Relationships Between Genomic, Imaging, and Histopathologic Characteristics in Pediatric Brain Tumors

Understanding the genetic makeup of tumors is crucial in the pursuit of diagnostics and therapies. Sequencing a tumor sample’s DNA, or identifying all of the genes present in the tumor, is important for better understanding cancers and creating treatments. However, genomic data is not the only clinically relevant information for diagnosing cancer. Researchers on this project seek to combine genomic data with tumor imagery and text-based data gathered directly from patients and medical professionals. Comparing this data could reveal connections and patterns relevant to more accurate diagnoses,effective treatments and better understand different tumor types. Using machine learning-based algorithms, or instructions for a computer that adapt themselves to new information, researchers will compare text-based clinical data provided by CBTN to genomic data made available through the Pediatric Brain Tumor Atlas. With access to such a broad dataset on pediatric brain cancers, researchers aim to improve the accuracy of diagnostic tests for pediatric patients.