在多囊性病中使用人工智能的人造形方法和体测量方法之间的比较
Jihyun Yang1, Young Rae Lee2, Young Youl Hyun1
1Division of Nephrology and Hypertension, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul 03181, Republic of Korea.
Journal of personalized medicine
|August 27, 2025
概括
人工智能 (AI) 体积测量为多囊病患者测量体积 (TKV) 提供了可靠和有效的替代方案. 这种人工智能方法与专家的测量结果强烈一致,改善了临床管理.
科学领域:
- 肝脏病学
- 医学成像
- 人工智能
背景情况:
- 梅奥诊所对多囊性病的成像分类 (MIC) 取决于总体积 (TKV) 的评估.
- 目前的TKV测量方法,如使用计算机断层扫描 (CT) 的圆形方法,是繁且不准确的.
- 需要在临床环境中改进可访问的TKV评估技术.
研究的目的:
- 将手动圆体积测量与基于AI的体积测量用于PKD患者的精度和效率进行比较.
- 评估人工智能体积学在治疗PKD中的临床效用.
主要方法:
- 在基于人工智能的体测量中使用了基于卷积神经网络的细分模型 (3D动态U-Net).
- 在32名PKD患者中,手动圆体和AI体积测量方法进行了比较.
- 在统计分析中使用了类间相关系数 (ICC) 和布兰德-阿尔特曼图.
主要成果:
- 人工智能体积测量与专家手工测量有很高的相关性 (教授的ICC为0.991,临床医生为0.983).
- 人工智能和专家测量之间的平均差异在统计学上是微不足道的.
- 人工智能体积测量在梅奥诊所系统中提供了一致的分类,类似于圆形方法.
结论:
- 基于人工智能的体测量是PKD中TKV评估的可靠,高效的替代方案.
- 这项技术可以帮助管理PKD并优化治疗结果.
- 人工智能体积测量为临床实践提供了评估体积的宝贵工具.
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