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一种使用人工智能技术在胃镜下测量食管静脉曲张直径的非侵入性技术。

A Noninvasive Technology Using Artificial Intelligence to Measure the Diameter of Esophageal Varices Under Endoscopy.

机构信息

Key Laboratory of Digestive Diseases of Anhui Province, Department of Gastroenterology, The First Affiliated Hospital of Anhui Medical University.

School of Computer Science and Technology, High-tech Campus, University of Science and Technology of China.

出版信息

Surg Laparosc Endosc Percutan Tech. 2023 Jun 1;33(3):282-285. doi: 10.1097/SLE.0000000000001168.

Abstract

BACKGROUND

The diameter of esophageal varices (EVs) can not only predict variceal bleeding episodes but is also considered to be a significant factor in determining the endoscopic treatment of EVs. At present, visual observation is the most common method for estimating the diameter of EVs, the results of which may vary greatly between endoscopists.

MATERIALS AND METHODS

Herein, a noninvasive measurement technology, a virtual ruler (VR), was designed using artificial intelligence. The diameter and pressure of EVs in 7 patients were measured using VR and an esophageal varix manometer (EVM). Statistical methods, including the Bland-Altman Plot and Pearson correlation coefficient analysis, were used to compare the aforementioned 2 methods.

RESULTS

The results showed that the diameter of EVs measured using the aforementioned 2 methods did not differ. In addition, the time taken to measure the diameter of EVs using VR was 31 seconds (range, 25 to 44 s), significantly shorter compared with 159 seconds (range, 95 to 201 s) taken using an EVM ( P < 0.01). Furthermore, the diameter of EVs measured using an EVM exhibited a high linear correlation with pressure.

CONCLUSIONS

The current study demonstrated that VR was more accurate in measuring the diameter of EVs compared with EVMs while reducing unnecessary early intervention and the risk of complications. In terms of clinical risk and economic cost, this technology is hardly a burden. Overall, VR could be a useful software for the endoscopic detection and treatment of EVs in patients with liver cirrhosis.

摘要

背景

食管静脉曲张(EVs)的直径不仅可以预测静脉曲张出血事件,而且被认为是决定 EVs 内镜治疗的重要因素。目前,视觉观察是估计 EVs 直径最常用的方法,结果可能在不同内镜医生之间存在很大差异。

材料和方法

在此,我们设计了一种使用人工智能的非侵入性测量技术——虚拟标尺(VR)。使用 VR 和食管静脉曲张测压计(EVM)测量了 7 例患者的 EVs 直径和压力。使用 Bland-Altman 图和 Pearson 相关系数分析等统计方法比较了上述两种方法。

结果

结果表明,使用上述两种方法测量的 EVs 直径无差异。此外,使用 VR 测量 EVs 直径的时间为 31 秒(范围为 25 至 44 秒),明显短于使用 EVM 测量的 159 秒(范围为 95 至 201 秒)(P < 0.01)。此外,使用 EVM 测量的 EVs 直径与压力呈高度线性相关。

结论

本研究表明,与 EVM 相比,VR 在测量 EVs 直径方面更准确,同时减少了不必要的早期干预和并发症风险。就临床风险和经济成本而言,这项技术几乎没有负担。总的来说,VR 可以成为肝硬化患者 EVs 内镜检测和治疗的有用软件。

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