Objective To identify the main computed tomography (CT) features that may help distinguishing a progression of interstitial lung disease (ILD) secondary to Systemic sclerosis (SSc) from COVID-19 pneumonia. Methods This multicentric study included 22 international readers divided in the radiologist group (RAD) and non-radiologist group (nRAD). A total of 99 patients, 52 with COVID-19 and 47 with SSc-ILD, were included in the study. Results Fibrosis inside focal ground glass opacities (GGO) in the upper lobes; fibrosis in the lower lobe GGO; reticulations in lower lobes (especially if bilateral and symmetrical or associated with signs of fibrosis) were the CT features most frequently associated with SSc-ILD. The CT features most frequently associated with COVID- 19 pneumonia were: consolidation (CONS) in the lower lobes, CONS with peripheral (both central/peripheral or patchy distributions), anterior and posterior CONS and rounded-shaped GGOs in the lower lobes. After multivariate analysis, the presence of CONS in the lower lobes (p < 0.0001) and signs of fibrosis in GGO in the lower lobes (p < 0.0001) remained independently associated with COVID-19 pneumonia or SSc-ILD, respectively. A predictive score was created which resulted positively associated with the COVID-19 diagnosis (96.1% sensitivity and 83.3% specificity). Conclusion The CT differential diagnosis between COVID-19 pneumonia and SSc-ILD is possible through the combination the proposed score and the radiologic expertise. The presence of consolidation in the lower lobes may suggest a COVID-19 pneumonia while the presence of fibrosis inside GGO may indicate a SSc-ILD.

Background: Granulomatous and Lymphocytic Interstitial Lung Diseases (GLILD) is a severe non-infectious complication of Common Variable Immunodeficiency (CVID), often associated with extrapulmonary involvement. Due to a poorly understood pathogenesis, GLILD diagnosis and management criteria still lack consensus. Accordingly, it is a relevant cause of long-term loss of respiratory function and is closely associated with a markedly reduced survival. The aim of this study was to describe clinical, immunological, laboratory and functional features of GLILD, whose combination in a predictive model might allow a timely diagnosis.Methods: In a multicenter retrospective cross-sectional study we enrolled 73 CVID patients with radiologic features of interstitial lung disease (ILD) associated to CVID (CVID-ILD) and 125 CVID patients without ILD (controls). Of the 73 CVID-ILD patients, 47 received a definite GLILD diagnosis while 26 received a clinical-radiologic diagnosis of CVID related ILD defined as uILD.Results: In GLILD group we found a higher prevalence of splenomegaly (84.8 vs. 39.2%), autoimmune cytopenia (59.6 vs. 6.4%) and bronchiectasis (72.3 vs. 28%), and lower IgA and IgG serum levels at CVID diagnosis. GLILD patients presented lower percentage of switched-memory B cells and marginal zone B cells, and a marked increase in the percentage of circulating CD21lo B cells (14.2 vs. 2.9%). GLILD patients also showed lower total lung capacity (TLC 87.5 vs. 5.0%) and gas transfer (DLCO 61.5 vs. 5.0%) percent of predicted. By univariate logistic regression analysis, we found IgG and IgA levels at CVID diagnosis, presence of splenomegaly and autoimmune cytopenia, CD21lo B cells percentage, TLC and DCLO percent of predicted to be associated to GLILD. The joint analysis of four variables (CD21lo B cells percentage, autoimmune cytopenia, splenomegaly and DLCO percent of predicted), together in a multiple logistic regression model, yielded an area under the ROC curve (AUC) of 0.98 (95% CI: 0.95-1.0). The AUC was only slightly modified when pooling together GLILD and uILD patients (0.92, 95% CI: 0.87-0.97).Conclusions: we propose the combination of two clinical parameters (splenomegaly and autoimmune cytopenia), one lung function index (DLCO%) and one immunologic variable (CD21lo%) as a promising tool for early identification of CVID patients with interstitial lung disease, limiting the use of aggressive diagnostic procedures.

The aim of this study was to evaluate the regional (i.e. myocardial segments) variability as well as the overall image quality of cardiac T1 and T2 maps obtained in diastole and in systole. In 22 healthy subjects (group-1), diastolic T1 and T2 maps were obtained at 1.5 T in short-axis view at basal, mid-ventricular and apical level, as well as in 4-chamber (4 ch) and in 2-chamber (2 ch) views. In another group of 25 patients (group-2), the maps were obtained in both diastole and systole. In the group-1, 15.4% of myocardial segments in T1 maps and 0.8% of myocardial segments in T2 maps, mainly located at apical level, showed relevant artifacts and/or partial-volume effect and had to be discarded. We found no significant difference in T1 values among basal, mid-ventricular and apical segments. T2 values at apical level were significantly higher than at basal and mid-ventricular level (short-axis, p < 0.0001; 4 ch, p < 0.009; 2 ch, p = 0.0002 at ANOVA tests). In the group-2, 21.1%/5.3% and 4.0%/0.8% of segments showed relevant artifacts in diastolic/systolic T1 and T2 maps, respectively. Apical T2 values were significantly lower in systole than in diastole. In systole, there were no significant differences in T1/T2 among basal, mid-ventricular and apical segments. The overall quality of T1 and T2 maps drops in apical segments. This could be problematic when evaluating focal myocardial changes. The acquisition in systole increases the number of evaluable segments.

Background: Chest computed tomography (CT) is the gold standard for the evaluation of systemic sclerosis-related interstitial lung disease (SSc-ILD). Lung ultrasound (LUS) is a radiation-free tool that identifies the B-lines as a main feature of ILD. We aimed to investigate the role of LUS in the evaluation of the extent of SSc-ILD. Methods: Adult SSc patients underwent pulmonary function tests (PFTs), LUS and CT. The CT images were qualitatively, semi-quantitatively (the Wells score on five levels and the categorical Goh et al. staging) and quantitatively (histogram-based densitometry) analysed for ILD. LUS quantified B-lines in 21 intercostal spaces on both the anterior and posterior chest wall. Results: Out of the 77 SSc patients eligible for the study, 35 presented with ILD on CT (21 limited, 14 extensive). Total B-lines significantly differentiated ILD vs. no ILD (median 24 vs. 8, p < 0.001). Posterior and total B-lines significantly differentiated limited from absent ILD, while anterior B-lines distinguished extensive from limited ILD. Total B-lines correlated with the Wells score (r = 0.446, p < 0.001) and MLA (r = −0.571, p < 0.001); similar results were confirmed when anterior and posterior B-lines were analysed separately. Conclusions: LUS is a useful tool to identify SSc-ILD and to correlate with different evaluations of ILD extent and severity.