摘要
目的:探讨人工智能(AI)与肺部低剂量CT(LDCT)联合应用于新型冠状病毒肺炎(COVID-19)中有效降低辐射剂量的可行性方案。方法:选取在医院就诊的216例COVID-19住院患者,采用随机数表法将其分为常规剂量CareDose模式的80150mAs组、低剂量CareDose模式的2150mAs组和人工固定低管电流模式的20mAs组,每组72例。3组患者扫描图像由AI阅片,并由3位高级职称的放射专家双盲评判图像质量和检出符合率;对比分析3组CT剂量指数(CTDI_(vol))、剂量长度乘积(DLP)和有效剂量(ED)。结果:2150mAs组图像主观评分和诊断符合率接近80150mAs组,且明显优于20mAs组。2150mAs组CTDI_(vol)、DLP和ED均显著低于80150mAs组,3组比较差异具有统计学意义(F=514.05,F=589.02,F=246.96;P<0.05)。结论:AI联合低剂量自动管电流调制技术能够显著降低COVID-19患者CT检查中的辐射剂量,且不影响诊断检出率。
Objective:To discuss the feasible plan of the combination of artificial intelligence(AI)and low-dose computed tomography(LDCT)on lung in the application of effective reducing radiation dose for patients with Coronavirus Disease 2019(COVID-19).Methods:216 inpatients with COVID-19 were selected and were randomly divided into three groups:80-150 mAs group with conventional dose CareDose mode,21-50 mAs group with low dose Care Dose mode and 20 mAs group with artificial fixed low tube current mode,with 72 cases in each group.The scanning images of patients in three groups were read by AI,and the image quality and detection coincidence rate were judged as double blind method by three senior radiologists.And the CT dose index(CTDI_(vol)),dose-length product(DLP)and diagnostic coincidence rate of the 21-50 mAs group closed to those of 80-150 mAs group and were significantly better than those of 20 mAs group,and the differences of those between the two groups were significant.And the CTDI_(vol),DLP and ED of 21-50 mAs group were significantly lower than those of 80-150 mAs group,and the differences of these indicators between 21-50 mAs group and 80-150 mAs,and between 21-50 mAs group and 20 mAs group(F=514.05,F=589.02,F=246.96,P<0.05),respectively.Conclusion:The combination of AI and low-dose automatic tube current modulation technique can significantly reduce the radiation dose of patients with COVID-19 in CT examination and does not affect the diagnostic detection ratel.
作者
李翔
张树桐
王翔
王曦
LI Xiang;ZHANG Shu-tong;WANG Xiang(The Central Hospital of Wuhan Affiliated to Tongji Medical College of Huazhong University of Science and Technology,Wuhan 430014,China)
出处
《中国医学装备》
2021年第4期180-183,共4页
China Medical Equipment
基金
武汉市新冠肺炎疫情防控应急科研专项(EX20C12)“低剂量CT联合AI应用COVID-19智能诊断”。