Imaging of COVID-19: An update of current evidences

Abstract

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been reported as a global emergency. As respiratory dysfunction is a major clinical presentation of COVID-19, chest computed tomography (CT) plays a central role in the diagnosis and management of patients with COVID-19. Recent advances in imaging approaches using artificial intelligence have been essential as a quantification and diagnostic tool to differentiate COVID-19 from other respiratory infectious diseases. Furthermore, cardiovascular involvement in patients with COVID-19 is not negligible and may result in rapid worsening of the disease and sudden death. Cardiac magnetic resonance imaging can accurately depict myocardial involvement in SARS-CoV-2 infection. This review summarizes the role of the radiology department in the management and the diagnosis of COVID-19, with a special emphasis on ultra-high-resolution CT findings, cardiovascular complications and the potential of artificial intelligence.

Keywords: Artificial intelligence; COVID-19; Cardiac magnetic resonance; Computed tomography; Pulmonary embolism.

Fig. 1

Flowchart for the CT examination. CT = computed tomography; COVID-19 = coronavirus disease 2019; HEPA = high efficiency particulate air; RT = radiological technologist.

Fig. 2

Schematic of CT suite in the setting of the patient infected with SARS-CoV-2. CT = computed tomography; MD = medical doctor; P = patient; PPE = personal protective equipment; RT = radiological technologist; SARS-CoV-2 = severe acute respiratory syndrome coronavirus 2.

Fig. 3

Process and staff distribution in the CT scanning machines and console rooms during CT examination of the patient infected with SARS-CoV-2. CT = computed tomography; P = patient; RT = radiological technologist; SARS-CoV-2 = severe acute respiratory syndrome coronavirus 2.

Fig. 4

Serial change in ultra-high-resolution computed tomography images in a 69-year-old man with coronavirus disease 2019 pneumonia. (A) Five days after onset of symptom, ground glass opacity and reticulation are seen in the right lower lung. (B) Fourteen days after onset of symptom, consolidation worsened and linear opacities, indicating atelectasis, become apparent (thin arrows). Enlargement of pulmonary artery near the consolidation is detected (thick arrow). (C) Thirty-two day after onset of symptom, consolidation and atelectasis improved, but ground glass opacity remained. (D) Seven months after onset of symptom, CT reveals slight reticulation in the right lower lung. Enlargement of pulmonary artery improved.

Fig. 5

Ultra-high-resolution computed tomography images in an 80-year-old woman with COVID 19. (A) Magnified CT image in the sagittal plane shows ground glass opacities and linear opacity patchy in dorsal peripheral zone of the right lower lung. (B) Magnified CT image in the coronal plane shows the Reid's secondary lobules (arrows). The size of affected lobule (arrowheads) is smaller than that of unaffected lobules (arrows). Crazy-paving appearance is also clearly depicted.

Fig. 6

An 80-year-old man with coronavirus disease 2019 pneumonia. Thin-slab maximum intensity projection CT image (8-mm thickness) in the axial plane shows larger vessels in the affected lung (right upper lobe, arrows) than those in the less affected lung (left upper lobe).

Fig. 7

Acute pulmonary embolism in a 71-year-old man with coronavirus disease 2019. (A) CT image in the axial plane shows consolidation in the right lower lung, and ground glass opacity in the left lower lung (arrowheads). (B, C), CT images in the axial (B) and coronal (B) planes reveal contrast defect suspicious of thrombus in the right lower pulmonary artery (arrows).

Fig. 8

Myopericarditis in a 68-year-old man with coronavirus disease 2019. (A, B), CT images in the axial plane using lung (A) and mediastinal (B) windows reveal peripheral and bilateral consolidation and linear opacity in the lower lung (arrowheads, A) and a small amount of pericardial effusion was detected (arrows, B). (C), Cardiac magnetic resonance image (T1 mapping) shows elevated native T1 time in the anteroseptal-inferior wall (arrows), suggesting myocardial edema.

Fig. 9

Automated segmentation of lung disease by COVID-19 using artificial intelligence. Computer-based segmentation enables objective classification of lung lesions into four parts in a 76-year-old man with coronavirus disease 2019 pneumonia. (A)-(C): Two-dimensional CT segmentation images, (D): Three-dimensional CT segmentation image. Violet indicates normal lung parenchyma; green indicates ground glass opacity; blue indicates reticulation; orange indicates consolidation.