Breast cancer in Ukraine: clinics and diagnostics. Current status and prospects of diagnostics (lecture)

The lecture discusses the current state of early Breast Cancer (BC) diagnosis in Ukraine, outlining its epidemiological features, morphological heterogeneity, clinical manifestations, and modern diagnostic methods. BC remains the most common oncological disease among women worldwide, including Ukraine. Each year, over 12,000 new cases are registered in the country, with many patients seeking medical help at advanced stages, which decreases treatment effectiveness and survival rates. The lecture stresses the importance of early diagnosis, achievable through increased physician awareness and widespread screening programs. It summarizes current knowledge on the clinicopathological subtypes of BC, assessment of hormonal receptor status, and the role of immunohistochemical and molecular-genetic testing in treatment decisions. Diagnostic imaging techniques (mammography, tomosynthesis, ultrasound, magnetic resonance imaging) and their diagnostic value are discussed, along with clinical examination algorithms. Special emphasis is placed on modern technologies, especially artificial intelligence, in automated image analysis for mammography and ultrasound. The integration of deep learning with medical imaging data improves diagnostic accuracy, allows detection of pathological changes at the preclinical stage, and reduces diagnostic errors. A key focus is the multidisciplinary approach to managing BC patients, which involves coordination among healthcare providers, adherence to current clinical protocols, and the use of genomic assays (such as Oncotype DX, MammaPrint), with personalized treatment plans. The lecture underlines the necessity of ongoing professional development for healthcare workers at all levels through postgraduate education, aiming to establish standardized algorithms for early BC detection. Overall, the lecture aims to provide students with a thorough understanding of modern principles in breast cancer diagnostics and strategies for enhancing their effectiveness in Ukraine, considering global trends, national challenges, and innovative approaches. Keywords: breast cancer symptoms, diagnostic algorithm, artificial intelligence in diagnosis.