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新型冠状病毒肺炎治愈病例的胸部 CT影像学变化与临床表现相关性分析
引用本文:吴炅,高才良,曾文兵,杨染,秦媛,李翔.新型冠状病毒肺炎治愈病例的胸部 CT影像学变化与临床表现相关性分析[J].安徽医药,2021,25(12):2403-2407.
作者姓名:吴炅  高才良  曾文兵  杨染  秦媛  李翔
作者单位:重庆大学附属三峡医院(重庆三峡中心医院)放射科,重庆404000
基金项目:中央高校“新型冠状病毒感染与防治”应急科研专项项目( 2020CDJYGRH-YJ03)
摘    要:目的 探讨新型冠状病毒肺炎(COVID-19)发病早期、进展期、转归期的胸部CT影像学动态变化与临床分型及表现的关系.方法 收集重庆大学附属三峡医院2020年1—2月88例治愈出院COVID-19病人的临床与影像学资料,其中出院诊断普通型51例,重型29例,危重型8例.每例病人做了(4±1)CT检查,范围为3~6次,每次检查间隔3~7 d,总共346次胸部CT.回顾性分析每例病人发病早期(1~7 d)、进展期(8~14 d)、转归期(>14 d)胸部CT影像学表现及变化.采用Kruskal-Wallis秩和检验(非正态分布)比较普通型、重型、危重型病人的年龄、发病至影像学好转天数、发病至出院天数差异.结果 COVID-19发病早期CT主要表现为双肺多叶多段(74/88,84%)、斑片状磨玻璃影(82/88,93%),以外带及胸膜下分布为主(374/492,76%);进展期双肺磨玻璃病灶逐渐增多、增大,密度增高,边缘变清晰,其内纹理增多、间质增厚,常出现"铺路石"征(29/88,33%)和"蜘蛛网"征(26/88,30%),斑片状实变影及条索影增多;转归期双肺磨玻璃及实变病灶逐渐吸收、减少,95%(84/88)的病人出院时双肺残留条索影、浅淡磨玻璃影或条网状间质纤维化病灶.普通型、重型、危重型病人的年龄中位数(四分位数间距)分别为47(7)、49(13)、69(20)岁,发病至影像学好转天数分别为13(6)、17(3)、24(9)d,发病至出院天数分别为18(5)、23(4)、29(4)d,三者均P<0.001.结论 胸部CT可以很好地观察COVID-19病人发病早期、进展期、转归期的影像学动态变化,COVID-19病人临床分型的严重程度与病人年龄、影像学及临床好转天数存在相关性.

关 键 词:新型冠状病毒肺炎(COVID-19)  胸部  放射摄影术  胸部  体层摄影术  X线计算机  体征和症状  呼吸系统

Analysis of correlation between chest CT imaging changes and clinical manifestations in cured cases of Corona Virus Disease 2019
WU Jiong,GAO Cailiang,ZENG Wenbing,YANG Ran,QIN Yuan,LI Xiang.Analysis of correlation between chest CT imaging changes and clinical manifestations in cured cases of Corona Virus Disease 2019[J].Anhui Medical and Pharmaceutical Journal,2021,25(12):2403-2407.
Authors:WU Jiong  GAO Cailiang  ZENG Wenbing  YANG Ran  QIN Yuan  LI Xiang
Institution:Department of Radiology, Chongqing University Three Gorges Hospital Chongqing Three Gorges Center Hospital, Chongqing 404000, China
Abstract:Objective To investigate the relationship between the dynamic changes of chest CT imaging in the early stage, progres.sive stage and prognosis stage of Corona Virus Disease 2019 (COVID-19) and its clinical classification and manifestation.Methods Clinical and imaging data of 88 cured and discharged COVID-19 patients in Chongqing University Three Gorges Hospital from Januaryto February 2020 were collected. Among them, 51 cases were diagnosed as normal type, 29 cases as heavy type and 8 cases as criticaltype. Each patient underwent (4±1) CT examinations ranging from 3 to 6 times, intervals of 3 to 7 days. There were a total of 346 chestCT scans. The chest imaging findings and changes of each patient in the early onset (1-7 d), progressive period (8-14 d), and transitionperiod (> 14 d) were retrospectively analyzed. The different in age, days of image improvement and days of discharge of normal, severeand critical type patients by Kruskal-Wallis rank sum test (non-normal distribution) were compared.Results In the early stage of CO. VID-19, CT mainly showed patchy ground glass opacity (82/88, 93%), in multiple lobes and segments of both lungs (74/88, 84%), main.ly in the outer zone and subpleural distribution (374/492, 76%). In progressive phase, ground glass lesions in both lungs gradually in.creased and enlarged, increased density, increased texture inside, interstitial thickening, "paving stone" sign (29/88, 33%) and "spiderweb" sign (26/88, 30%) often appear, patchy consolidation and cableway shadows increased. At discharge, 95% (84/88) patients had re.sidual stripe shadows, light ground glass opacity, or reticular interstitial fibrosis lesions in both lungs. The median age (quartile spac.ing) of patients with normal type, severe type and critical type were 47 (7), 49 (13) and 69 (20) years old, respectively. The days from on.set to radiological improvement were 13 (6), 17 (3) and 24 (9) d, respectively. The days from onset to discharge were 18 (5), 23 (4) and29 (4) d, respectively. P values of all three were < 0.001.Conclusions Chest CT can well observe the dynamic changes of imaging in the early, progression and recurrent stages of COVID-19 patients. The severity of clinical classification of COVID-19 patients is corre. lated with age, days of imaging and clinical improvement.
Keywords:Corona Virus Disease 2019 (COVID-19)  Thorax  Radiography  chest  Tomography  X-ray computer  Signs and symptoms  respiratory
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