Imaging-based clusters in current smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)
Hoffman, Eric A.
Comellas, Alejandro P.
Newell, John D.
Graham Barr, R.
Cooper, Christopher B.
Han, Mei Lan
Hansel, Nadia N.
Kanner, Richard E.
Kazerooni, Ella A.
Kleerup, Eric A. C.
Martinez, Fernando J.
Rennard, Stephen I.
Woodruff, Prescott G.
AffiliationUniv Arizona, Dept Med, Div Genet Genom & Precis Med
MetadataShow full item record
CitationHaghighi et al. Respiratory Research (2018) 19:178. https://doi.org/10.1186/s12931-018-0888-7
Rights© The Author(s). 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at firstname.lastname@example.org.
AbstractBackground: Classification 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. Methods: Among 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. Results: Four 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. Conclusions: Association of imaging-based clusters with existing clinical metrics suggests the sensitivity of MICA in differentiating subpopulations.
NoteOpen Access Journal.
VersionFinal published version
SponsorsNIH [U01-HL114494, R01-HL112986, S10-RR022421]; NIH/NHLBI [HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, HHSN268200900020C]; Bayer; Bellerophon Therapeutics; Boehringer-Ingelheim Pharmaceuticals, Inc.; Chiesi Farmaceutici S.p.A.; Forest Research Institute, Inc.; GlaxoSmithKline; Grifols Therapeutics, Inc.; Ikaria, Inc.; Nycomed GmbH; Takeda Pharmaceutical Company; Novartis Pharmaceuticals Corporation; ProterixBio; Regeneron Pharmaceuticals, Inc.; Sanofi; Sunovion
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