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Abstract
20% of brain tumor patients present with seizures at the onset of diagnosis, while a further 25-40% develop epileptic seizures as the tumor progresses. Tumor-related epilepsy (TRE) is a condition in which the tumor causes recurring, unprovoked seizures. The occurrence of TRE differs between patients, along with the effectiveness of treatment methods. Therefore, determining the tumor properties that correlate with epilepsy can help guide TRE treatment. This article reviews the MRI sequences and image post-processing algorithms in the study of TRE. It focuses on epilepsy caused by glioma tumors because it is the most common type of malignant brain tumor and it has a high prevalence of epilepsy. In correlational TRE studies, conventional MRI sequences and diffusion-weighted MRI (DWI) are used to extract variables related to the tumor radiological characteristics, called imaging factors. Image post-processing is used to correlate the imaging factors with the incidence of epilepsy. The earlier studies of TRE used univariate and multivariate analysis to study the correlations between specific variables and incidence of epilepsy. Later, studies used voxel-based morphometry and voxel lesion-symptom mapping. Radiomics has been recently used to post-process the images for the study of TRE. This article will discuss the limitation of the existing imaging modalities and post-processing algorithms. It ends with some suggestions and challenges for future TRE studies.
Keywords: Keywords: Glioma, MRI, Tumor-related epilepsy, Voxel-based morphometry, Lesion symptom mapping, Radiomics.
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