Correlation between clinical characteristics, spirometric indices and high resolution computed tomography findings in patients of chronic obstructive pulmonary disease

摘要

Introduction: Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disease affecting the airways, leading to significant morbidity and mortality throughout the world. There is a need to have a holistic evaluation of COPD patients, other than just measuring the level of obstruction as performed by spirometry. High resolution computed tomography (HRCT) scan of thorax partly fulfills this requirement. Materials and Methods: Fifty patients of COPD (confirmed on spirometry as per the GOLD guidelines 2014 guidelines) were enrolled, out of which 35 patients got a HRCT done. Complete clinical evaluation was done. The Philips computer program for lung densitometry was used with these limits (?800/?1, 024 Hounsfield unit [HU]) to calculate densities, after validating densitometry values with phantoms. We established the area with a free hand drawing of the region of interest, then we established limits (in HUs) and the computer program calculated the attenuation as mean lung density (MLD) of the lower and upper lobes. Results: There was a significant correlation between smoking index and anteroposterior tracheal diameter (P = 0.036). Tracheal index was found to be decreasing with increasing disease severity which was statistically significant (P = 0.037). Mean upper lobe MLD was ?839.27 HU, mean lower lobe MLD was ?834.91 HU and the mean MLD was ?837.08 HU. The lower lobes MLD were found to be decreasing with increasing disease severity. A mild linear correlation of pre forced expiratory volume in the first second (FEV1) was observed with lower lobe and total average MLD while a mild linear correlation of Post-FEV1 was observed with both coronal (P = 0.042) and sagittal (P = 0.001) lower lobes MLD. In addition, there was a linear correlation between both pre (P = 0.050) and post (P = 0.024) FEV1/forced vital capacity with sagittal lower lobe MLD. A predictive model can be derived to quantify obstruction severity (FEV1). Conclusion: HRCT may be an important additional tool in the holistic evaluation of COPD. HRCT can well be correlated with the spirometric and clinical features and the level of obstruction can be indirectly derived from it by measuring the MLD.