Pal Aman, Ali Abulhassan, Young Timothy R, Oostenbrink Juan, Prabhakar Akul, Prabhakar Amogh, Deacon Nina, Arnold Amar, Eltayeb Ahmed, Yap Charles, Young David M, Tang Alan, Lakshmanan Subramanian, Lim Ying Yi, Pokarowski Martha, Kakodkar Pramath
School of Medicine, National University of Ireland Galway, Galway H91 TK33, Galway, Ireland.
Department of Computer Science, Yale University, New Haven, CO 06520, United States.
World J Radiol. 2021 Sep 28;13(9):258-282. doi: 10.4329/wjr.v13.i9.258.
Since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, over 103214008 cases have been reported, with more than 2231158 deaths as of January 31, 2021. Although the gold standard for diagnosis of this disease remains the reverse-transcription polymerase chain reaction of nasopharyngeal and oropharyngeal swabs, its false-negative rates have ignited the use of medical imaging as an important adjunct or alternative. Medical imaging assists in identifying the pathogenesis, the degree of pulmonary damage, and the characteristic features in each imaging modality. This literature review collates the characteristic radiographic findings of COVID-19 in various imaging modalities while keeping the preliminary focus on chest radiography, computed tomography (CT), and ultrasound scans. Given the higher sensitivity and greater proficiency in detecting characteristic findings during the early stages, CT scans are more reliable in diagnosis and serve as a practical method in following up the disease time course. As research rapidly expands, we have emphasized the CO-RADS classification system as a tool to aid in communicating the likelihood of COVID-19 suspicion among healthcare workers. Additionally, the utilization of other scoring systems such as MuLBSTA, Radiological Assessment of Lung Edema, and Brixia in this pandemic are reviewed as they integrate the radiographic findings into an objective scoring system to risk stratify the patients and predict the severity of disease. Furthermore, current progress in the utilization of artificial intelligence radiomics is evaluated. Lastly, the lesson from the first wave and preparation for the second wave from the point of view of radiology are summarized.
自2019年冠状病毒病(COVID-19)大流行爆发以来,截至2021年1月31日,已报告超过103214008例病例,死亡人数超过2231158人。尽管该疾病诊断的金标准仍然是鼻咽和口咽拭子的逆转录聚合酶链反应,但其假阴性率促使医学成像成为一种重要的辅助手段或替代方法。医学成像有助于确定发病机制、肺损伤程度以及每种成像方式的特征。这篇文献综述整理了COVID-19在各种成像方式中的特征性影像学表现,同时初步聚焦于胸部X线摄影、计算机断层扫描(CT)和超声扫描。鉴于CT扫描在疾病早期检测特征性表现方面具有更高的敏感性和更强的熟练度,在诊断中更可靠,并且是跟踪疾病病程的实用方法。随着研究迅速扩展,我们强调了CO-RADS分类系统作为一种工具,有助于医护人员交流COVID-19疑似病例的可能性。此外,还综述了在此次大流行中其他评分系统的应用,如MuLBSTA、肺水肿的放射学评估和布里夏评分,因为它们将影像学表现整合到一个客观评分系统中,对患者进行风险分层并预测疾病严重程度。此外,还评估了人工智能影像组学应用的当前进展。最后,总结了从放射学角度来看第一波疫情的经验教训以及对第二波疫情的准备情况。