彻底改变膀健康:使用二维超声波对膀体积进行人工智能自动测量
Evan Avraham Alpert1,2, Daniel David Gold1,2, Deganit Kobliner-Friedman1
1Department of Emergency Medicine, Eisenberg R&D Authority, Shaare Zedek Medical Center, Jerusalem 9112001, Israel.
Diagnostics (Basel, Switzerland)
|August 29, 2024
概括
一个人工智能 (AI) 模块使用超声波准确测量膀体积 (BV),与手动测量有很强的相关性. 这种人工智能工具为诊断尿路疾病提供了一个可靠的,非侵入性的替代方案.
科学领域:
- 医疗成像医学成像
- 人工智能在医学中的应用
- 泌尿器科 泌尿器科 泌尿器科 泌尿器科
背景情况:
- 升高的空气后残留体积 (PVR) 对于诊断尿道外流管阻塞和尾巴马综合征至关重要.
- 传统的导管是侵入性的,并带有感染风险.
- 超声波为膀体积测量提供了一个安全,无痛和准确的替代方案.
研究的目的:
- 用2D超声波图像评估基于人工智能的膀体积 (BV) 测量的自动化模块的准确性.
- 为了比较人工智能驱动的BV测量与专家超声波专家的手动测量.
主要方法:
- 来自111名患者的横向和纵向膀超声图像的前性分析.
- 使用AI模块和前列圆形法进行自动化BV测量.
- 盲人专家超声波器手动测量BV,通过皮尔森相关性,卡帕系数和布兰德-阿尔特曼分析进行比较.
主要成果:
- 在基于AI的和手动的BV测量之间观察到非常强的相关性 (r = 0.97).
- 对于升高的PVR (≥200毫升) 的高诊断准确性:特异性为1.00,灵敏度为0.82.
- 方法之间几乎完美的一致性 (kappa = 0.85) 和出色的可重复性 (观察者之间和观察者内部).
结论:
- 基于人工智能的模块从超声波图像中准确测量膀体积.
- 这种新的自动化方法与黄金标准有很强的相关性.
- 人工智能工具是急性护理环境中非专家的有希望的决策支持系统.
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