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. 2021 Jan-Feb;63(1):56-73.
doi: 10.1016/j.rx.2020.11.001. Epub 2020 Nov 24.

Radiologic diagnosis of patients with COVID-19

[Article in English, Spanish]
Affiliations

Radiologic diagnosis of patients with COVID-19

[Article in English, Spanish]
E Martínez Chamorro et al. Radiologia (Engl Ed). 2021 Jan-Feb.

Abstract

The pandemia caused by the SARS-CoV-2 virus has triggered an unprecedented health and economic crisis. Although the diagnosis of infection with SARS-CoV-2 is microbiological, imaging techniques play an important role in supporting the diagnosis, grading the severity of disease, guiding treatment, detecting complications, and evaluating the response to treatment. The lungs are the main organ involved, and chest X-rays, whether obtained in conventional X-ray suites or with portable units, are the first-line imaging test because they are widely available and economical. Chest CT is more sensitive than plain chest X-rays, and CT studies make it possible to identify complications in addition to pulmonary involvement, as well as to suggestive alternative diagnoses. The most common radiologic findings in COVID-19 are airspace opacities (consolidations and/or ground-glass opacities), which are typically bilateral, peripheral, and located primarily in the lower fields.

La pandemia por el virus SARS-CoV-2 ha desencadenado una crisis económica y sanitaria sin precedentes. Aunque el diagnóstico es microbiológico, las técnicas de imagen tienen un papel importante para apoyar el diagnóstico, graduar la gravedad de la enfermedad, guiar el tratamiento, detectar posibles complicaciones y valorar la respuesta terapéutica. La afectación es principalmente pulmonar. La radiografía de tórax en sala convencional o portátil es el primer método de imagen por su amplia disponibilidad y bajo coste. La tomografía computarizada torácica tiene una mayor sensibilidad que la radiografía de tórax y permite valorar tanto la afectación pulmonar como posibles complicaciones, además de proporcionar diagnósticos alternativos. Los hallazgos radiológicos más frecuentes son las opacidades del espacio aéreo en forma de consolidaciones y/u opacidades en vidrio deslustrado, con distribución típicamente bilateral, periférica y de predominio en los campos inferiores.

Keywords: COVID-19; Chest X-rays; Computed tomography; Diagnosis; Diagnóstico; Radiografía de tórax; Tomografía computarizada.

