Assessment of COPD severity by combining pulmonary function tests and chest CT images.

ABSTRACT

PURPOSE: Chronic obstructive pulmonary disease (COPD) is characterized by airflow limitations. Physicians frequently assess the stage using pulmonary function tests and chest CT images. This paper describes a novel method to assess COPD severity by combining measurements of pulmonary function tests (PFT) and the results of chest CT image analysis. METHODS: The proposed method utilizes measurements from PFTs and chest CT scans to assess COPD severity. This method automatically classifies COPD severity into five stages, described in GOLD guidelines, by a multi-class AdaBoost classifier. The classifier utilizes 24 measurements as feature values, which include 18 measurements from PFTs and six measurements based on chest CT image analysis. A total of 3 normal and 46 abnormal (COPD) examinations performed in adults were evaluated using the proposed method to test its diagnostic capability. RESULTS: The experimental results revealed that its accuracy rates were 100.0 % (resubstitution scheme) and 53.1 % (leave-one-out scheme). A total of 95.7 % of missed classifications were assigned in the neighboring severities. CONCLUSIONS: These results demonstrate that the proposed method is a feasible means to assess COPD severity. A much larger sample size will be required to establish the limits of the method and provide clinical validation.