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PLoS One. 2018 Feb 14;13(2):e0192892. doi: 10.1371/journal.pone.0192892. eCollection 2018.

Heterogeneity in pulmonary emphysema: Analysis of CT attenuation using Gaussian mixture model.

Author information

1
Clinical PET Center, Institute of Biomedical Research and Innovation, Minatojimaminamimachi, Chuo-ku, Kobe, Hyogo, Japan.
2
Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, Kyoto, Japan.
3
Preemptive Medicine and Lifestyle Disease Research Center, Kyoto University Hospital, 53 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, Kyoto, Japan.
4
Department of Radiology, Chibune General Hospital, Tsukuda, Nishi-Yodogawa-ku, Osaka, Osaka, Japan.

Abstract

PURPOSE:

To utilize Gaussian mixture model (GMM) for the quantification of chronic obstructive pulmonary disease (COPD) and to evaluate the combined use of multiple types of quantification.

MATERIALS AND METHODS:

Eighty-seven patients (67 men, 20 women; age, 67.4 ± 11.0 years) who had undergone computed tomography (CT) and pulmonary function test (PFT) were included. The heterogeneity of CT attenuation in emphysema (HC) was obtained by analyzing a distribution of CT attenuation with GMM. The percentages of low-attenuation volume in the lungs (LAV), wall area of bronchi (WA), and the cross-sectional area of small pulmonary vessels (CSA) were also calculated. The relationships between COPD quantifications and the PFT results were evaluated by Pearson's correlation coefficients and through linear models, with the best models selected using Akaike information criterion (AIC).

RESULTS:

The correlation coefficients with FEV1 were as follows: LAV, -0.505; HC, -0.277; CSA, 0.384; WA, -0.196. The correlation coefficients with FEV1/FVC were: LAV, -0.640; HC, -0.136; CSA, 0.288; WA, -0.131. For predicting FEV1, the smallest AIC values were obtained in the model with LAV, HC, CSA, and WA. For predicting FEV1/FVC, the smallest AIC values were obtained in the model with LAV and HC. In both models, the coefficient of HC was statistically significant (P-values = 0.000880 and 0.0441 for FEV1 and FEV1/FVC, respectively).

CONCLUSION:

GMM was applied to COPD quantification. The results of this study show that COPD severity was associated with HC. In addition, it is shown that the combined use of multiple types of quantification made the evaluation of COPD severity more reliable.

PMID:
29444178
PMCID:
PMC5812649
DOI:
10.1371/journal.pone.0192892
[Indexed for MEDLINE]
Free PMC Article

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