Imaging-based clusters in former smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and intermediate outcome measures in COPD study (SPIROMICS).
COPD
Emphysema
Former smokers
Functional small airway disease
Imaging-based cluster analysis
Journal
Respiratory research
ISSN: 1465-993X
Titre abrégé: Respir Res
Pays: England
ID NLM: 101090633
Informations de publication
Date de publication:
15 Jul 2019
15 Jul 2019
Historique:
received:
19
02
2019
accepted:
02
07
2019
entrez:
17
7
2019
pubmed:
17
7
2019
medline:
17
1
2020
Statut:
epublish
Résumé
Quantitative computed tomographic (QCT) imaging-based metrics enable to quantify smoking induced disease alterations and to identify imaging-based clusters for current smokers. We aimed to derive clinically meaningful sub-groups of former smokers using dimensional reduction and clustering methods to develop a new way of COPD phenotyping. An imaging-based cluster analysis was performed for 406 former smokers with a comprehensive set of imaging metrics including 75 imaging-based metrics. They consisted of structural and functional variables at 10 segmental and 5 lobar locations. The structural variables included lung shape, branching angle, airway-circularity, airway-wall-thickness, airway diameter; the functional variables included regional ventilation, emphysema percentage, functional small airway disease percentage, Jacobian (volume change), anisotropic deformation index (directional preference in volume change), and tissue fractions at inspiration and expiration. We derived four distinct imaging-based clusters as possible phenotypes with the sizes of 100, 80, 141, and 85, respectively. Cluster 1 subjects were asymptomatic and showed relatively normal airway structure and lung function except airway wall thickening and moderate emphysema. Cluster 2 subjects populated with obese females showed an increase of tissue fraction at inspiration, minimal emphysema, and the lowest progression rate of emphysema. Cluster 3 subjects populated with older males showed small airway narrowing and a decreased tissue fraction at expiration, both indicating air-trapping. Cluster 4 subjects populated with lean males were likely to be severe COPD subjects showing the highest progression rate of emphysema. QCT imaging-based metrics for former smokers allow for the derivation of statistically stable clusters associated with unique clinical characteristics. This approach helps better categorization of COPD sub-populations; suggesting possible quantitative structural and functional phenotypes.
Sections du résumé
BACKGROUND
BACKGROUND
Quantitative computed tomographic (QCT) imaging-based metrics enable to quantify smoking induced disease alterations and to identify imaging-based clusters for current smokers. We aimed to derive clinically meaningful sub-groups of former smokers using dimensional reduction and clustering methods to develop a new way of COPD phenotyping.
METHODS
METHODS
An imaging-based cluster analysis was performed for 406 former smokers with a comprehensive set of imaging metrics including 75 imaging-based metrics. They consisted of structural and functional variables at 10 segmental and 5 lobar locations. The structural variables included lung shape, branching angle, airway-circularity, airway-wall-thickness, airway diameter; the functional variables included regional ventilation, emphysema percentage, functional small airway disease percentage, Jacobian (volume change), anisotropic deformation index (directional preference in volume change), and tissue fractions at inspiration and expiration.
RESULTS
RESULTS
We derived four distinct imaging-based clusters as possible phenotypes with the sizes of 100, 80, 141, and 85, respectively. Cluster 1 subjects were asymptomatic and showed relatively normal airway structure and lung function except airway wall thickening and moderate emphysema. Cluster 2 subjects populated with obese females showed an increase of tissue fraction at inspiration, minimal emphysema, and the lowest progression rate of emphysema. Cluster 3 subjects populated with older males showed small airway narrowing and a decreased tissue fraction at expiration, both indicating air-trapping. Cluster 4 subjects populated with lean males were likely to be severe COPD subjects showing the highest progression rate of emphysema.
CONCLUSIONS
CONCLUSIONS
QCT imaging-based metrics for former smokers allow for the derivation of statistically stable clusters associated with unique clinical characteristics. This approach helps better categorization of COPD sub-populations; suggesting possible quantitative structural and functional phenotypes.
Identifiants
pubmed: 31307479
doi: 10.1186/s12931-019-1121-z
pii: 10.1186/s12931-019-1121-z
pmc: PMC6631615
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
153Subventions
Organisme : NHLBI NIH HHS
ID : U24 HL141762
Pays : United States
Organisme : NIH HHS
ID : S10 OD018526
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA086862
Pays : United States
Organisme : NHLBI NIH HHS
ID : K24 HL137013
Pays : United States
Organisme : NHLBI NIH HHS
ID : U01 HL114494
Pays : United States
Organisme : NHLBI NIH HHS
ID : U01 HL137880
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL130506
Pays : United States
Organisme : NCRR NIH HHS
ID : S10 RR022421
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL112986
Pays : United States
Organisme : NIEHS NIH HHS
ID : P30 ES005605
Pays : United States
Organisme : NIH HHS
ID : NIH grants U01-HL114494, R01-HL112986 and S10-RR022421
Pays : United States
Organisme : NIEHS NIH HHS
ID : P30 ES006694
Pays : United States
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