妊娠期COVID-19病人的临床特征、CT表现及AI分析  

Clinical characteristics,CT findings and AI application in pregnant women with COVID-19 pneumonia

作　　者：吴小青 谢元亮[1] 张树桐 陈建普 王翔[1] WU Xiaoqing;XIE Yuanliang;ZHANG Shutong;CHEN Jianpu;WANG Xiang(Department of Radiology,The Central Hospital of Wuhan,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430000,China)

机构地区：[1]华中科技大学同济医学院附属武汉市中心医院放射科,武汉430000

出　　处：《国际医学放射学杂志》2020年第3期262-266,共5页International Journal of Medical Radiology

摘　　要：目的分析妊娠期患新型冠状病毒肺炎(COVID-19)病人的临床及影像特征,并探讨人工智能(AI)在COVID-19诊断中的价值。方法回顾性纳入CT影像及临床资料完整的确诊COVID-19女性病人70例,年龄22~39岁,排除CT无异常表现的轻型病人。其中,30例病人处于妊娠期(妊娠组),平均年龄(29.4±4.7)岁,余40例病人为普通组,平均年龄(29.6±3.9)岁。记录全部病人的病灶特征、分布、累及肺叶、伴随征象等影像表现并进行AI分析。采用卡方检验、t检验或Wilcoxon检验比较2组临床资料及CT特征间的差异,采用Kappa检验分析AI与放射科医生对不同CT征象诊断的一致性。结果 2组病人临床分型均为普通型。妊娠组无临床症状感染者(21例,70%)多于普通组(4例,10%),且发热及其他症状(胸闷、胸痛、乏力等)少于普通组病人(均P<0.05)。妊娠组淋巴细胞百分比、中性粒细胞百分比、D-二聚体和C反应蛋白均高于普通组(均P<0.05)。妊娠组CT分期多为早期,普通组多为进展期(P<0.05)。2组病人CT特征比较,妊娠组单一磨玻璃密度影(GGO)更多,普通组多发GGO更多(均P<0.05),其他影像特征差异无统计学意义(P>0.05)。AI与放射科医生对大部分CT征象诊断的一致性良好(均κ>0.8),对外周区域和GGO病灶的诊断一致性一般(κ为0.41~0.80);对纤维条索的诊断一致性不佳(κ=0.268)。结论妊娠期COVID-19病人多无明显症状,其CT特征及实验室检查与普通COVID-19病人存在一定差异。AI可作为诊断COVID-19的辅助工具。Objective To analyze the clinical and radiological characteristics of COVID-19 patients in pregnancy,and to study the value of artificial intelligence(AI)in the diagnosis of COVID-19.Methods This study retrospectively included 70 female COVID-19 patients with CT images and complete clinical data,andthe range of ages were 22-39 years old.The mild COVID-19 patients with normal CT findings were excluded.All patients underwent AI analysis.Of them,30 patients were in pregnancy(age,29.4±4.7 years),the other 40 COVID-19 patients(age,29.6±3.9 years)were not in pregnancy(ordinary group).The CT characteristics(lesions,distribution,involvement of lung lobes,and accompanying signs)were recorded for each patient.Chi-square test and t test or Wilcoxon test were used to compare the clinical features and CT characteristics between the two groups.Kappa analysis wasused toanalyze the consistency of identifying CT characteristics between AI and radiologist.Results The clinical manifestations in the two groups were common type.The pregnant group presented more mild symptoms than the ordinary group:Nosymptoms,21 cases,70%vs 4 cases,10%and less cases with fever and other symptoms(oppression or pain in the chest,fatigue,etc.)(P<0.05).Lymphocyte percentage and neutrophil granulocyte rate,D-dimer and C-reactive protein were higher in the pregnant group than in the ordinary group(P<0.05).Based on CT appearances,thepregnant group was mostly in early stage,and the ordinary group was mostly in progressive stage(P<0.05).Comparing the CT characteristics of the patients in the two groups,there was more single ground-glass opacity(GGO)in the pregnant group and multiple GGO in the ordinary group(P<0.05),the other CT features did not statistically differ between the two groups(P>0.05).CT characteristics identified by AI and radiologist agreed well(κ>0.8),the diagnostic consistency of the identifying peripheral area and GGO were general(κ=0.41-0.80),while the consistency of identifying fibrous stripes was poor(κ=0.268).Conclusions COVID-19pati

关 键 词：新型冠状病毒肺炎 妊娠 体层摄影术 X线计算机 人工智能 

分 类 号：R445.4[医药卫生—影像医学与核医学] R816.4[医药卫生—诊断学]