Canine lymphoma is a large and complex field of oncohematology. The updated classification system of the World Health Organization (WHO), which is based on clinical, topographic, cytomorphological, immunophenotypic, genetic, and molecular characteristics of neoplastic cells, is recognized as the basic systematization of canine lymphoma. The variety of forms, subtypes of canine lymphoma, the systemic nature of the disease and the increase in cases of their detection, determine the importance and relevance in veterinary oncology of a comprehensive study of this disease. The main vector in the disease control and proper patient management is the timely and accurate diagnosis. The diagnostic scheme for lymphoma includes a medical history and physical examination, hematology, biochemical blood analysis, and urine tests, diagnostic imaging of the chest and abdominal cavities, pathomorphological studies, and cell immunophenotyping. However, the basis for the final diagnosis is cytological and histological methods with cell immunophenotyping. The differentiation clusters of Band T-cells of canine lymphomas are slightly different from those used for human lymphoma immunophenotyping. High-grade canine lymphomas from mature lymphocytes are detected in 86% of cases, with multicentric large B-cell lymphoma being recognized as the most common in the world. The use of modern, high-tech diagnostic methods (ultrasonography, tomography, cytology, molecular genetic) by foreign veterinary oncologists not only promotes a quick and accurate diagnosis but allows scientists to make important discoveries. Consideration of paraneoplastic syndromes may promote earlier detection of dogs' lymphomas. Significance of prognostic factors and understanding of the pathogenesis of lymphoma were evaluated for the veterinarian to make the right clinical decisions, make a long-term prognosis and select appropriate therapy. The difficulty of making an accurate diagnosis of lymphoma is associated with many diagnostic procedures and various factors affecting them, which ultimately requires the formation of a clear diagnostic algorithm.
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