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Figures

Figure 1
Figure 1
False positives or pitfalls. (A and B) Chest X-ray with poor inspiration. A 38-year-old woman with signs and symptoms raising suspicion of COVID-19. (A) Posteroanterior chest X-ray. Bilateral increase in density, predominantly in the middle and lower fields, raising suspicion of COVID-19 pneumonia (arrow tips). Poor inspiration (7 posterior costal arches are identified) and voluminous breasts. (B) Same patient. Repeat chest X-ray a few minutes after forced inspiration, wherein all above-mentioned findings are no longer seen (note the change in the morphology of the cardiac silhouette). (C) Artefact due to high breast density. An 18-year-old woman with signs and symptoms raising suspicion of COVID-19. Bilateral symmetrical opacities in lower fields due to highly dense breast tissue (arrows). Negative PCR results for SARS-CoV-2.
Figure 2
Figure 2
Typical findings in COVID-19 pneumonia. (A) A 47-year-old woman with signs and symptoms raising suspicion of COVID-19. Posteroanterior (PA) chest X-ray. Reticular interstitial pattern with peripheral predominance (arrows). (B) Same patient as in image A. PA chest X-ray taken 3 days later. Positive PCR for SARS-CoV-2. Despite being taken with poorer inspiration, the X-ray shows faint rounded bilateral peripheral alveolar opacities (dotted arrows). (C) A 57-year-old male with dyspnoea and positive PCR for SARS-CoV-2. Bilateral peripheral opacities in upper, middle and lower fields (arrow tips). (D) A 45-year-old male with dyspnoea and COVID-19 confirmed by PCR. Anteroposterior chest X-ray showing multiple bilateral diffuse confluent areas of consolidation with extensive involvement of both lungs. Note the presence of two central venous lines, one left jugular and the other right subclavian (white arrows), and a gastrointestinal tube (black arrow).
Figure 3
Figure 3
Atypical findings in COVID-19 pneumonia. (A) Lobar pneumonia. A 28-year-old male with signs and symptoms consistent with COVID-19 and positive PCR for SARS-CoV-2. Chest X-ray in posteroanterior (PA) projection. Right upper lobe involvement (arrow). (B and C) Bilateral involvement and pleural effusion. A 17-year-old male with fever and positive PCR for SARS-CoV-2. PA (B) and lateral (C) chest X-ray. Faint bilateral infiltrates in lower fields (arrows) with minimal pleural effusion in the left posterior costodiaphragmatic sinus (arrow tip).
Figure 4
Figure 4
Methods for grading severity of pulmonary involvement secondary to COVID-19 by chest X-ray. (A) Grading method suggested by Borghesi et al., Using an upper horizontal line (lower edge of the aortic arch) and a lower horizontal line (lower edge of the right inferior pulmonary vein), 6 lung fields are obtained. Each field is assigned a score based on radiological findings: 0 if there are no findings; 1 if there are interstitial infiltrates; 2 if there are interstitial and alveolar infiltrates with an interstitial predominance; and 3 if there are interstitial and alveolar infiltrates with an alveolar predominance. The maximum score is 18. According to this grading system, in the case presented, the score would be: A = 2, B = 3, C = 3, D = 3, E = 3 and F = 3. Total score = 17/18. (B) Adaptation of the “Radiographic Assessment of Lung Edema” (RALE) method proposed by Warren et al., initially devised to grade the severity of acute pulmonary oedema. Using a vertical line (along the spine) and a horizontal line (along the lower edge of the left main bronchus), 4 quadrants are obtained. Each quadrant is assigned a score of 0–4 depending on the extent of consolidation or ground-glass opacities (0 = no findings; 1 < 25%; 2 = 25%–50%; 3 = 50%–75%; 4 > 75%). These scores must be multiplied by another score assigned to consolidation density (1 = incipient, 2 = moderate, 3 = dense). The maximum score is 48. According to this grading method, the example presented would be scored as follows: Q1 = 2 × 1 = 2; Q2 = 4 × 3 = 12; Q3 = 2 × 3 = 6, and Q4 = 2 × 3 = 6. Total score = 26/48. (C) Grading method used by Schalekamp et al.. This divides the thorax into 4 quadrants. Each quadrant is assigned a score of 0–2, where 0 = no involvement; 1 = medium/moderate involvement (0–50% of the lung parenchyma); and 2 = severe impairment (>50% of the parenchyma). Maximum score of 8. This example would be scored as follows: right upper quadrant = 1; right lower quadrant = 2; left upper quadrant = 1; left lower quadrant = 1. Total score = 5/8. This study found that scores averaging 4.4 ± 1.9 and bilateral involvement were associated with critical illness.
Figure 5
Figure 5
Tomosynthesis. A 30-year-old woman with COVID-19. (A) Conventional posteroanterior chest projection. Bilateral opacities in lower fields (arrows) that could correspond to dense breast tissue. Owing to uncertainties around the right hemithorax (arrows), a decision was made to perform a digital tomosynthesis (DT) study. (B and C) DT images. These show extensive consolidation in the right lower lung field (white circle in B), as well as small contralateral consolidations only visualised on DT (arrow tip in C) corresponding to foci of pneumonia. Reproduced courtesy of Dr J. Plasencia of Hospital General Universitario Morales Meseguer [Morales Meseguer University General Hospital] in Murcia, Spain.
Figure 6
Figure 6
Typical findings in COVID-19 pneumonia on computed tomography (CT). Axial chest CT images with 1-mm slices. (A) Ground-glass opacities with rounded morphology and a peripheral and subpleural distribution (arrows). (B) Consolidations with a peripheral and subpleural predominance (arrows). (C) Reticulation with a peripheral and subpleural location (arrow tips). (D) Peripheral ground-glass opacities with overlapping interlobular and intralobular septal thickening in relation to a crazy-paving pattern (arrow). Peripheral consolidation (asterisk) is also seen.
Figure 7
Figure 7
Typical findings in COVID-19 pneumonia on computed tomography (CT). Images from a CT scan of the chest with 1-mm slices. (A and B) Axial (A) and sagittal (B) images showing a lesion in the posterior segment of the right upper lobe with the reversed-halo sign (arrows). (C) Extensive ground-glass involvement with areas of consolidation in the right lower lobe with the vacuolar sign (arrow tips). (D) Abnormal architecture of the right lower lobe with a crazy-paving pattern and bronchial dilation (black arrow).
Figure 8
Figure 8
Typical findings in COVID-19 pneumonia on computed tomography (CT). Axial chest CT images with 1-mm slices. (A) Vascular thickening (arrow) associated with an area of ground-glass opacity (asterisk). (B) Subpleural curvilinear line (arrow). (C) Subpleural parenchymal bands (arrows). (D) Hypoattenuating line (arrows) between visceral pleura and ground-glass opacity (arrow tips).
Figure 9
Figure 9
Progression of COVID-19 pneumonia in a 56-year-old woman. Axial chest computed tomography (CT) images with a thickness of 1 mm at the level of the carina. (A) Study 10 days after the onset of symptoms. Peripheral and bilateral ground-glass opacities (arrow tips) and a small consolidation forming in the posterior segment of the right upper lobe (arrow). (B) CT scan 15 days after the first CT scan. Progression of ground-glass opacities to consolidations (arrows). (C) CT scan 32 days after the first CT scan. Partial resorption of consolidations (arrow tips) and focal pleural thickening in the apicoposterior segment of the left upper lobe (black arrow).
Figure 10
Figure 10
Semi-quantitative scales to assess the extent of lung lesions due to COVID-19 pneumonia with computed tomography. aUpper regions (1 and 4) above carina; middle regions (2 and 5) between carina and inferior pulmonary vein; lower regions (3 and 6) below inferior pulmonary vein. bLi et al. showed that the classification with a cut-off point of 7 had a sensitivity of 80% and a specificity of 82.8% for distinguishing between severely and mildly ill patients (area under the curve [AUC] 0.87). cWu et al. demonstrated that the pulmonary inflammation index (PII) is an independent indicator of disease progression and severity. The Chongqing Radiology Association of China uses it as an evaluation criterion. dWith a cut-off point of 24.5, the scale predicts mortality with a sensitivity of 85% and a specificity of 84%.

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