Chest computed tomography in severe bronchopulmonary dysplasia: Comparing quantitative scoring methods

PURPOSE

Bronchopulmonary dysplasia (BPD) is the most common complication of extreme preterm birth and structural lung abnormalities are frequently found in children with BPD. To quantify lung damage in BPD, three new Hounsfield units (HU) based chest-CT scoring methods were evaluated in terms of 1) intra- and inter-observer variability, 2) correlation with the validated Perth-Rotterdam-Annotated-Grid-Morphometric-Analysis (PRAGMA)-BPD score, and 3) correlation with clinical data.

METHODS

Chest CT scans of children with severe BPD were performed at a median of 7 months corrected age. Hyper- and hypo-attenuated regions were quantified using PRAGMA-BPD and three new HU based scoring methods (automated, semi-automated, and manual). Intra- and inter-observer variability was measured using intraclass correlation coefficients (ICC) and Bland-Altman plots. The correlation between the 4 scoring methods and clinical data was assessed using Spearman rank correlation.

RESULTS

Thirty-five patients (median gestational age 26.1 weeks) were included. Intra- and inter-observer variability was excellent for hyper- and hypo-attenuation regions for the manual HU method and PRAGMA-BPD (ICCs range 0.80-0.97). ICC values for the semi-automated HU method were poorer, in particular for the inter-observer variability of hypo- (0.22-0.71) and hyper-attenuation (-0.06-0.89). The manual HU method was highly correlated with PRAGMA-BPD score for both hyper- (ρs0.92, p < 0.001) and hypo-attenuation (ρs0.79, p < 0.001), while automated and semi-automated HU methods showed poor correlation for hypo- (ρs < 0.22) and good correlation for hyper-attenuation (ρs0.72-0.74, p < 0.001). Several scores of hyperattenuation correlated with the use of inhaled bronchodilators in the first year of life; two hypoattenuation scores correlated with birth weight.

CONCLUSIONS

PRAGMA-BPD and the manual HU method have the best reproducibility for quantification of CT abnormalities in BPD.

CT features of community-acquired pneumonia at the emergency department

BACKGROUND

Chest computed tomography (CT) was reported to improve the diagnosis of community-acquired pneumonia (CAP) as compared to chest X-ray (CXR). The aim of this study is to describe the CT-patterns of CAP in a large population visiting the emergency department and to see if some of them are more frequently missed on CXR.

MATERIALS AND METHODS

This is an ancillary analysis of the prospective multicenter ESCAPED study including 319 patients. We selected the 163 definite or probable CAP based on adjudication committee classification; 147 available chest CT scans were reinterpreted by 3 chest radiologists to identify CAP patterns. These CT-patterns were correlated to epidemiological, biological and microbiological data, and compared between false negative and true positive CXR CAP.

RESULTS

Six patterns were identified: lobar pneumonia (51/147, 35%), including 35 with plurifocal involvement; lobular pneumonia (43/147, 29%); unilobar infra-segmental consolidation (24/147, 16%); bronchiolitis (16/147, 11%), including 4 unilobar bronchiolitis; atelectasis and bronchial abnormalities (8/147, 5.5%); interstitial pneumonia (5/147, 3.5%). Bacteria were isolated in 41% of patients with lobar pneumonia-pattern (mostly Streptococcus pneumoniae and Mycoplasma pneumonia) versus 19% in other patients (p = 0.01). Respiratory viruses were equally distributed within all patterns. CXR was falsely negative in 46/147 (31%) patients. Lobar pneumonia was significantly less missed on CXR than other patterns (p = 0.003), especially lobular pneumonia and unilobar infra-segmental consolidation, missed in 35% and 58% of cases, respectively.

CONCLUSION

Lobar and lobular pneumonias are the most frequent CT-patterns. Lobar pneumonia is appropriately detected on CXR and mainly due to Streptococcus pneumoniae or Mycoplasma pneumoniae. Chest CT is very useful to identify CAP in other CT-patterns. Prior the COVID pandemic, CAP was rarely responsible for interstitial opacities on CT.