Purpose of this review

The aim of this review is to collate the existing literature regarding MR imaging and genetic studies into the identification and subtyping of medulloblastoma. The review will also aim to summarise advanced analysis techniques which incorporate machine learning approaches to deal with MR and genetic data, known as radiomics and radiogenomics.
We aim to summarise the literature and identify common features and results throughout the literature to better understand medulloblastoma, but also attempt to find conflicting reports to highlight more controversial areas.
Despite the abundant use of radiomics and radiogenomics in glioblastoma and other cancerous tumours, its application to medulloblastoma is limited (Fig \ref{446193}), so finally we will discuss the possible future of machine learning approaches to MR and genetic data regarding medulloblastoma.