Imaging-based clusters in former 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
Lee, Chang Hyun
Barr, R Graham
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
Smith, Benjamin M
Woodruff, Prescott G
AffiliationUniv Arizona, Dept Med
MetadataShow full item record
CitationHaghighi, B., Choi, S., Choi, J., Hoffman, E. A., Comellas, A. P., Newell, J. D., ... & Couper, D. (2019). 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, 20(1), 153.
Rights© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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AbstractBackground: 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: 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: 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: 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.
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VersionFinal published version
SponsorsNIH [U01-HL114494, R01-HL112986, S10-RR022421]; Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [NRF-2017R1D1A1B03034157]; Korea Ministry of Environment (MOE) [RE201806039]; NIH/NHLBI [HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, HHSN268200900020C]
Except where otherwise noted, this item's license is described as © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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- Authors: Zou C, Li F, Choi J, Haghighi B, Choi S, Rajaraman PK, Comellas AP, Newell JD, Lee CH, Barr RG, Bleecker E, Cooper CB, Couper D, Han M, Hansel NN, Kanner RE, Kazerooni EA, Kleerup EC, Martinez FJ, O'Neal W, Paine R 3rd, Rennard SI, Smith BM, Woodruff PG, Hoffman EA, Lin CL
- Issue date: 2021
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