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住院COVID-19患者的腹部计算机断层扫描成像结果:长达一年的经验及可解释人工智能揭示的关联

Abdominal Computed Tomography Imaging Findings in Hospitalized COVID-19 Patients: A Year-Long Experience and Associations Revealed by Explainable Artificial Intelligence.

作者信息

Scarabelli Alice, Zilocchi Massimo, Casiraghi Elena, Fasani Pierangelo, Plensich Guido Giovanni, Esposito Andrea Alessandro, Stellato Elvira, Petrini Alessandro, Reese Justin, Robinson Peter, Valentini Giorgio, Carrafiello Gianpaolo

机构信息

Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, 20122 Milan, Italy.

Department of Radiology, IRCCS Fondazione Cà Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy.

出版信息

J Imaging. 2021 Dec 1;7(12):258. doi: 10.3390/jimaging7120258.

Abstract

The aim of this retrospective study is to assess any association between abdominal CT findings and the radiological stage of COVID-19 pneumonia, pulmonary embolism and patient outcomes. We included 158 adult hospitalized COVID-19 patients between 1 March 2020 and 1 March 2021 who underwent 206 abdominal CTs. Two radiologists reviewed all CT images. Pathological findings were classified as acute or not. A subset of patients with inflammatory pathology in ACE2 organs (bowel, biliary tract, pancreas, urinary system) was identified. The radiological stage of COVID pneumonia, pulmonary embolism, overall days of hospitalization, ICU admission and outcome were registered. Univariate statistical analysis coupled with explainable artificial intelligence (AI) techniques were used to discover associations between variables. The most frequent acute findings were bowel abnormalities ( = 58), abdominal fluid ( = 42), hematomas ( = 28) and acute urologic conditions ( = 8). According to univariate statistical analysis, pneumonia stage > 2 was significantly associated with increased frequency of hematomas, active bleeding and fluid-filled colon. The presence of at least one hepatobiliary finding was associated with all the COVID-19 stages > 0. Free abdominal fluid, acute pathologies in ACE2 organs and fluid-filled colon were associated with ICU admission; free fluid also presented poor patient outcomes. Hematomas and active bleeding with at least a progressive stage of COVID pneumonia. The explainable AI techniques find no strong relationship between variables.

摘要

这项回顾性研究的目的是评估腹部CT检查结果与COVID-19肺炎、肺栓塞的影像学分期以及患者预后之间的任何关联。我们纳入了2020年3月1日至2021年3月1日期间158例接受了206次腹部CT检查的成年COVID-19住院患者。两名放射科医生对所有CT图像进行了复查。病理结果分为急性或非急性。确定了一组在ACE2器官(肠道、胆道、胰腺、泌尿系统)有炎症病理表现的患者。记录了COVID肺炎的影像学分期、肺栓塞、住院总天数、入住重症监护病房情况及预后。采用单变量统计分析结合可解释人工智能(AI)技术来发现变量之间的关联。最常见的急性表现为肠道异常(=58)、腹腔积液(=42)、血肿(=28)和急性泌尿系统疾病(=8)。根据单变量统计分析,肺炎分期>2与血肿、活动性出血及结肠积液频率增加显著相关。至少存在一项肝胆表现与所有>0期的COVID-19相关。腹腔游离液体、ACE2器官的急性病变及结肠积液与入住重症监护病房相关;游离液体也提示患者预后不良。血肿和活动性出血与至少进展期的COVID肺炎相关。可解释人工智能技术未发现变量之间有强关联。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b61/8704652/f5c0784f91fc/jimaging-07-00258-g001.jpg

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