  Imaging biomarkers in neuro-oncology are used for diagnosis, prognosis and
treatment response monitoring. Magnetic resonance imaging is typically used
throughout the patient pathway because routine structural imaging provides
detailed anatomical and pathological information and advanced techniques
provide additional physiological detail. Following image feature extraction,
machine learning allows accurate classification in a variety of scenarios.
Machine learning also enables image feature extraction de novo although the low
prevalence of brain tumours makes such approaches challenging. Much research is
applied to determining molecular profiles, histological tumour grade and
prognosis at the time that patients first present with a brain tumour.
Following treatment, differentiating a treatment response from a post-treatment
related effect is clinically important and also an area of study. Most of the
evidence is low level having been obtained retrospectively and in single
centres.
