通过常规使用全自动软件缩短超声心动图检查时间:测量和报告创建时间的比较研究。

IF 1.4 Q3 CARDIAC & CARDIOVASCULAR SYSTEMS
Journal of Echocardiography Pub Date : 2024-09-01 Epub Date: 2024-02-03 DOI:10.1007/s12574-023-00636-6
Yukina Hirata, Yuka Nomura, Yoshihito Saijo, Masataka Sata, Kenya Kusunose
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引用次数: 0

摘要

背景:人工解读超声心动图数据既耗时又依赖于操作者。随着人工智能(AI)的出现,人们对其简化超声心动图解读和减少变异性的潜力越来越感兴趣。本研究旨在比较人工智能与人类专家在将获取的动态图像转换为 DICOM 数据后进行测量所需的时间:方法:23 名连续的患者由一名操作员进行检查,患者的图像质量和病情各不相同。超声心动图参数由人类专家使用手动方法和全自动 US2.ai 软件进行独立评估。US2.ai 软件的自动化流程包括实时处理二维和多普勒数据、测量临床上重要的变量(如左心室功能和几何形状)、自动参数评估以及生成报告,报告中包含与指南一致的结果和评论。我们评估了超声心动图测量和报告生成所需的时间:结果:与手动方法相比,人工智能大大缩短了测量时间(159±66 秒 vs. 325±94 秒,p 结论:这款全自动软件有可能在超声心动图测量中发挥重要作用:这款全自动软件有望成为超声心动图分析的高效工具,通过提供快速、零点击的报告来改进临床工作流程,从而显著增加价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reducing echocardiographic examination time through routine use of fully automated software: a comparative study of measurement and report creation time.

Background: Manual interpretation of echocardiographic data is time-consuming and operator-dependent. With the advent of artificial intelligence (AI), there is a growing interest in its potential to streamline echocardiographic interpretation and reduce variability. This study aimed to compare the time taken for measurements by AI to that by human experts after converting the acquired dynamic images into DICOM data.

Methods: Twenty-three consecutive patients were examined by a single operator, with varying image quality and different medical conditions. Echocardiographic parameters were independently evaluated by human expert using the manual method and the fully automated US2.ai software. The automated processes facilitated by the US2.ai software encompass real-time processing of 2D and Doppler data, measurement of clinically important variables (such as LV function and geometry), automated parameter assessment, and report generation with findings and comments aligned with guidelines. We assessed the duration required for echocardiographic measurements and report creation.

Results: The AI significantly reduced the measurement time compared to the manual method (159 ± 66 vs. 325 ± 94 s, p < 0.01). In the report creation step, AI was also significantly faster compared to the manual method (71 ± 39 vs. 429 ± 128 s, p < 0.01). The incorporation of AI into echocardiographic analysis led to a 70% reduction in measurement and report creation time compared to manual methods. In cases with fair or poor image quality, AI required more corrections and extended measurement time than in cases of good image quality. Report creation time was longer in cases with increased report complexity due to human confirmation of AI-generated findings.

Conclusions: This fully automated software has the potential to serve as an efficient tool for echocardiographic analysis, offering results that enhance clinical workflow by providing rapid, zero-click reports, thereby adding significant value.

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来源期刊
Journal of Echocardiography
Journal of Echocardiography CARDIAC & CARDIOVASCULAR SYSTEMS-
CiteScore
3.00
自引率
6.20%
发文量
35
期刊介绍: The Journal of Echocardiography, the official journal of the Japanese Society of Echocardiography, publishes work that contributes to progress in the field and articles in clinical research as well, seeking to develop a new focus and new perspectives for all who are concerned with this discipline. The journal welcomes original investigations, review articles, letters to the editor, editorials, and case image in cardiovascular ultrasound, which will be reviewed by the editorial board. The Journal of Echocardiography provides the best of up-to-date information from around the world, presenting readers with high-impact, original work focusing on pivotal issues.
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