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不同年龄人群新型冠状病毒感染CT表现分析

Analysis of Chest Computed Tomography Manifestations of Coronavirus Disease 2019 in Different Age Groups
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摘要 目的:分析不同年龄人群新型冠状病毒感染(COVID-19)胸部CT影像特征,提高对不同年龄人群COVID-19影像表现的认识。方法:回顾性分析476例COVID-19的胸部CT资料,男275例,女201例,按照不同年龄段分为A组(0~45岁)33人、B组(45~60岁)72人、C组(60~75岁)203人、D组(75岁以上)168人,共4组,比较4组病例胸部CT病灶累及肺叶侧别、数目、密度和病灶分布等CT基本征象及基于深度学习的病灶体积、体积占比和密度等的差异。结果:476例COVID-19患者均有流行病学史,性别在各组间差异无统计学意义。4组病例双肺下叶病灶最为多见,A组病灶多位于单侧肺,C组和D组病灶以双肺分布多见。各组病灶体积、体积占比随年龄增大呈递增趋势,且分布均以双肺下叶为主,其中A、C和D组均以右肺下叶最为常见且体积及体积占比最大,B组以左肺下叶病灶体积及占比较大;与A组比较,C组各项指标增大,差异均有统计学意义,且右肺下叶病灶体积与B组比较差异有统计学意义;D组左肺上叶病灶体积与A组比较明显增大,占比较A组和B组明显增大,余D组全肺及右肺上叶、中叶、下叶及左肺下叶病灶体积及体积占比较A、B和C组均明显增大,且差异有统计学意义。病灶均以磨玻璃密度影及实变为主,A组以纯磨玻璃密度最多见,混合磨玻璃密度次之,实变密度少见;D组病灶以实变密度较多见,大多呈混合磨玻璃密度;B和C组纯磨玻璃、混合磨玻璃、实变密度病灶出现情况介于A组和D组之间;各组病灶密度均以磨玻璃密度为主,CT值区间以-570~-470 HU及-470~-370 HU为主,D组各CT值区间病灶体积均较A、B和C组高,体积占比均较A组高且差异有统计学意义。结论:本组研究COVID-19患者均有流行病学史,熟悉不同年龄人群胸部CT特征可使临床诊疗工作更具针对性,可为COVID-19病情监测以及个体化防治措施提供参考。 Objective:This study aimed to analyze the chest computed tomography(CT)imaging features of coronavirus disease 2019(COVID-19)in people of different ages and improve the understanding of the imaging manifestations of COVID-19.Methods:Chest CT data of 476 cases with COVID-19 were retrospectively analyzed,including 275 males and 201 females.The patients were divided into four groups according to different age groups:groups A(0~45 years old)33,B(45~60 years old)72,C(60~75 years old)203,and D(over 75 years old)168.A comparison was made between the four groups of patients with chest CT lesions involving lobe side,number and density,distribution,and other basic CT signs,as well as differences in lesion volume,volume proportion,and density based on deep learning.Results:All the 476 patients with COVID-19 had an epidemiological history,and there was no statistically significant difference in sex between the groups.The lesions in the lower lobes of both lungs were the most common in the four groups.The lesions in group A were mostly located in the unilateral lung,while those in groups C and D were mostly distributed in both lungs.The volume and proportion of lesions increased with age in each group,and the distribution was mainly in the lower lobe of both lungs.In groups A,C,and D,the right lower lobe was the most common and had the largest volume and proportion,while in group B,the left lower lobe had the largest volume and proportion.Compared with group A,all indexes of group C increased,and the difference was statistically significant;the lesion volume of the right inferior lobe of the lung was statistically significant compared with group B.The volume of lesions in the left upper lobe of the lung in group D was significantly increased compared with that in groups A and B,and the volume and proportion of lesions in the whole lung,upper,middle,and lower lobes of the right lung,and the lower lobe of the left lung in group D were significantly increased compared with that in groups A,B and C,and the difference was statistically significant.In group A,the density of pure ground glass was the most common,followed by the density of mixed ground glass,and the density of solid change was rare.The solid density of lesions in group D was more common,most of which showed mixed ground glass density.The incidence of pure ground glass,mixed ground glass,and solid density lesions was higher in groups B and C than that in groups A and D.The lesion density in each group was mainly ground glass density,and the CT value ranged from-570 to-470 HU and-470 to-370 HU.The lesion volume in each CT value range of group D was higher than that in groups A,B,and C,and the volume proportion was higher than that in group A,and the difference was statistically significant.Conclusion:All patients with COVID-19 in this group have an epidemiological history.Being familiar with chest CT features of people of different ages can make clinical diagnosis and treatment more targeted and provide a reference for COVID-19 disease monitoring and individualized prevention and treatment measures.
作者 赵建华 梁丹艳 王晓兰 柴军 ZHAO Jianhua;LIANG Danyan;WANG Xiaolan;CHAI Jun(Department of Imaging Medical,the People’Hospital of Inner Mongolia Autonomous Region,Hohhot 010017,China;Statistics Office of Quality Control Division,the People’Hospital of Inner Mongolia Autonomous Region,Hohhot 010017,China;Inner Mongolia Clinical Medical College of Inner Mongolia Medical University/Inner Mongolia Clinical Medical College of Baotou Medical College,Hohhot 010017,China;Graduate School of Baotou Medical College,Inner Mongolia University of Science and Technology,Baotou 014040,China)
出处 《CT理论与应用研究(中英文)》 2023年第5期603-611,共9页 Computerized Tomography Theory and Applications
基金 内蒙古自治区人民医院院内基金项目(基于深度学习的病毒性肺炎不同临床转归胸部CT评价(2020YN08)) 包头医学院研究生教育教学改革项目(人工智能在放射影像学专业学位研究生教学中的初步应用(BYJSJG202303)) 内蒙古自治区卫生健康科技计划项目(超高分辨率CT靶扫描技术联合低剂量对诊断亚实性肺结节的价值(202201015)) 内蒙古医科大学2023年度高等教育教学改革研究项目(“人工智能+教学”模式在医学影像学专业教学中的应用探索(NYJXGG2023139))。
关键词 体层摄影术 X线计算机 新型冠状病毒感染 tomography X-ray computed coronavirus disease 2019
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