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Inhaling gas with different CT densities allows detection of abnormalities in the lung periphery of patients with smoking-induced COPD.
Authors:K Yamaguchi  K Soejima  E Koda  N Sugiyama
Affiliation:Department of Medicine, School of Medicine, Keio University, Tokyo, Japan. yamaguc@cpnet.med.keio.ac.jp
Abstract:STUDY OBJECTIVES: To establish a novel method allowing detection of regional abnormalities in gas distribution at the acinar level by high-resolution CT (HRCT). PARTICIPANTS: Nonsmoking control subjects (n = 28) and patients with smoking-induced COPD (n = 47). MEASUREMENTS AND RESULTS: Changes in lung CT densities were examined by HRCT while the subjects inhaled a gas mixture consisting of 21% O(2) in SF(6) or 21% O(2) in He. HRCT images of the right upper and lower lung fields were obtained at the end of inspiration and expiration of the second and 60th breaths after the start of each gas. Introducing mean lung density (MLD) and relative area with low CT attenuation (%LAA), we analyzed the differences in acinar SF(6) and He distribution in the early phase (second breath) and in the equilibrium state (60th breath). We found that the differences in inspiratory MLD between the SF(6) and He images at the 60th breath were qualitatively consistent with the differences predicted from the physical properties of these gases. However, the differences in inspiratory MLD between the SF(6) and He images taken at the second breath were smaller than those at the 60th breath, especially in the smoking group with COPD. These differences in second-breath inspiratory MLD in the smoking group were smaller in the upper lung field than in the lower lung field. The differences in MLD between the two gases were not detected at end-expiration at the time of either the second or 60th breaths. The %LAA values did not differ between the SF(6) and He images in either the nonsmoking group or the smoking group. CONCLUSIONS: SF(6)/He-associated HRCT images obtained at end-inspiration, but not at end-expiration, in the early breathing phase are useful for predicting acinar gas distribution abnormalities in patients with COPD.
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