扩散加权成像在检测乳腺癌的附加值错过了基于人工智能的乳房造影
Jin You Kim1, Jin Joo Kim2, Ho Jun Lee2
1Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, 179, Gudeok-ro, Seo-gu, Busan, 49241, Republic of Korea. youdosa@naver.com.
La Radiologia medica
|December 1, 2025
概括
基于人工智能的计算机辅助诊断 (AI-CAD) 错过了30.7%的乳腺癌. 独立的扩散权重成像 (DWI) 在检测这些AI错过的癌症方面表现有前途,特别是在密集的乳房中.
科学领域:
- 放射学 放射学是一门学科.
- 医疗成像医学成像
- 医疗保健中的人工智能
背景情况:
- 基于人工智能的计算机辅助诊断 (AI-CAD) 越来越多地用于乳腺癌查.
- 然而,AI-CAD系统可以忽略某些乳腺癌.
研究的目的:
- 为了评估AI-CAD错过的乳腺癌.
- 为了确定与AI错过的乳腺癌相关的因素.
- 评估AI-CAD忽略的癌症独立扩散权重成像 (DWI) 的诊断价值.
主要方法:
- 对414名确诊患有乳腺癌的女性进行了回顾性分析.
- 根据AI-CAD的性能,将癌症分类为AI检测或AI错过.
- 两个放射科医生对AI错过的癌症进行了DWI的独立审查.
主要成果:
- AI-CAD错过了30.7% (127/414) 的乳腺癌.
- 密集的乳房和较小的瘤大小 (≤2厘米) 是AI错过的癌症的独立预测因素.
- 独立DWI检测了83.5%和79.5%的AI错过的癌症,与实质性的观察者之间的协议.
结论:
- 独立的DWI有效地检测出AI-CAD错过的大多数乳腺癌.
- DWI显示出在基于AI的查中作为选辅助的潜力,特别是在密集的乳房和乳房影像隐性病变方面.
- 需要进行未来的多中心试验来验证这些发现.
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