Lung perfusion changes in COVID-19 pneumonia: a dual energy computerized tomography study.

OBJECTIVE: There is limited and contradictory information about pulmonary perfusion changes detected with dual energy computed tomography (DECT) in COVID-19 cases. The purpose of this study was to define lung perfusion changes in COVID-19 cases with DECT, as well as to reveal any possible links between perfusion changes and laboratory findings. METHODS: Patients who had a positive RT-PCR for SARS-CoV-2 and a contrast-enhanced chest DECT examination were included in the study. The pattern and severity of perfusion deficits were evaluated, as well as the relationships between perfusion deficit severity and laboratory results and CT severity ratings. The paired t-test, Wilcoxon test, and Student's t-test were used to examine the changes in variables and perfusion deficits. p < 0.05 was regarded as statistically significant. RESULTS: Study population consisted of 40 patients. Mean age was 60.73 ± 14.73 years. All of the patients had perfusion deficits at DECT images. Mean perfusion deficit severity score of the population was 8.45 ± 4.66 (min.-max, 1-19). In 24 patients (60%), perfusion deficits and parenchymal lesions matched completely. In 15 patients (37.5%), there was partial match. D dimer, CRP levels, CT severity score, and perfusion deficit severity score all had a positive correlation. CONCLUSIONS: Perfusion deficits are seen not only in opacification areas but also in parenchyma of normal appearance. The CT severity score, CRP, D-dimer, and SpO2 levels of the patients were determined to be related with perfusion deficit severity. ADVANCES IN KNOWLEDGE: Findings of the current study may confirm the presence of micro-thrombosis in COVID-19 pneumonia.

Computed tomography at every step: Long coronavirus disease.

BACKGROUND: Some patients continue to experience symptoms related to Coronavirus disease (COVID-19) after the acute phase of infection. Imaging studies, especially computed tomography (CT) of the chest, have gained importance since the beginning of the pandemic. CT can help diagnose COVID-19, assess the extent of pulmonary involvement, and predict the disease severity. We aimed to define the frequency of persistent symptoms and correlate their presence with the results of laboratory findings and the severity of the disease based on the findings of chest CT. METHODS: We examined patients discharged from the hospital after treatment for COVID-19 and whose nasopharyngeal swab sample tested positive for severe acute respiratory syndrome coronavirus 2 after at least 4 weeks from the initial diagnosis. The patients were asked about the presence of persisting symptoms. In addition to the demographic data, laboratory results and severity levels seen on the chest CT were recorded. RESULTS: In all, 116 patients were included in the study, of which 61 reported at least one persisting symptom (52.5%). The mean age of the study population was 48.90 ± 17.74 years. The persistent symptoms included shortness of breath, chest pain, cough, muscle weakness, dizziness, headache, fatigue, and palpitations. The mean CT severity score was 3.80 ± 0.38 and it was lower in patients without any persistent symptoms. CONCLUSIONS: Levels of C-reactive protein and fibrinogen, anemia, and female sex were associated with some of the persistent symptoms., the severity of the disease seen on CT was a successful predictor for the disease severity/prognosis and was also correlated with prolonged COVID infection and more persistent symptoms.