ArticleRespiratory research2018
Imaging-based clusters in current smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS).
Article in Respiratory research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01969344 (Subpopulations and Intermediate Outcome Measures in COPD Study), which is not on this map. Cited by 19 papers.
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Subpopulations and Intermediate Outcome Measures in COPD Study
Who cites it
19 citing papers in PubMed.
- Discriminative feature learning for multiclass lung disease classification using contrastive learning.Frontiers in radiology · 2026Article
- Assessment of ventilation heterogeneity and particle deposition in asthmatics using combined SPECT/CT imaging and computational modeling approaches.European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences · 2025Article
- Automated CT-based measurements of radial and longitudinal expansion of airways due to breathing-related lung volume change.Medical physics · 2025Article
- Longitudinal study of COPD phenotypes using integrated SPECT and qCT imaging.Frontiers in physiology · 2025Article
- Identification of Severe Acute Exacerbations of Chronic Obstructive Pulmonary Disease Subgroups by Machine Learning Implementation in Electronic Health Records.Chronic obstructive pulmonary diseases (Miami, Fla.) · 2024Article
- Exploratory Study on COPD Phenotypes and their Progression: Integrating SPECT and qCT Imaging Analysis.medRxiv : the preprint server for health sciences · 2024Article
- Investigating distributions of inhaled aerosols in the lungs of post-COVID-19 clusters through a unified imaging and modeling approach.European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences · 2024Article
- Direct estimation of regional lung volume change from paired and single CT images using residual regression neural network.Medical physics · 2023Article
- Radiomic phenotyping of the lung parenchyma in a lung cancer screening cohort.Scientific reports · 2023Article
- A computed tomography imaging-based subject-specific whole-lung deposition model.European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences · 2022Article
- Characterizing Subjects Exposed to Humidifier Disinfectants Using Computed-Tomography-Based Latent Traits: A Deep Learning Approach.International journal of environmental research and public health · 2022Article
- Contrastive learning and subtyping of post-COVID-19 lung computed tomography images.Frontiers in physiology · 2022Article
- Latent traits of lung tissue patterns in former smokers derived by dual channel deep learning in computed tomography images.Scientific reports · 2021Article
- A CT-Based Automated Algorithm for Airway Segmentation Using Freeze-and-Grow Propagation and Deep Learning.IEEE transactions on medical imaging · 2021Article
- Article
- LOCALLY ADAPTIVE HALF-MAX METHODS FOR AIRWAY LUMEN-AREA AND WALL-THICKNESS AND THEIR REPEAT CT SCAN REPRODUCIBILITY.Proceedings. IEEE International Symposium on Biomedical Imaging · 2020Article
- Review
- Imaging-based clusters in former smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and intermediate outcome measures in COPD study (SPIROMICS).Respiratory research · 2019Article
- Longitudinal Imaging-Based Clusters in Former Smokers of the COPD Cohort Associate with Clinical Characteristics: The SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS).International journal of chronic obstructive pulmonary diseaseArticle
Corrections and comments
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Authors and funding
20 authors.
Funding
Abstract
backgroundClassification of COPD is usually based on the severity of airflow, which may not sensitively differentiate subpopulations. Using a multiscale imaging-based cluster analysis (MICA), we aim to identify subpopulations for current smokers with COPD.
methodsAmong the SPIROMICS subjects, we analyzed computed tomography images at total lung capacity (TLC) and residual volume (RV) of 284 current smokers. Functional variables were derived from registration of TLC and RV images, e.g. functional small airways disease (fSAD%). Structural variables were assessed at TLC images, e.g. emphysema and airway wall thickness and diameter. We employed an unsupervised method for clustering.
resultsFour clusters were identified. Cluster 1 had relatively normal airway structures; Cluster 2 had an increase of fSAD% and wall thickness; Cluster 3 exhibited a further increase of fSAD% but a decrease of wall thickness and airway diameter; Cluster 4 had a significant increase of fSAD% and emphysema. Clinically, Cluster 1 showed normal FEV1/FVC and low exacerbations. Cluster 4 showed relatively low FEV1/FVC and high exacerbations. While Cluster 2 and Cluster 3 showed similar exacerbations, Cluster 2 had the highest BMI among all clusters.
conclusionsAssociation of imaging-based clusters with existing clinical metrics suggests the sensitivity of MICA in differentiating subpopulations.
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