人工智能工具在轴性脊椎关节炎成像评估中的性能:系统文献综述和元分析
Dominique Rosillon1, Manouk de Hooge2, Thomas Van Den Berghe3
1DESiRE-consulting, Sorée, Belgium.
Joint bone spine
|February 1, 2026
概括
人工智能 (AI) 在解释轴性脊柱关节炎 (axSpA) 图像方面表现出有希望的表现. 然而,在 axSpA 检测中,人类专业知识对于准确的诊断和患者安全至关重要.
科学领域:
- 医学成像分析 医学成像分析
- 医疗保健中的人工智能
- 风湿病学 诊断 诊断 风湿病学
背景情况:
- 人工智能 (AI) 提供了先进的功能,以提高轴性脊柱关节炎 (axSpA) 图像解释的检测,准确性和效率.
- 该研究的重点是将人工智能技术的性能与axSpA的各种成像模式中的人类读者进行比较.
研究的目的:
- 系统地审查和总结AI在解释axSpA的成像模式方面的表现.
- 将人工智能驱动的解释与人类读者在使用MRI,CT和CR诊断axSpA时的表现进行比较.
主要方法:
- 使用PubMed和Scopus进行了遵循PRISMA指南的系统文献审查.
- 包括2010年1月至2025年6月期间发表的研究,通过元分析分析了绩效指标.
- 用DerSimonian-Laird随机效应模型对主体和图像水平的总体估计进行了评估,Higgins I2.2评估了异质性.
主要成果:
- 包括在2020-2025年间发表的33项研究,主要来自亚洲 (67%) 和利用深度学习 (85%) 在MRI (64%) 上.
- 人工智能展示了高的整体性能:灵敏度87%,特异性80%,准确度84%,在主体层面上AUC为0.88.
- 在图像层面观察到类似的性能指标,表明一致的AI能力.
结论:
- 近年来,评估用于axSpA成像的AI的研究显著增加.
- 人工智能在axSpA解释方面表现出强的表现,但人类专家的参与仍然对诊断准确性和临床安全至关重要.
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