计算机辅助诊断在乳腺成像报告和数据系统超声波培训的应用 - - 一项随机对照研究
Shuyi Lyu1,2, Meiwu Zhang1, Baisong Zhang1
1Department of Ultrasound, Ningbo No. 2 Hospital, Ningbo, China.
Translational cancer research
|May 13, 2024
概括
计算机辅助诊断 (CAD) 显著提高了放射科住院医生的乳腺成像报告和数据系统 (BI-RADS) 分类技能. 通过CAD辅助的培训提高了与专家评估的一致性,并提高了居民对BI-RADS的信心.
科学领域:
- 医疗成像医学成像
- 放射学教育 放射学教育
- 人工智能在医学中的应用
背景情况:
- 乳腺成像报告和数据系统 (BI-RADS) 的分类一致性在经验丰富的放射科医生之间有所不同,这给学员带来了挑战.
- 掌握BI-RADS对于准确的乳腺癌诊断和患者管理至关重要.
研究的目的:
- 评估计算机辅助诊断 (CAD) 系统 (AI-SONIC) 在培训放射科住院医生 BI-RADS 分类方面的有效性.
- 评估CAD对居民诊断准确度,与专家意见一致性以及信心水平的影响.
主要方法:
- 12名居民被随机分为三组接受BI-RADS培训:独立研究,CAD辅助研究和专家指导的指导.
- 居民完成了培训前后测试和问卷,以评估分数,一致性和信心.
- 性能与高级放射科医生进行了比较.
主要成果:
- 所有组都在培训后有所改善,但CAD辅助 (组2) 和专家领导 (组3) 的培训比独立研究 (组1) 获得的得分要高得多.
- CAD和专家领导的培训改善了住院人员与高级放射科医生的一致性 (κ > 0.4),而独立研究只显示了公平的协议 (κ = 0.225).
- 居民报告对BI-RADS分类的信心增加,对使用CAD作为学习辅助工具的满意度和意愿很高.
结论:
- AI-SONIC CAD系统有效地帮助放射科住院人员掌握BI-RADS分类.
- CAD培训增强了居民和专家之间的读者间一致性,并提高了居民的信心.
- 人工智能-SONIC系统显示了在标准化BI-RADS培训的潜在价值,为放射科的住院人员.
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