Child brain tumors can be classified by advanced imaging and AI

Diffusion weighted imaging and machine learning can successfully classify the diagnosis and characteristics of common types of pediatric brain tumors a UK-based multi-center study, including WMG at the University of Warwick has found. This means that the tumor can be characterized and treated more efficiently. The largest cause of death from cancer in children are brain tumors in a particular part of the brain, called the posterior fossa. However, within this area, there are three main types of brain tumor, and being able to characterize them quickly and efficiently can be challenging. Currently, a qualitative assessment of MRI by radiologists is used; however, overlapping radiological characteristics can make it difficult to distinguish which type of tumor it is, without the confirmation of biopsy.