Korean Journal of Radiology

  • 제19권1호
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  • Pages.139-146
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  • 2018
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  • 1229-6929(pISSN)
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  • 2005-8330(eISSN)
대한영상의학회 (The Korean Society of Radiology)
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DOI QR코드

DOI QR Code

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

  • Nambu, Atsushi (Department of Radiology, National Jewish Health) ;
  • Zach, Jordan (Department of Radiology, National Jewish Health) ;
  • Kim, Song Soo (Department of Radiology, National Jewish Health) ;
  • Jin, Gongyoung (Department of Radiology, National Jewish Health) ;
  • Schroeder, Joyce (Department of Radiology, National Jewish Health) ;
  • Kim, Yu-Il (Department of Medicine, National Jewish Health) ;
  • Bowler, Russell (Division of Pulmonary Medicine, Department of Medicine, National Jewish Health) ;
  • Lynch, David A (Department of Radiology, National Jewish Health)
  • 투고 : 2017.02.27
  • 심사 : 2017.07.02
  • 발행 : 2018.02.01
⟨ 이전 논문 다음 논문 ⟩

초록

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 ${\leq}-950$ 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.

키워드

참고문헌

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