2018年1月1日
Significance of low-attenuation cluster analysis on quantitative CT in the evaluation of chronic obstructive pulmonary disease
Korean Journal of Radiology
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- 巻
- 19
- 号
- 1
- 開始ページ
- 139
- 終了ページ
- 146
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.3348/kjr.2018.19.1.139
- 出版者・発行元
- Korean Radiological Society
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.
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.
- リンク情報
- ID情報
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- DOI : 10.3348/kjr.2018.19.1.139
- ISSN : 1229-6929
- PubMed ID : 29354010
- SCOPUS ID : 85040771499