摘要
目的:探讨冠脉CT血管成像(CTA)人工智能(AI)辅助阅片对不同年资规培医生工作效能的影响。方法:收集2022年6月—7月在梅州市人民医院接受冠脉CTA检查的44例患者。低、高年资规培医生采用单独阅片与AI辅助阅片判读冠脉CTA图像,并记录各支血管有无狭窄及阅片时长。以冠状动脉血管造影(CAG)为金标准,计算规培医生单独阅片与AI辅助阅片诊断冠脉狭窄的灵敏度和特异度;比较规培医生两种阅片方法诊断效能及阅片时长的差异性。结果:低、高年资规培医生应用冠脉CTA人工智能辅助阅片诊断冠脉狭窄的特异度高于单独阅片,且差异具有统计学意义(P<0.05),诊断冠脉狭窄的灵敏度稍高于单独阅片,但差异无统计学意义(P>0.05)。低、高年资规培医生应用冠脉CTA人工智能辅助阅片的阅片时长显著短于单独阅片(P<0.05)。结论:冠脉CTA人工智能能够提升低、高年资规培医生诊断冠脉狭窄的特异度,并显著缩短阅片时长。
Objective To explore the effect of coronary CT angiography(CTA)assisted by artificial intelligence(AI)on the work efficiency of resident-trained physicians with different years of training.Methods Forty-four patients who underwent coronary CTA examination in Meizhou People's Hospital from June 2022 to July 2022 were collected.Junior and senior resident-trained physicians used reading alone and AI-assisted reading to interpret coronary CTA images,and recorded the presence or absence of stenosis in each branch vessel and the reading time.The coronary angiogram(CAG)was used as a reference standard to calculate the sensitivity and specificity of coronary artery stenosis diagnosis by resident-trained physicians reading alone versus AI-assisted reading;Comparison of the diagnostic efficacy and reading time of two methods for reviewing medical films by resident-trained physicians.Results The specificity of coronary artery stenosis diagnosis by CTA AI-assisted reading was higher than that by reading alone,and the difference was statistically significant(P<0.05),and the sensitivity of coronary artery stenosis diagnosis was slightly higher than that by reading alone,but the difference was not statistically significant(P>0.05).The reading time of coronary CTA AI-assisted reading by junior and senior resident-trained physicians was significantly shorter than that of reading alone(P<0.05).Conclusion Coronary CTA artificial intelligence can improve the specificity of diagnosis of coronary artery stenosis and significantly shorten the reading time of resident physicians with different years of training.
作者
张添辉
钟正
黄志峰
范伟雄
ZHANG Tianhui;ZHONG Zheng;HUANG Zhifeng;FAN Weixiong(Department of Radiology,Meizhou People's Hospital,Meizhou,Guangdong 514031,China)
出处
《影像研究与医学应用》
2023年第16期11-14,共4页
Journal of Imaging Research and Medical Applications
基金
2021年度广东省临床教学基地教学改革研究项目“基于人工智能辅助诊断系统在放射科阅片教学中的应用”(2021JD198)。
关键词
冠状动脉
人工智能
住院医师
规范化培训
计算机断层扫描
Coronary artery
Artificial intelligence
Residency
Standardized training
Computed tomography
