The autoimmune, chronic demyelinating diseases of the CNS described in this thesis include multiple sclerosis (MS), neuromyelitis optica spectrum disorders (NMOSD), and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Differential diagnosis of these diseases was facilitated by the discovery of highly specific antibodies found in NMOSD patients, anti-AQP4 antibodies, and highly specific antibodies found in MOGAD patients, anti-MOG antibodies. Early diagnosis is key for the selection of the right therapy and determination of antibodies to AQP4 and MOG can bring to a significantly faster and much easier diagnosis.. Laboratory tests used to determine antibodies must meet high criteria of sensitivity, specificity, and accuracy to be used in the routine. Of the many methods described for determining these antibodies, the cell-based indirect immunofluorescence (CBA IIF) with cells transfected with AQP4 and MOG stands out. In this thesis two methods for the determination of anti- AQP4 antibodies, the previously used ELISA method and the new CBA IIF method are compared, and their diagnostic sensitivity, specificity, and accuracy in real laboratory conditions are also examined. The CBA IIF test for the combined determination of antibodies to AQP4 and MOG made by EUROIMMUN has proved to be highly sensitive, highly specific, and easy to perform with minimal time and resources spent. The results of this research confirmed a higher sensitivity of the ELISA test for determining antibodies to AQP4 compared to the CBA IIF test (92% to 84%) while the CBA IIF test is more specific (94% vs. 82%). The CBA IIF test has higher accuracy (90.67%) than the ELISA test (85.33%). Due to only one positive result of anti-MOG antibodies, it was not possible to present and interpret the results of the sensitivity and specificity of the test because of the too small number of examined samples. The research should be extended to a larger number of respondents and include healthy controls to obtain fully credible data for our population.