呈现异常临床特征的多肌痛类风湿症患者仍然表现出特有的F-FDG PET/CT发现
Emily Martin1, Christopher R McMaster1,2, Aurora Mt Poon3
1Department of Rheumatology, Austin Health, Heidelberg, VIC, Australia.
European journal of nuclear medicine and molecular imaging
|December 5, 2025
概括
F-FDG PET/CT扫描显示了异型多发性肌痛性风湿症 (PMR) 的特征发现,但吸收量减少. 人工智能 (AI) 在这些情况下可靠地识别PMR,帮助诊断.
科学领域:
- 核医学是一种核医学.
- 放射学 放射学是指放射学
- 人工智能在医学中的应用
背景情况:
- 多发性肌痛风湿症 (PMR) 诊断可能具有挑战性,特别是在具有非典型临床特征的患者中.
- 用低剂量计算机断层扫描 (F-FDG PET/CT) 进行的F-氧葡萄糖正子发射断层扫描在风湿学中是一种有价值的成像方式.
研究的目的:
- 评估F-FDG PET/CT在诊断非典型PMR患者中的实用性.
- 为了比较非典型的PMR病例中的F-FDG PET/CT发现与典型的PMR患者中的发现.
- 用F-FDG PET/CT图像评估用于PMR诊断的AI模型的性能.
主要方法:
- 用自然语言处理对F-FDG PET/CT报告进行回顾性分析.
- 临床诊断确认和患者分层到临床诊断的确认和患者分层.
- 这是一个典型的典型的典型.
- 或或或或或或或或或或
- 不典型的非典型的
- 根据2012年EULAR/ACR标准建立了PMR组.
- 在未使用类固醇的患者中,对F-FDG摄入量的定性和半定量 (SUVmax) 分析.
- 在非典型的队列图像上测试ResNet50 AI模型,使用GradCam可视化.
主要成果:
- 十七个未使用过类固醇的非典型PMR病例与35个未使用过类固醇的典型PMR病例进行了比较.
- 在不同组的关键肌肉骨部位中观察到类似的异常频率.
- 与非典型队列相比,典型的PMR队列中平均SUVmax显著更高.
- 在非典型队列中,人工智能模型在诊断PMR时达到94.1%的准确性 (16/17个案例).
结论:
- 在非典型情况下,F-FDG PET/CT 显示出特征性的PMR 发现,尽管其放射性追踪器性降低.
- 人工智能技术在可靠地检测PMR成像模式方面表现有前途,即使是在非典型的呈现中.
- F-FDG PET/CT和AI可以帮助诊断具有挑战性的PMR病例.
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