人工智能对检测可操作的肺癌在胸部X射线图上的有效性
Hyun Joo Shin1, Se Hyun Kwak2, Kyeong Yeon Kim2
1Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Republic of Korea.
Translational lung cancer research
|January 20, 2025
概括
人工智能 (AI) 在胸部X射线 (CXR) 上检测可操作的肺癌方面表现有前途,识别了86%的可见癌症. 人工智能的有效性随着病变的大小和特定位置的增加而增加,有助于早期诊断.
科学领域:
- 医疗成像医学成像
- 人工智能在医学中的应用
- 在瘤学瘤学.
背景情况:
- 早期发现肺癌对于治疗成功至关重要.
- 胸部放射 (CXR) 是广泛可用的,但在检测可操作的肺癌方面存在局限性.
- 人工智能 (AI) 具有提高医学成像诊断准确性的潜力.
研究的目的:
- 评估基于人工智能的胸部放射图 (CXR) 分析对检测可手术的肺癌的有效性.
- 评估影响AI在CXR上检测肺癌的能力的因素.
主要方法:
- 从594名肺癌手术患者的手术前CXR回顾性分析.
- 使用商业AI损伤检测软件进行CXR分析.
- 放射科医生和肺科医生审查了AI的发现,CT扫描作为参考标准.
主要成果:
- 人工智能在CXR上检测肺癌的灵敏度为57.7%,识别了86%的可见癌症.
- 随着疾病阶段 (IB:86.3%,II-III:90.9%) 和结节大小 (>1厘米) 的不同,检测率有所改善.
- 人工智能检测与上区域 (OR 2.78) 和外围 (OR 4.59) 位置以及固体结节直径 (OR 1.20) 有意义地相关.
结论:
- 基于AI的CXR分析可以成为识别可操作的肺癌的有效工具.
- 人工智能在检测较大的病变以及上部和外围肺部区域的病变方面表现特别强大.
- 人工智能可以通过改善胸部放射图的解释来提高肺癌的早期检测.
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