基于人工智能的决策支持系统在托尔瓦普坦处方中对自身主导性多囊性病的可行性
Jung Hyun Shin1, Ye Hyun Kim2, Myung Kyu Lee2
1Department of Urology, Ewha Womans University Mokdong Hospital, Seoul, Korea.
Investigative and clinical urology
|June 21, 2023
概括
一个新的AI驱动的3D体积模型准确地测量了自身主导多性病 (ADPKD) 患者的总体体积. 该工具支持对托尔瓦普坦治疗的临床决策,并预测疾病的进展.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 精确的总体积 (TKV) 测量对于管理自身主导性多囊性病 (ADPKD) 来说至关重要.
- 选择适合的候选人治疗像托尔瓦普坦依赖于精确的TKV评估.
- 目前的方法可能耗时或缺乏标准化.
研究的目的:
- 在ADPKD中开发和验证用于TKV测量的全自动化3D体积模型.
- 将该模型集成到用于临床决策支持的软件即服务 (SaaS) 平台中.
- 帮助托尔瓦普坦为ADPKD患者开处方.
主要方法:
- 利用计算机断层扫描 (CT) 扫描来自七个机构的753名ADPKD患者.
- 开发了一个基于卷积神经网络的自动细分模型,用于3D膜生成.
- 应用了三步算法:预处理,ADPKD面积提取和TKV计算后处理.
- 使用Dice分数验证性能,并基于梅奥成像分类集成到基于SaaS平台.
主要成果:
- 人工智能模型获得了0.971的高子得分,在后处理后提高到0.979.
- 交点超过联盟 (IoU) 超过了0.95,表明与地面真相面具的差异微不足道.
- 该SaaS平台成功计算了TKV,并根据高度调整的TKV根据年龄对患者进行了分类.
- 后处理有效地消除了假阳性细分.
结论:
- 与人类专家相比,开发的AI-3D体积模型展示了有效,可行和不劣的性能.
- 该模型准确地测量TKV,并有助于预测ADPKD的快速进展.
- 这种自动化方法为ADPKD的临床管理和治疗选择提供了有价值的工具.
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