Study of emphysematous changes in the population of Moscow using automated evaluation of radiological examinations.

Abstract

Background. Emphysema, commonly seen in patients with chronic obstructive pulmonary disease (COPD), worsens the course of chronic cardiovascular and endocrine diseases and is also associated with an increased risk of lung cancer. Although the evaluation of COPD incidence is applied systematically, the prevalence of emphysema is often not known. One of the ways to offset that is automated analysis of chest CT scans using artificial intelligence technologies. Goal. To study the prevalence of emphysema in the population of Moscow using automated analysis of radiological examinations. Methods. The results of the chest CT scan of 116,216 patients were analyzed. All studies were performed between October 2022 and June 2023 in Moscow medical facilities. The Emphysema-IRA AI service (Intelligent Radiology Assistance Laboratories (AIRA Labs) LLC) used an automated mode to determine the presence of emphysematous changes in the lungs (binary classification – yes/no) and the percentage of emphysematous lesions in both lungs and each lung separately. Results. The prevalence of pulmonary emphysema among the Moscow population was 0.614 per 1,000 people; the prevalence of clinically significant emphysema was 0.173 per 1,000 people. The majority of individuals presented with either pulmonary or clinically significant emphysema in CT belong to the elderly group (47.0% and 55.0%, respectively); the proportion of young people is also significant (9.0% and 5.0%). Men of all age groups have a significantly higher chance to get diagnosed with emphysema which suggests a higher incidence compared to the female population (Chi-square = 1000.0; p<0.001). Regardless of gender, a 5-year increase in age elevates the likelihood of both emphysema and clinically significant emphysema by 1.1 times. Conclusions. Automated detection of signs of pulmonary emphysema on CT allows for a quick, population-wide, and objective assessment of the COPD prevalence. Thanks to the development of AI-based medical software, it has become possible to develop and implement ground-breaking digital technologies for healthcare management and public health studies.