完全自动化和人工智能辅助的人工智能基的CT定量表溢液变化的精度在胸腔切除后发生变化
Eui Jin Hwang1, Hyunsook Hong1, Seungyeon Ko1
1From the Department of Radiology (E.J.H., S.K., H.K., D.K., S.H.Y.) and Medical Research Collaborating Center (H.H.), Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea; Department of Radiology, Seoul National University College of Medicine (E.J.H., H.K., S.H.Y.), Seoul, Korea; Department of Radiology, Hanyang University Medical Center, Hanyang University College of Medicine, Seoul, Korea (S.J.Y.).
Radiology. Artificial intelligence
|January 15, 2025
概括
人工智能 (AI) 和人工辅助CT测量流量量变化系统地低估了排液. 这种差异需要在临床实践中仔细考虑.
科学领域:
- 医疗成像医学成像
- 人工智能在医学中的应用
- 胸部放射学 胸部放射学
背景情况:
- 在胸部CT时精确量化胸腔溢液变化对于疾病评估和治疗监测至关重要.
- 目前在CT扫描上测量胸膜溢出体积的方法存在局限性.
- 人工智能 (AI) 为自动化体积量化提供了潜力.
研究的目的:
- 评估基于人工智能的体积量化对CT扫描中的肺流变化的准确性.
- 为了比较基于人工智能的测量与人类辅助的测量以及排水流体的体积.
- 评估人工智能和人工辅助CT量化的可靠性和系统错误.
主要方法:
- 预计将招收79名接受胸腔切除术的参与者.
- 胸部CT扫描在液体排水之前和之后获得.
- 自动化AI细分用于初始体积测量,随后进行放射科医生校正 (人类辅助测量).
- 将CT衍生的排水量与实际排水流体体积进行比较.
主要成果:
- 完全自动化的人工智能和人工辅助测量都系统地低估了排水流体的体积.
- 低估误差与排放的流体体积成比例增加.
- 在测量方法之间和测量方法内观察到非常好的一致性 (ICC,0.99) 和测试复试可靠性 (ICC,0.9950.997).
- 估计最大95%的误差为自动测量708mL,人类辅助测量312mL.
结论:
- 基于人工智能细分的CT量化流体积变化,与实际体积变化相比,呈现出系统的差异.
- 人类辅助测量也显示了显著的低估,突出了当前基于CT的定量化的局限性.
- 需要进一步的研究来完善人工智能算法,并解决多流的CT量化中的系统错误.
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