THE EVOLUTION OF PROSTATE CANCER DIAGNOSIS: FROM PALPATION TO ARTIFICIAL INTELLIGENCE

Being one of the most common types of cancer, prostate cancer requires a specific diagnostic approach, using modern, highly sensitive, and specific diagnostic methods. An analysis of existing methods will allow us to determine the most effective strategies for early detection and control of the disease. The purpose of this study. To summarize existing data on the diagnostic algorithm for prostate cancer, identify the strengths and weaknesses of each of the procedures used, and evaluate the impact and effectiveness of modern diagnostic methods. Methods and materials. Information was searched and analyzed in Google Scholar, PubMed, Elsevier, Web of Science, and Medline databases. The review includes data from meta-analyses, randomized controlled trials, systematic reviews, and clinical trials. Duplicate articles have been deleted, information verified, and irrelevant works excluded. As a result, 75 full-text documents and abstracts were selected, providing a comprehensive analysis of the problem under consideration. Conclusion. Combined approaches increase the accuracy of pancreatic cancer diagnosis. PSMA-PET improves the detection of metastases, but remains expensive and difficult to access in developing countries. A liquid biopsy has potential, but requires improved sensitivity. Transrectal ultrasound examination remains an important tool, but its diagnostic value is limited. A magnetic resonance imaging-targeted biopsy reveals more clinically significant prostate cancer than a systematic biopsy. Artificial intelligence in diagnostics requires development, but its use should be regulated.