Magnetic Susceptibility-Based Imaging in Gliomas: Insights into Tumor Grading and Margin Delineation

Magnetic susceptibility influenced by hemorrhage, iron-containing products, and increased venous vasculature is becoming an emerging biomarker in neuroimaging to provide insights into the biochemical and molecular composition of brain tumors using susceptibility-based MR imaging (R2*, SWI, and QSM). The aim of the present study is to evaluate the role of susceptibility-based MR imaging in the grading and delineation of glioma tumor margins. A structured literature search of PubMed, Scopus, and Google Scholar (2000-2025) was conducted using predefined keywords. Forty studies were selected based on strict inclusion/exclusion criteria for qualitative analysis. R2*-based imaging has demonstrated strong potential as non-invasive biomarkers for glioma grading by reflecting microvascularity, hemorrhage, and intracellular iron content; however, it exhibits lower specificity compared to other techniques. In patients with glioma, intra-tumoral susceptibility signals (ITSS) detected by SWI were more prominent in high-grade tumors compared to low-grade ones. Quantitative measures such as normalized ITSS contrast and qITSS provided semi-automated assessment, reducing observer bias. It demonstrates high sensitivity for detecting ITSS but lacks the ability to differentiate between hemorrhage (paramagnetic) and calcification (diamagnetic). QSM provided quantitative susceptibility values that correlated with tumor grade, complementing the visual ITSS assessment on SWI. Higher susceptibility values on QSM were associated with high-grade gliomas. Notably, it differentiates between hemorrhage and calcification based on their magnetic properties, enhancing accurate diagnosis and treatment planning by providing distinct information about tissue composition, which is crucial for characterizing brain lesions. Also, QSM, and to a lesser extent SWI, provide valuable information about tumor margins by highlighting iron deposition and microvascular abnormalities. QSM is a powerful tool for tumor grading that can be used alongside SWI, particularly in cases where contrast agents cannot be administered, such as in patients with renal impairment. When contrast-enhanced (CE) imaging is feasible, a multimodal approach combining SWI, QSM, and perfusion weighted imaging (PWI) can be employed to improve tumor grading accuracy. Furthermore, QSM combined with diffusion tensor imaging (DTI) in a multimodal approach significantly enhances the precision of tumor boundary delineation, particularly in infiltrative gliomas. However, the QSM method has not yet been routinely adopted in clinical practice due to various challenges. Nonetheless, there is hope that the integration of artificial intelligence and deep learning into this technique will enable its effective clinical application.