Significance of Low-Attenuation Cluster Analysis on Quantitative CT in the Evaluation of Chronic Obstructive Pulmonary Disease
10.3348/kjr.2018.19.1.139
- Author:
Atsushi NAMBU
1
;
Jordan ZACH
;
Song Soo KIM
;
Gongyoung JIN
;
Joyce SCHROEDER
;
Yu Il KIM
;
Russell BOWLER
;
David A LYNCH
Author Information
1. Department of Radiology, National Jewish Health, Denver, CO 80206, USA. nambu-a@gray.plala.or.jp
- Publication Type:Original Article
- Keywords:
CT;
Chronic obstructive pulmonary disease;
COPD;
Quantitative CT;
Cluster size analysis;
Low attenuation area
- MeSH:
Body Mass Index;
Cluster Analysis;
Forced Expiratory Volume;
Pulmonary Disease, Chronic Obstructive;
Tobacco Products
- From:Korean Journal of Radiology
2018;19(1):139-146
- CountryRepublic of Korea
- Language:English
-
Abstract:
OBJECTIVE: To assess clinical feasibility of low-attenuation cluster analysis in evaluation of chronic obstructive pulmonary disease (COPD). MATERIALS AND METHODS: Subjects were 199 current and former cigarette smokers that underwent CT for quantification of COPD and had physiological measurements. Quantitative CT (QCT) measurements included low-attenuation area percent (LAA%) (voxels ≤ −950 Hounsfield unit [HU]), and two-dimensional (2D) and three-dimensional D values of cluster analysis at three different thresholds of CT value (−856, −910, and −950 HU). Correlation coefficients between QCT measurements and physiological indices were calculated. Multivariable analyses for percentage of predicted forced expiratory volume at one second (%FEV1) was performed including sex, age, body mass index, LAA%, and D value had the highest correlation coefficient with %FEV1 as independent variables. These analyses were conducted in subjects including those with mild COPD (global initiative of chronic obstructive lung disease stage = 0–II). RESULTS: LAA% had a higher correlation coefficient (-0.549, p < 0.001) with %FEV1 than D values in subjects while 2D D−910HU (−0.350, p < 0.001) revealed slightly higher correlation coefficient than LAA% (−0.343, p < 0.001) in subjects with mild COPD. Multivariable analyses revealed that LAA% and 2D D value−910HU were significant independent predictors of %FEV1 in subjects and that only 2D D value−910HU revealed a marginal p value (0.05) among independent variables in subjects with mild COPD. CONCLUSION: Low-attenuation cluster analysis provides incremental information regarding physiologic severity of COPD, independent of LAA%, especially with mild COPD.
