Detection and Classification of Bronchiectasis Through Convolutional Neural Networks

Artificial Intelligence-based CT Assessment of Bronchiectasis: The COPDGene Study

Background CT is the standard method used to assess bronchiectasis. A higher airway-to-artery diameter ratio (AAR) is typically used to identify enlarged bronchi and bronchiectasis; however, current imaging methods are limited in assessing the extent of this metric in CT scans. Purpose To determine the extent of AARs using an artificial intelligence-based chest CT and assess the association of AARs with exacerbations over time. Materials and Methods In a secondary analysis of ever-smokers from the prospective, observational, multicenter COPDGene study, AARs were quantified using an artificial intelligence tool. The percentage of airways with AAR greater than 1 (a measure of airway dilatation) in each participant on chest CT scans was determined. Pulmonary exacerbations were prospectively determined through biannual follow-up (from July 2009 to September 2021). Multivariable zero-inflated regression models were used to assess the association between the percentage of airways with AAR greater than 1 and the total number of pulmonary exacerbations over follow-up. Covariates included demographics, lung function, and conventional CT parameters. Results Among 4192 participants (median age, 59 years; IQR, 52-67 years; 1878 men [45%]), 1834 had chronic obstructive pulmonary disease (COPD). During a 10-year follow-up and in adjusted models, the percentage of airways with AARs greater than 1 (quartile 4 vs 1) was associated with a higher total number of exacerbations (risk ratio [RR], 1.08; 95% CI: 1.02, 1.15; P = .01). In participants meeting clinical and imaging criteria of bronchiectasis (ie, clinical manifestations with ≥3% of AARs >1) versus those who did not, the RR was 1.37 (95% CI: 1.31, 1.43; P < .001). Among participants with COPD, the corresponding RRs were 1.10 (95% CI: 1.02, 1.18; P = .02) and 1.32 (95% CI: 1.26, 1.39; P < .001), respectively. Conclusion In ever-smokers with chronic obstructive pulmonary disease, artificial intelligence-based CT measures of bronchiectasis were associated with more exacerbations over time. Clinical trial registration no. NCT00608764 © RSNA, 2022 Supplemental material is available for this article. See also the editorial by Schiebler and Seo in this issue.

Profile of Clinical and Analytical Parameters in Bronchiectasis Patients during the COVID-19 Pandemic: A One-Year Follow-Up Pilot Study

Whether the COVID-19 pandemic may have modified the clinical planning and course in bronchiectasis patients remains to be fully elucidated. We hypothesized that the COVID-19 pandemic may have influenced the management and clinical outcomes of bronchiectasis patients who were followed up for 12 months. In bronchiectasis patients (n = 30, 23 females, 66 years), lung function testing, disease severity [FEV₁, age, colonization, radiological extension, dyspnea (FACED), exacerbation (EFACED)] and dyspnea scores, exacerbation numbers and hospitalizations, body composition, sputum microbiology, and blood analytical biomarkers were determined at baseline and after a one-year follow-up. Compared to baseline (n = 27, three patients dropped out), in bronchiectasis patients, a significant increase in FACED and EFACED scores, number of exacerbations, and erythrocyte sedimentation rate (ESR) was observed, while FEV₁, ceruloplasmin, IgE, IgG, IgG aspergillus, IgM, and IgA significantly decreased. Patients presenting colonization by Pseudomonas aeruginosa (PA) remained unchanged (27%) during follow-up. In bronchiectasis patients, FEV₁ declined only after a one-year follow-up along with increased exacerbation numbers and disease severity scores, but not hospitalizations. However, a significant decrease in acute phase-reactants and immunoglobulins was observed at the one-year follow-up compared to baseline. Despite the relatively small cohort, the reported findings suggest that lung function impairment may not rely entirely on the patients’ inflammatory status.

Do Redox Balance and Inflammatory Events Take Place in Mild Bronchiectasis? A Hint to Clinical Implications

We hypothesized that in mild bronchiectasis patients, increased systemic inflammation and redox imbalance may take place and correlate with clinical parameters. In plasma samples from patients with very mild bronchiectasis, inflammatory cells and molecules and redox balance parameters were analyzed. In the patients, lung function and exercise capacity, nutritional status, bacterial colonization, and radiological extension were assessed. Correlations between biological and clinical variables were determined. Compared to healthy controls, levels of acute phase reactants, neutrophils, IgG, IgA, myeloperoxidase, protein oxidation, and GSH increased and lung function and exercise capacity were mildly reduced. GSH levels were even greater in ex-smoker and Pseudomona-colonized patients. Furthermore, radiological extension inversely correlated with airway obstruction and, disease severity, and positively correlated with neutrophil numbers in mild bronchiectasis patients with no nutritional abnormalities. In stable patients with mild bronchiectasis, several important inflammatory and oxidative stress events take place in plasma. These findings suggest that the extension of bronchiectasis probably plays a role in the development of redox imbalance and systemic inflammation in patients with mild bronchiectasis. These results have therapeutic implications in the management of bronchiectasis patients.

Imaging in non-cystic fibrosis bronchiectasis and current limitations

Non-cystic fibrosis bronchiectasis represents a heterogenous spectrum of disorders characterised by an abnormal and permanent dilatation of the bronchial tree associated with respiratory symptoms. To date, diagnosis relies on computed tomography (CT) evidence of dilated airways. Nevertheless, definite radiological criteria and standardised CT protocols are still to be defined. Although largely used, current radiological scoring systems have shown substantial drawbacks, mostly failing to correlate morphological abnormalities with clinical and prognostic data. In limited cases, bronchiectasis morphology and distribution, along with associated CT features, enable radiologists to confidently suggest an underlying cause. Quantitative imaging analyses have shown a potential to overcome the limitations of the current radiological criteria, but their application is still limited to a research setting.

In the present review, we discuss the role of imaging and its current limitations in non-cystic fibrosis bronchiectasis. The potential of automatic quantitative approaches and artificial intelligence in such a context will be also mentioned.

Diagnosis and Initial Investigation of Bronchiectasis

Bronchiectasis refers to both the name of a disease and a single radiological appearance that may, or may not, be associated with disease. As chronic respiratory disease, bronchiectasis is characterized by a variable range of signs and symptoms that may overlap with other chronic respiratory conditions. The proper identification of bronchiectasis as a disease in both primary and secondary care is of paramount importance. However, a standardized definition of radiologically and clinically significant bronchiectasis is still missing. Disease heterogeneity is a hallmark of bronchiectasis and applies not only to radiological features and clinical manifestations but also to other aspects of the disease, including the etiological and microbiological diagnosis as well as the evaluation of pulmonary function. Although the guidelines suggest a "minimum bundle" of tests, the diagnostic approach to bronchiectasis is challenging and may be driven by the "treatable traits" approach based on endotypes and biological characteristics. A broad spectrum of diagnostic tests could be used to investigate the etiology of bronchiectasis as well as other pulmonary, extrapulmonary, and environmental traits. Individualizing bronchiectasis workup according to the site of care (e.g., primary, secondary, and tertiary care) could help optimize patients' management and reduce healthcare costs.