IMAGINATION

The term “gliomas” refers to a collective name used for various malignant brain tumors. Based on guidelines established by the World Health Organization (WHO), gliomas are classified based on molecular characteristics because these features are associated with patients’ survival ranging from 15 months to 7 years. Therefore, early differentiation of different types of gliomas is of great importance. However, previous scientific publications have shown that advanced analysis of radiological imaging, often Magnetic Resonance Imaging (MRI), can characterize the tumor without the need for the patient to undergo a brain biopsy. This non-invasive tumor profiling is achieved using artificial intelligence (AI), which requires a large number of cases to be available. With the help of a multicenter database, resulting from a subproject within the overarching project and continuously supplemented with new cases from the three collaborating centers, these AI software packages can be utilized. However, it is unknown to what extent these costly packages impact the disease progression and patient treatment. This project aims to critically evaluate and standardize the use of AI analyses on MRI data of glioma patients within our collaboration region. Therefore, we collaborate with patients, various clinical doctors, and scientists from diverse backgrounds. By working across borders, we achieve a larger and more diverse dataset of a rare disease. This optimizes the representativeness and generalizability of the results, leading to a better understanding of radiological care for glioma patients at an international level. Additionally, bringing together specialists within the border region will lead to innovative approaches, new insights, and improved methodologies.