A study of role of high resolution computed tomography among copd patients in a tertiary care centre

Background: From the last few years, high-resolution computed tomography (HRCT) has come up as a new diagnostic modality to diagnose emphysematous and chronic bronchitis components of chronic obstructive pulmonary disease (COPD). IN this study was undertaken to evaluate for HRCT features in patients with COPD, which include various qualitative and quantitative features of HRCT and to detect patients' characteristics that correlate with these HRCT features. HRCT allows direct visualization of areas of lung destruction, and allows detection of parenchymal changes 0.2-0.3 mm in size. HRCT is more sensitive than chest radiography and lung function tests in the detection of early smoking related lung damage and also to see disease progression in COPD. It is also help to identify the presence and to quantify the amount of emphysema present. Material and Method-after taking ethical approval informed consent is taken from 100 patient of COPD from OPD and IPD in GMC KOTA in a span of one year is selected by simple non purposive sampling spirometry done and HRCT done and various parameter is calculated. Result-in this study various parameter like age, DOI, pack year, spirometric parameter quality of life is taken as a study variable of patient and HRCT various quantitative and qualitative parameter is taken to find out relation between them in our study age, duration of illness, pack year, shows correlation with various CT features shows disease progression p value is below 0.01 (which is extremely significant).in this study %FEV1,AQ30 shows association with few CT features not all . Conclusion: In our study variable in COPD patients are shows significant relation with Various quantitative and qualitative HRCT features were found to correlate with patients’ characteristics, spirometric indices, and health-related quality-of-life score, suggesting that HRCT is useful not only in detecting emphysema and its various subtypes but also in predicting the extent and severity of COPD and find relation between high resolution computed tomography features and patients characteristics in chronic obstructive pulmonary disease .