Quantitative Computed Tomography in Asthma: For Good Measure

Assessment of Treatment Response in Patients With Severe Asthma Using Visual and Quantitative Analysis of Chest CT

OBJECTIVE

To evaluate the role of visual and quantitative chest CT parameters in assessing treatment response in patients with severe asthma.

MATERIALS AND METHODS

Korean participants enrolled in a prospective multicenter study, named the Precision Medicine Intervention in Severe Asthma study, from May 2020 to August 2021, underwent baseline and follow-up chest CT scans (inspiration/expiration) 10-12 months apart, before and after biologic treatment. Two radiologists scored bronchiectasis severity and mucus plugging extent. Quantitative parameters were obtained from each CT scan as follows: normal lung area (normal), air trapping without emphysema (AT without emph), air trapping with emphysema (AT with emph), and airway (total branch count, Pi10). Clinical parameters, including pulmonary function tests (forced expiratory volume in 1 s [FEV1] and FEV1/forced vital capacity [FVC]), sputum and blood eosinophil count, were assessed at initial and follow-up stages. Changes in CT parameters were correlated with changes in clinical parameters using Pearson or Spearman correlation.

RESULTS

Thirty-four participants (female:male, 20:14; median age, 50.5 years) diagnosed with severe asthma from three centers were included. Changes in the bronchiectasis and mucus plugging extent scores were negatively correlated with changes in FEV1 and FEV1/FVC (ρ = from -0.544 to -0.368, all P < 0.05). Changes in quantitative CT parameters were correlated with changes in FEV1 (normal, r = 0.373 [P = 0.030], AT without emph, r = -0.351 [P = 0.042]), FEV1/FVC (normal, r = 0.390 [P = 0.022], AT without emph, r = -0.370 [P = 0.031]). Changes in total branch count were positively correlated with changes in FEV1 (r = 0.349 [P = 0.043]). There was no correlation between changes in Pi10 and the clinical parameters (P > 0.05).

CONCLUSION

Visual and quantitative CT parameters of normal, AT without emph, and total branch count may be effective for evaluating treatment response in patients with severe asthma.

Mild asthma: Lessons learned and remaining questions

Patients living with mild disease represent the largest proportion of asthma patients. There are significant challenges in proposing a definition that would best describe these patients, while also accurately identifying at-risk individuals. Current literature suggests considerable inflammatory and clinical heterogeneity within this group. Research has shown that these patients are at risk of poor control, exacerbations, lung function decline, and death. Despite conflicting data on its prevalence, eosinophilic inflammation appears to be a predictor of poorer outcomes in mild asthma. There is an immediate need to better understand phenotypic clusters in mild asthma. It is also important to understand factors that influence disease progression and remission, as it is evident that both vary in mild asthma. Guided by robust literature that supports inhaled corticosteroid-based strategies over short-acting beta-agonist (SABA) reliant regimens, the management of these patients has evolved considerably. Unfortunately, SABA use remains high in clinical practice despite strong advocacy from the Global Initiative for Asthma. Future mild asthma research should explore the role of biomarkers, develop prediction tools based on composite risk scores, and explore targeted therapies at least for at-risk individuals.

Heterogeneity of Airway Smooth Muscle Remodeling in Asthma

Rationale: Ventilatory defects in asthma are heterogeneous and may represent the distribution of airway smooth muscle (ASM) remodeling. Objectives: To determine the distribution of ASM remodeling in mild-severe asthma. Methods: The ASM area was measured in nine airway levels in three bronchial pathways in cases of nonfatal (n = 30) and fatal asthma (n = 20) and compared with control cases without asthma (n = 30). Correlations of ASM area within and between bronchial pathways were calculated. Asthma cases with 12 large and 12 small airways available (n = 42) were classified on the basis of the presence or absence of ASM remodeling (more than two SD of mean ASM area of control cases, n = 86) in the large or small airway or both. Measurements and Main Results: ASM remodeling varied widely within and between cases of nonfatal asthma and was more widespread and confluent and more marked in fatal cases. There were weak correlations of ASM between levels within the same or separate bronchial pathways; however, predictable patterns of remodeling were not observed. Using mean data, 44% of all asthma cases were classified as having no ASM remodeling in either the large or small airway despite a three- to 10-fold increase in the number of airways with ASM remodeling and 81% of asthma cases having ASM remodeling in at least one large and small airway. Conclusions: ASM remodeling is related to asthma severity but is heterogeneous within and between individuals and may contribute to the heterogeneous functional defects observed in asthma. These findings support the need for patient-specific targeting of ASM remodeling.

Quantitative CT Image-Based Structural and Functional Changes during Asthma Acute Exacerbations

Asthma acute exacerbations (AE) have been investigated using quantitative computed tomography (QCT)-based imaging metrics, but QCT has not yet been used to investigate a comprehensive set of imaging metrics during AE. This study aims to explore imaging features, captured both at segmental and parenchymal scales, during asthma AE, compared to stable asthma (SA). Two sets of the QCT images at total lung capacity (TLC) and functional residual capacity (FRC) were captured for 14 subjects during asthma AE and in SA phase, respectively. We calculated airway wall thickness (WT), hydraulic diameter (D_h), and airway circularity (Cr) of the 36 segmental airways, percentage of functional small airway disease (fSAD%), percentage of emphysema, tissue fraction (β_tiss), and coefficient of variation of β_tiss (CV of β_tiss). We performed Spearman correlation tests for changes in QCT metrics and pulmonary function tests, measured in AE and SA. During asthma AE, structural metrics, i.e., WT, D_h, and Cr, were not changed significantly. In functional metrics, CV of β_tiss at FRC indicating the heterogeneity of lung tissue distribution was significantly increased, while the mean of β_tiss at FRC did not change during AE. An increase of fSAD% during AE was most correlated with a decrease of forced expiratory volume in 1 second and forced vital capacity, especially in the lower lobes. This study demonstrates that the heterogeneous feature of β_tiss measured at lower lobes is more noticeable during asthma AE, compared with other traditional imaging metrics. This metric could be utilized to identify unique features during asthma AE.