The role of computed tomography and the assessment of lung involvement with 3D-pulmo software in COVID-19 pneumonia: a case report.

A previously healthy 76-year-old woman with a history of five days of hyperpyrexia up to 40° was admitted to the emergency department because of dyspnea. At admission, her SpO2 was 78%. Laboratory findings showed high CRP (195.25 mg/L, normal range 1-5 mg/L) and LDH (359 U/L, normal value < 248 U/L), white blood cell count was normal. Elevation of D-dimer (1596,17 μgr/L; < 500 μgr/L threshold to exclude venous thromboembolism) and IL-6 (130 pgr/mL, normal value < 5.9 pgr/mL) were found as well. She was negative for Legionella and Streptococcus pneumonia; she was tested and found positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Because of the rapid deterioration of the clinical condition, the patient required mechanical ventilation and was admitted to intensive care.

A Computed Tomography (CT) examination was performed at admission, using a multi-detector CT scanner with 64 channels. The detailed parameters were: 120 kVp tube voltage; 100 mAs tube current; 1 mm slice thickness; 1 mm reconstruction interval; lung reconstruction algorithm. CT was acquired at full inspiration with the patient in the supine position and without contrast medium. The exam showed patchy bilateral ground-glass opacities (GGO) in the upper lobes mainly peripheral and associated with the thickness of interlobular and intralobular (“crazy paving” pattern); perilesional vascular thickening was seen. In the lower lobes, CT showed more consolidated areas with air bronchogram. Bronchus architectural distortion, traction bronchiectasis, and fibrous stripes were also found. No signs of pleural effusion or mediastinal lymphadenopathy. Evaluation with 3D-Pulmo software showed a 50% involvement of the total parenchyma.

Coronavirus disease-19 (COVID-19) is a viral respiratory infection caused by SARS-CoV-2 [1]. The infection has airborne transmission via droplets. Symptoms include tiredness, fever, dry cough, and shortness of breath [2]. COVID-19 can range from asymptomatic to severe pneumonia leading to acute respiratory distress syndrome (ARDS) and death from respiratory failure [1].

Diagnosis is based on the combination of a history of exposure, clinical characteristics and RT-PCR (real-time polymerase chain reaction) assay from specimens obtained by oropharyngeal or nasopharyngeal swab, bronchoalveolar lavage, or tracheal aspirate, followed by imaging examination [3].

Chest X-Ray is not sensitive in the early stage; during the rapid progression, hazy increased opacities and consolidations may be present [3].

CT has low specificity but high sensitivity in the detection of COVID-19. In the early stage, typical CT findings include multiple GGO, patchy consolidations, or crazy paving pattern. In the later phases of the disease, large consolidative opacities and contextual air bronchograms are present. Almost always, the CT manifestations are bilateral with involvement of more lobes (most frequently lower lobes), with predominantly peripheral distribution [4].

Architectural distortion, fibrous stripes, subpleural lines, vascular thickening, and reversed halo sign may be present. Mediastinal lymph-nodes enlargement and pleural effusion are rarely reported [5].

Distribution of pulmonary lesions and lung involvement grading on admission could be assessed automatically by deep learning quantitative CT. The percentage of well-aerated parenchyma defined by software may stratify the severity of the infection and could be an important radiological predictor of the patient’s outcome [6].

Patients positive for COVID-19 are isolated and treated with the highest standard of care; however, at present, there are still no "specific drugs" available [7].

Teaching points

CT imaging may be helpful in early detection of interstitial pneumonia in patients with high clinical suspicion for COVID-19 pneumonia and an initial negative or unknown RT-PCR. Furthermore, imaging may be helpful to assess the severity grade of lung’s involvement to stratify the severity of the infection and to monitor its course.