Phenotypic clusters on computed tomography reflects asthma heterogeneity and severity.

Taewoo Kim,Hye-Ryun Kang,Sang-Heon Cho,Sujeong Kim,Kwang Nam Jin,Sanghun Choi,Chang Hyun Lee

doi:10.1016/j.waojou.2022.100628

Abstract

BackgroundAsthma is a heterogeneous inflammatory airway disorder with various phenotypes. Quantitative computed tomography (QCT) methods can differentiate among lung diseases through accurate assessment of the location, extent, and severity of the disease. The purpose of this study was to identify asthma clusters using QCT metrics of airway and parenchymal structure, and to identify associations with visual analyses conducted by radiologists.MethodsThis prospective study used input from QCT-based metrics including hydraulic diameter (Dh), luminal wall thickness (WT), functional small airway disease (fSAD), and emphysematous lung (Emph) to perform a cluster analysis and made comparisons with the visual grouping analysis conducted by radiologists based on site of airway involvement and remodeling evaluated.ResultsA total of 61 asthmatics of varying severities were grouped into 4 clusters. From C1 to C4, more severe lung function deterioration, higher fixed obstruction rate, and more frequent asthma exacerbations were observed in the 5-year follow-up period. C1 presented non-severe asthma with increased WT, Dh of proximal airways, and fSAD. C2 was mixed with non-severe and severe asthmatics, and showed bronchodilator responses limited to the proximal airways. C3 and C4 included severe asthmatics that showed a reduced Dh of the proximal airway and diminished bronchodilator responses. While C3 was characterized by severe allergic asthma without fSAD, C4 included ex-smokers with high fSAD% and Emph%. These clusters correlated well with the grouping done by radiologists and clinical outcomes.ConclusionsFour QCT imaging-based clusters with distinct structural and functional changes in proximal and small airways can stratify heterogeneous asthmatics and can be a complementary tool to predict clinical outcomes.

Highlights

The emphasis on the recognition of heterogeneity in asthma phenotypes has increased with the growing interest in personalized treatment
C2 was mixed with non-severe and severe asthmatics, and showed bronchodilator responses limited to the proximal airways
While C3 was characterized by severe allergic asthma without functional small airway disease (fSAD), C4 included ex-smokers with high fSAD% and emphysematous lung (Emph)%

Summary

Introduction

The emphasis on the recognition of heterogeneity in asthma phenotypes has increased with the growing interest in personalized treatment. Various histological abnormalities have often been observed in the asthmatic airway, including epithelial goblet cell hyperplasia, increased smooth muscle mass, bronchial wall thickening, subepithelial fibrosis, and angiogenesis.[1,2,3] Airway remodeling, an important component of asthma pathophysiology, is characterized by structural changes that occur in lungs and airways due to chronic airway inflammation.[4,5,6] Most studies investigating clustering analyses have focused on findings primarily obtained from endobronchial biopsies of asthmatics. The purpose of this study was to identify asthma clusters using QCT metrics of airway and parenchymal structure, and to identify associations with visual analyses conducted by radiologists

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