Korean J Radiol.  2018 Feb;19(1):139-146. 10.3348/kjr.2018.19.1.139.

Significance of Low-Attenuation Cluster Analysis on Quantitative CT in the Evaluation of Chronic Obstructive Pulmonary Disease

• Nambu A
• Zach J
• Kim SS
• Jin G
• Schroeder
• Kim YI
• Bowler R
• Lynch DA

• KMID: 2425119
• DOI: http://doi.org/10.3348/kjr.2018.19.1.139

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.

Keyword

CT; Chronic obstructive pulmonary disease; COPD; Quantitative CT; Cluster size analysis; Low attenuation area

MeSH Terms

Body Mass Index
Cluster Analysis*
Forced Expiratory Volume
Pulmonary Disease, Chronic Obstructive*
Tobacco Products

Figure

• 

  Fig. 1 3D cluster analysis in patient with severe emphysema.In this rendering, 3D-connected low-attenuation voxels are represented by sphere with volume corresponding to that of real cluster that has more complex shape. 3D = three-dimensional

• 

  Fig. 2 Scatter plots showing relationships between %FEV1 and LAA%, and %FEV1 and 2D D value−910HU.A. %FEV1 vs. LAA% in subjects. B. %FEV1 and 2D D value−910HU in subjects. C. %FEV1 vs. LAA% in subjects with mild emphysema. D. %FEV1 vs. 2D D value−910HU in subjects with mild emphysema. Note that dots are more scattered in areas with lower LAA% in (A) and (C) and that dots are closer to regression line in subjects with mild emphysema (D) than in all subjects (B). LAA% = percentages of low attenuation areas ≤ −950 Hounsfield unit in CT value, 2D = two-dimensional, 2D D value = slopes of functions of cluster sizes and cumulative frequencies that were calculated two-dimensionally, on log-log scale, %FEV1 = percentage of predicted forced expiratory volume at one second

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