| Abstract [eng] |
Central nervous system vasculitides are rare but clinically complex conditions that remain challenging to diagnose due to nonspecific clinical, laboratory, and radiological findings as well as a broad spectrum of disorders that could mimic vasculitis. Differentiating primary angiitis of the central nervous system from secondary vasculitides and non-vasculitic pathologies is particularly difficult, because an incorrect diagnosis may lead to unjustified immunosuppressive treatment and worsen patient prognosis. The aim of this study was to summarise the principles of differential diagnosis of central nervous system vasculitides and to develop a literature-based differential diagnostic algorithm, and to illustrate its application through clinical case analysis. Objectives: 1. To summarise the concept and classification of central nervous system vasculitides in the context of differential diagnosis. 2. To analyse the clinical, laboratory, and radiological features of primary vasculitis of the central nervous system. 3. To evaluate the diagnostic characteristics of secondary vasculitides of the central nervous system and conditions mimicking primary angiitis of the central nervous system. 4. To develop differential diagnostic algorithms for central nervous system vasculitides and assess their applicability through clinical case analysis. Methods: A narrative literature review was conducted using the PubMed (MEDLINE) database. Studies published between 2020 and 2026 addressing the clinical, laboratory, radiological, and histopathological features of central nervous system vasculitides were analysed. Based on the selected sources, summary tables and a two-stage differential diagnostic algorithm were developed, integrating clinical data, cerebrospinal fluid analysis, magnetic resonance imaging, angiographic methods, and, when available, high-resolution vessel wall imaging. The applicability of the algorithm was illustrated through a retrospective clinical case analysis. Results: No single diagnostic method for primary vasculitis of the central nervous system is sufficiently specific to establish a reliable diagnosis. Differential diagnosis must be based on a comprehensive evaluation. Brain biopsy is considered the most reliable method for confirming the diagnosis; however, because of its limited sensitivity and invasive nature, it is usually performed selectively. A structured algorithmic approach helps systematically exclude infectious, systemic autoimmune, and neoplastic conditions and reduces the risk of diagnostic errors. Conclusions: Central nervous system vasculitides constitute a heterogeneous group of disorders whose classification and clinical and radiological presentation must be evaluated within the framework of differential diagnosis; no single diagnostic method is sufficiently specific to establish a reliable diagnosis. Because the clinical, laboratory, and radiological findings of primary vasculitis of the central nervous system are nonspecific, the diagnosis is established by exclusion after systematically ruling out secondary vasculitides and other mimicking conditions. The differential diagnostic algorithms developed in this study allow a structured diagnostic approach, facilitate the systematic exclusion of infectious, systemic autoimmune, and neoplastic conditions, and reduce the risk of misdiagnosis and unjustified immunosuppressive therapy in clinical practice. The analyzed clinical case demonstrated that an algorithm-based differential diagnostic model may help to systematically assess the likelihood of primary central nervous system vasculitis and secondary inflammatory intracranial vasculopathy, as well as support a cautious and individualized treatment approach. |
