International Journal of Chronic Obstructive Pulmonary Disease

CT in COPD: From Early Detection to Prognostic Biomarkers and Treatable Traits

Although spirometry remains essential for the diagnosis and physiological assessment of Chronic obstructive pulmonary disease (COPD), it provides limited information on the underlying structural changes and biological heterogeneity of the disease. Computed tomography (CT) has therefore emerged as an important tool for characterizing pulmonary and extrapulmonary abnormalities across the COPD spectrum. CT can identify emphysema, air trapping, airway remodeling, mucus plugging, bronchiectasis, pulmonary vascular changes, and alterations in body composition, some of which may be present before overt airflow obstruction develops. Advances in quantitative CT, parametric response mapping, radiomics, and artificial intelligence further enable objective assessment of disease burden and subtle structural abnormalities, creating new opportunities for earlier disease recognition, refined phenotyping, and more precise characterization of COPD beyond conventional spirometric measures.

COPD is frequently underrecognized in its early stages, while conventional spirometry alone may not adequately capture the structural abnormalities and biological heterogeneity that contribute to disease progression and adverse outcomes. CT imaging offers a unique opportunity to detect clinically relevant abnormalities that may precede overt airflow obstruction, quantify disease burden, and identify distinct structural phenotypes associated with different trajectories and prognoses. Importantly, the value of CT extends beyond disease characterization. Imaging-derived biomarkers may improve prediction of lung function decline, exacerbations, hospitalization, and mortality, while selected CT features may represent clinically actionable or potentially treatable traits. With the rapid development of quantitative imaging, radiomics, and artificial intelligence, CT is increasingly positioned to bridge structural abnormalities with biological mechanisms and clinical outcomes. Defining how these imaging features can be translated into risk stratification and therapeutic decision-making is therefore essential for advancing precision medicine and improving the management of COPD.

This Article Collection will focus on advances in CT imaging across the spectrum of COPD, particularly its potential roles in early disease recognition, phenotyping, prognostic assessment, and precision management. Topics of interest include CT-based identification of early structural abnormalities and pre-COPD; quantitative assessment of emphysema, air trapping, small airway disease, airway remodeling, mucus plugging, bronchiectasis, pulmonary vascular abnormalities, and body composition (keletal muscle, adipose tissue, sarcopenia, ectopic fat); as well as emerging applications of radiomics, artificial intelligence, and automated image analysis. Studies evaluating CT-derived biomarkers in relation to lung function decline, disease progression, exacerbations, hospitalization, mortality, and treatment response are particularly encouraged. We also welcome research exploring imaging-defined actionable or treatable traits and the integration of CT with clinical characteristics, pulmonary function, circulating biomarkers, genetics, proteomics, or other omics data for individualized risk stratification. Original research and review articles are particularly encouraged.

Keywords

• Chronic obstructive pulmonary disease
• Computed tomography
• Imaging biomarkers
• Early disease detection
• Treatable traits

­­All manuscripts submitted to this Article Collection will undergo a full peer-review; the Guest Advisor for this Collection will not be handling the manuscripts (unless they are an Editorial Board member).

Please review the journal scope and author submission instructions prior to submitting a manuscript.

The deadline for submitting manuscripts is 30 June 2027.

Please contact Zhiyuan Zhang at zhiyuan.zhang@taylorandfrancis.com with any queries and discount codes regarding this Article Collection.

Guest Advisors

Zhenyu Liang is a Professor of Respiratory Medicine at the First Affiliated Hospital of Guangzhou Medical University and Guangzhou Institute of Respiratory Health. My research focuses on chronic obstructive pulmonary disease (COPD), particularly clinical heterogeneity, quantitative CT imaging, disease phenotyping, and risk stratification. I am actively involved in clinical and translational research exploring imaging and other biomarkers for the characterization and prognostic assessment of COPD. My research interests also include early disease identification and precision approaches to COPD management.

Fengyan Wang focuses on CT imaging biomarkers, phenotyping, and clinical outcomes in chronic obstructive pulmonary disease (COPD), with particular interest in early-stage disease identification and intervention. Her work integrates quantitative imaging and multidimensional evaluation to better understand disease heterogeneity and progression.  Her research has covered airway mucus plugs, extrapulmonary CT lesions, emphysema-related prognosis, and pulmonary vascular pruning in COPD.

Lifei Lu is a clinical researcher specializing in chronic obstructive pulmonary disease (COPD), with a particular focus on small airway dysfunction and early disease identification. My research applies clinical epidemiology and population-based data analysis to investigate the development, progression, and long-term outcomes of COPD and pre-COPD. I am also interested in the epidemiology, prognostic impact, and integrated management of COPD-related comorbidities and multimorbidity.