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Relevance: Gliomas represent a major group of primary central nervous system tumors, accounting for approximately 80% of all malignant brain neoplasms. Recent advances in molecular diagnostics, including the identification of mutations in the isocitrate dehydrogenase (IDH) gene, offer new opportunities to improve the classification of gliomas and to understand the mechanisms of their development. IDH mutations, which are found in a large proportion of gliomas, are associated with a better prognosis and represent an important biomarker for the development of targeted therapeutic strategies. Diagnostic techniques, particularly magnetic resonance imaging (MRI), also play an important role, providing additional ways to assess the morphological and biological characteristics of gliomas, contributing to a more accurate determination of tumor malignancy and molecular profile, which is key to treatment decisions. The study aimed to To study the possibilities of magnetic resonance imaging in assessing the degree of malignancy of glial brain tumors. Methods: A literature review was performed using the keywords: glioma, IDH mutation, IDH wild-type, MRI, magnetic resonance spectroscopy (MRS), apparent diffusion coefficient (ADC), diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), diffusion kurtosis image (DKI), Susceptibility Weighted Imaging (SWI) in PubMed, BMC Medicine, and Google Scholar databases. The review includes the results of an analysis of 45 literature reviews on the diagnostic capabilities of molecular diagnostics and MRI to assess the malignancy of gliomas. Results: This review highlights the importance of current approaches to the diagnosis of gliomas, demonstrating that different grades of malignancy and IDH mutation status are associated with unique features on MR imaging, including differences in localization, signal, and enhancement patterns. DTI and DWI extend the ability of MRI to assess tissue microstructure, allowing for more precise tumor characterization. Studies combining MRI morphologic features, ADC and DTI parameters offer a non-invasive approach to glioma prognosis, highlighting the importance of integrated use of imaging modalities to improve diagnosis and therapy. Conclusion: The use of magnetic resonance imaging allows for more accurate morphologic and metabolic characterization of gliomas in assessing the degree of malignancy, allowing physicians to make more accurate prognostic assessments and select the most appropriate treatment strategy.
Toleshbaev et al. (Wed,) studied this question.