Diagnostic value of chest CT scanning for determination of Covid-19 severity in individual lung lobes.

INTRODUCTION AND OBJECTIVE: CT examination is an important diagnostic tool in assessment of the severity of the infection and course of the disease. The aim of the study was to evaluate the degree and frequency of involvement of individual lung lobes and the population Lobe Involvement Coefficient (pLIC) value in the investigated population. MATERIAL AND METHODS: The analyzed material comprised 124 patients aged 18-92 years. CT examinations were performed using a 16- and 32-row CT LightSpeed apparatus. The spatial distribution of typical Covid -19 pathological changes was analyzed, divided into five lung lobes. The degree of the severity of lobe involvement was assessed using counters and percentages, as well as the population Lobe Involvement Coefficient (pLIC). Statistical analysis of data was performed with the use of Statistica 10.0 software. Values were measured on an oridinal scale. Anova Friedman's test was used to compare lobes. RESULTS: Statistically significant differences in the involvement between most of the individual lobes were shown. There was no statistically significant difference in the degree of lobe involvement between the left and right upper lobes, nor in the left and right lower lobes. The highest pILC was demonstrated for the lower lobe and the lowest value was obtained for the middle lobe. CONCLUSIONS: The lower lobes were affected most frequently and most severely, with no statistical difference between the right and left sides. The middle lobe was affected relatively least frequently and lightly. The introduced pLIC index allows quantitative assessment of individual lobes involvement in relation to the entire studied population.

Ischaemic background of brain fog in long-haul COVID-19 - a nuclear magnetic resonance spectroscopy-based metabonomic analysis. Preliminary results.

PURPOSE: Long-haul COVID-19 is a condition of unknown background occurring in COVID-19 survivors regardless of the severity of the SARS-CoV-2 infection itself. The aim of the study was to evaluate brain changes in patients suffering from variable symptoms of brain fog after COVID-19. MATERIAL AND METHODS: Eleven patients hospitalized due to symptoms of severe brain fog, i.e. insomnia, sudden impairment of cognitive function, headache, and depression, and 14 healthy volunteers underwent brain imaging including MR spectroscopy. RESULTS: Routine MR imaging revealed no specific macroscopic changes in keeping with brain fog. Considering that the clinical manifestation of brain fog is transient, the evaluation of the metabolic status of the brain remained the method of choice. The concentration of the major cerebral metabolites, i.e. NAA, Cho, and Cr, remained stable. However, changes in Glx and Lac concentration were observed in MR spectroscopy. CONCLUSIONS: Following results along with clinical course of the brain for imply probable ischaemic background of symptoms.

Chest Computed Tomography (CT) as a Predictor of Clinical Course in Coronavirus Disease.

BACKGROUND Chest imaging may be taken into consideration in detecting viral lung infections, especially if there are no tests available or there is a need for a prompt diagnosis. Imaging modalities enable evaluation of the character and extent of pulmonary lesions and monitoring of the disease course. The aim of this study was to verify the prognostic value of chest CT in COVID-19 patients. MATERIAL AND METHODS We conducted a retrospective review of clinical data and CT scans of 156 patients with SARS-CoV-2 infection confirmed by real-time reverse-transcription polymerase-chain-reaction (rRT-PCR) assay hospitalized in the Central Clinical Hospital of the Ministry of the Interior in Warsaw and in the Medical Centre in Lancut, Poland. The total severity score (TSS) was used to quantify the extent of lung opacification in CT scans. RESULTS The dominant pattern in discharged patients was ground-glass opacities, whereas in the non-survivors, the dominant pulmonary changes were consolidations. The non-survivors were more likely to have pleural effusion, pleural thickening, lymphadenopathy, air bronchogram, and bronchiolectasis. There were no statistically significant differences among the 3 analyzed groups (non-survivors, discharged patients, and patients who underwent prolonged hospitalization) in the presence of fibrotic lesions, segmental or subsegmental pulmonary vessel enlargement, subpleural lines, air bubble sign, and halo sign. CONCLUSIONS Lung CT is a diagnostic tool with prognostic utility in COVID-19 patients. The correlation of the available clinical data with semi-quantitative radiological features enables evaluation of disease severity. The occurrence of specific radiomics shows a positive correlation with prognosis.