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DOI 10.5114/pjr.2019.82737

Медицинская библиотека · Polish journal of radiology · 2019

Quantitative assessment of airway and parenchymal components of chronic obstructive pulmonary disease using thin-section helical computed tomography.

Chauhan Narvir S, Sood Dinesh, Takkar Preeti, Dhadwal Devendra S, Kapila Rajiv

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Аннотация

PURPOSE: The purpose of this study was to diagnose and characterise chronic obstructive pulmonary disease (COPD) into its forms, patterns, and severity using MDCT.

MATERIAL AND

METHODS

In this prospective study, spirometric and MDCT evaluation was done in 52 consecutive patients diagnosed with COPD. In each patient six segmental bronchi were evaluated for CT morphometric indices of bronchial wall thickness (BWT) and wall area percentage (WAP). Quantitative evaluation of emphysema was done using inbuilt software, and volume of emphysematous lung was determined using percentage low attenuation area (LAA). COPD was categorised into the following: emphysema predominant; airway predominant; or mixed phenotypes, and severity grading was assigned as mild, moderate, or severe.

RESULTS

Centrilobular was the predominant emphysema pattern occurring alone (36.5%) or in combination with paraseptal changes (34.6%). Among COPD phenotypes, emphysema predominant was the commonest (44.3%), followed by mixed (30.8%), and bronchitis predominant (25.0%). The mean BWT in the airway-predominant group was significantly higher (1.94 ± 0.28 mm) than in the emphysema-predominant subgroup (1.79 ± 0.23 mm) with a p value of 0.005.

CONCLUSION

MDCT is an indispensable tool in quantitative and qualitative evaluation of COPD patients. Measurement of CT indices like BWT, WAP, and %LAA can reliably categorise COPD into phenotypes like emphysema predominant, airway predominant, or mixed, which serve as a guide for patient management.

Для цитирования: Chauhan Narvir S, Sood Dinesh, Takkar Preeti, Dhadwal Devendra S, Kapila Rajiv. Quantitative assessment of airway and parenchymal components of chronic obstructive pulmonary disease using thin-section helical computed tomography.. Polish journal of radiology. 2019. DOI: 10.5114/pjr.2019.82737.
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