Prediction of Tumor Progression in Patients with DIPG DMG Using Volumetric Measurements Obtained via Automatic Deep Learning Brain Tumor Segmentation

Award: $60,000 over 1 year (2022-2023)
Principal Investigators:  Dr. Anahita Fathi Kazerooni, Instructor Center for Data Driven Discovery in Biomedicine at Children’s Hospital of Philadelphia
Funding Partners: Tough2Gether for DIPG/DMG and Elle’s Angels Foundation as part of the DIPG DMG Research Funding Alliance

This project seeks to predict tumor response to treatment and progression in patients with DMG/DIPG by using volumetric measurements obtained via automatic deep learning brain tumor segmentation.  This method intends to create a 3D model to replace the current 2D methods of measurement by using AI methods and widely available MRIs. This project is using AI (an algorithm that Dr. Kazerooni has created) and machine learning for diagnostics, prognosis, and out come, response to treatments. This will run automatically on any scan to give the RAPNO (Response Assessment in Pediatric Neuro-Oncology) info to the clinicians.