Multi-scale Model of Children with Brain Tumors

Histopathological methods involve clinical investigation of the tissues of a tumor to diagnose patients and understand the possible effects of treatments. This is done largely through the use of imagery analysis. However, genetic and molecular evaluation has shown that tumors with the same histopathological features can behave differently, requiring different modes of treatment. This means that standard histopathological evaluation is no longer considered the end-point for decision making about patient care. Some recent studies have found that imaging signatures can predict genetic features and how tumors may respond to different treatments. Other results have found correlation between features found in radiological images and overall survival and progression-free survival of brain cancer patients. Through access to the Pediatric Brain Tumor Atlas, researchers will have access to a rich database of relevant genetic data across pediatric cancer types. Researchers will use this data to develop and test a multi-scale model to better understand pediatric brain tumors and to bolster and advance current histopathological methods. These models will guide researchers on which data types are most predictive for diagnosis and treatment which will streamline the decision making of medical professionals.