THE ROLE OF COMPUTED TOMOGRAPHY IN THE DIAGNOSIS OF LUNG ADENOCARCINOMA

Lung adenocarcinoma is the most common histological type of lung cancer, occupying a leading position in oncological morbidity and mortality worldwide. This article provides a detailed analysis of the role, capabilities, modern methods, and clinical significance of computed tomography (CT) in the diagnosis of lung adenocarcinoma. CT examination is the "gold standard" for detecting lung adenocarcinoma at early stages, assessing tumor size, local invasion, lymph nodes, and distant metastases. Modern low-dose CT (LDCT) screening programs have reduced lung cancer mortality by 20-25%. CT semiotics characteristic of adenocarcinoma include: ground-glass opacities (GGO), the "spiculation" sign, the "halo" sign, the vacuole sign, and cavitation. CT-based TNM staging is crucial for determining prognosis and selecting treatment tactics. Recently, artificial intelligence and deep learning models (CNN-LSTM-RF) allow for automatic analysis of CT images, distinguishing adenocarcinoma from other histological types with up to 97% accuracy. The article also covers epidemiological indicators in the Central Asian region, differential diagnosis, and future prospects of CT examination.