Imaging-based clusters in current smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)

Babak Haghighi; Sanghun Choi; Jiwoong Choi; Eric A Hoffman; Alejandro P Comellas; John D Jr Newell; R. Graham Barr; Eugene Bleecker; Christopher B Cooper; David Couper; Mei Lan Han; Nadia N Hansel; Richard E Kanner; Ella A Kazerooni; Eric A C Kleerup; Fernando J Martinez; Wanda O'Neal; Stephen I Rennard; Prescott G Woodruff; Ching-Long Lin

doi:10.1186/s12931-018-0888-7

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Imaging-based clusters in current smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)

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Imaging-based clusters in current smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)

Babak Haghighi, Sanghun Choi, Jiwoong Choi, Eric A Hoffman, Alejandro P Comellas, John D Jr Newell, R. Graham Barr, Eugene Bleecker, Christopher B Cooper, David Couper, …

Respiratory research, Vol.19(1), pp.178-178

09/18/2018

DOI: 10.1186/s12931-018-0888-7

PMCID: PMC6145340

PMID: 30227877

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Abstract

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. 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. 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. Association of imaging-based clusters with existing clinical metrics suggests the sensitivity of MICA in differentiating subpopulations.

Adult

Aged

Cluster Analysis

Cohort Studies

Cross-Sectional Studies

Female

Forced Expiratory Volume - physiology

Humans

Male

Middle Aged

Outcome Assessment, Health Care - methods

Pulmonary Disease, Chronic Obstructive - diagnostic imaging

Pulmonary Disease, Chronic Obstructive - physiopathology

Smokers

Tomography, X-Ray Computed - methods

Details

Title: Subtitle: Imaging-based clusters in current smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)
Creators: Babak Haghighi - University of Iowa
Sanghun Choi - Kyungpook National University
Jiwoong Choi - University of Iowa
Eric A Hoffman - University of Iowa
Alejandro P Comellas - University of Iowa
John D Jr Newell - University of Iowa
R. Graham Barr - Columbia University
Eugene Bleecker - University of Arizona
Christopher B Cooper - University of California, Los Angeles
David Couper - University of North Carolina at Chapel Hill
Mei Lan Han - University of Michigan
Nadia N Hansel - Johns Hopkins University
Richard E Kanner - University of Utah
Ella A Kazerooni - University of Michigan
Eric A C Kleerup - Department of Medicine, UCLA, Los Angeles, CA, USA
Fernando J Martinez - Cornell University
Wanda O'Neal - School of Medicine, University of North Carolina, Chapel Hill, NC, USA
Stephen I Rennard - University of Nebraska–Lincoln
Prescott G Woodruff - University of California, San Francisco
Ching-Long Lin - University of Iowa
Resource Type: Journal article
Publication Details: Respiratory research, Vol.19(1), pp.178-178
DOI: 10.1186/s12931-018-0888-7
PMID: 30227877
PMCID: PMC6145340
NLM abbreviation: Respir Res
ISSN: 1465-993X
eISSN: 1465-993X
Grant note: U01 HL114494 / NHLBI NIH HHS HHSN268200900017C / NHLBI NIH HHS P30 ES005605 / NIEHS NIH HHS HHSN268200900019C / NHLBI NIH HHS HHSN268200900020C / NHLBI NIH HHS U24 HL141762 / NHLBI NIH HHS U01 HL137880 / NHLBI NIH HHS HHSN268200900015C / NHLBI NIH HHS HHSN268200900013C / NHLBI NIH HHS U01-HL114494, R01-HL112986 and S10-RR022421 / NIH HHS R01 HL112986 / NHLBI NIH HHS HHSN268200900016C / NHLBI NIH HHS HHSN268200900018C / NHLBI NIH HHS HHSN268200900014C / NHLBI NIH HHS P30 ES006694 / NIEHS NIH HHS S10 RR022421 / NCRR NIH HHS
Language: English
Date published: 09/18/2018
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Pulmonary, Critical Care, and Occupational Medicine; ICTS; IIHR--Hydroscience and Engineering; Mechanical Engineering; Internal Medicine
Record Identifier: 9984195066802771

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