报告模式和临床经验对放射科医生的视线和图像分析行为在胸部X-ray X-ray 的影响
Mahta Khoobi1, Marc S von der Stück1, Felix Barajas Ordonez1
1Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Pauwelsstrasse 30, 52072 Aachen, Germany.
Radiology
|February 3, 2026
概括
结构化报告 (SR) 和AI预填写的SR (AI-SR) 改进了胸部X光学分析. AI-SR显著提高了诊断准确性,而SR和AI-SR都减少了报告时间和提高了阅读器效率.
科学领域:
- 放射学 放射学是一门学科.
- 医疗成像医学成像
- 人工智能在医学中的应用
背景情况:
- 结构化报告 (SR) 和人工智能 (AI) 为放射学工作流程提供了潜在的进步.
- 评估不同报告方法对放射科医生的表现的影响对于优化成像解释至关重要.
研究的目的:
- 评估自由文本报告,SR和AI预填 SR (AI-SR) 如何影响图像分析行为,诊断准确性,效率和胸部X射线图解读的用户体验.
- 为了在这些报告模式中比较新手和非新手读者的表现.
主要方法:
- 一项前性研究,涉及8名读者 (新手和非新手) 分析了35张胸部X光片,使用自由文本,SR和AI-SR模式.
- 用眼睛追踪技术来分析图像分析行为.
- 诊断准确性与专家的共识相比较,报告时间和用户满意度也被衡量.
主要成果:
- 与自由文本 (κ = 0.58) 和SR (κ = 0.60) (P <.001) 相比,AI-SR显示出更高的诊断准确性 (κ = 0.71).
- 与自由文本 (88s) 相比,SR和AI-SR都显著减少了报告时间 (SR: 37s,AI-SR: 25s) (P < .001).
- 眼睛追踪显示,SR和AI-SR减少了沙卡德计数和固定持续时间,表明效率提高.
结论:
- 结构化报告通过将视觉注意力集中在图像上来提高效率.
- 人工智能预先填写的结构化报告进一步提高了胸部放射图解读的诊断准确性.
- 新手和非新手读者都从AI-SR中受益,据报道,用户满意度很高.
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