94%, respectively. Among the 103 true positive notifications, 24 caused the operator to adjust the inappropriate position of the device (23%), which is approximately four times per procedure. False notifications occurred because of false positive device detection. No adverse events related to the software occurred. No periprocedural complications occurred.

CONCLUSIONS

Neuro-Vascular Assist, a real time AI assistance software, worked appropriately and may be beneficial in carotid artery stenting procedures. Future large scale studies are warranted to confirm.

摘要

背景

神经介入医生必须同时密切关注多个屏幕上的多个设备,这可能导致疏忽和并发症。人工智能(AI)在荧光透视成像中识别和监测这些设备方面具有潜在应用价值。

方法

我们报告了在6例接受颈动脉支架置入术的患者中使用实时人工智能辅助软件Neuro-Vascular Assist(日本东京iMed technologies公司)的初步经验。该软件在血管内手术过程中通过跟踪导丝、引导导管和栓子保护装置提供实时辅助。在手术过程中,当设备移出预定义的感兴趣区域或屏幕外时,该软件会发出通知。对该软件的有效性、安全性和准确性进行了评估。

结果

该软件运行良好,没有问题,且易于使用。每次手术的平均通知次数为21.0次。每次手术的真阳性、假阳性和假阴性的平均次数分别为17.2、3.8和1.2次。精确率和召回率分别为82%和94%。在103次真阳性通知中,有24次(23%)导致操作员调整了设备的不当位置,每次手术约4次。错误通知是由于设备检测出现假阳性。未发生与该软件相关的不良事件。未发生围手术期并发症。

结论

实时人工智能辅助软件Neuro-Vascular Assist运行良好,可能对颈动脉支架置入术有益。未来需要进行大规模研究以证实。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验