New Investigator Grant Awarded to Sarah Brüning

Radiotherapy (RT) remains the primary treatment to prolong life and alleviate symptoms for children with diffuse midline glioma. However, the effectiveness of radiotherapy varies greatly between individuals and it is currently not possible to say before the treatment how much an individual tumor will respond. Current treatment protocols rely on a "one-size-fits-all" approach, borrowed from studies in adults, which does not account for the unique biology of tumors in children which indeed are considered a different disease.

This project aims to provide a much better informed estimation of the individual efficacy of RT for each child. This will also allow to investigate if we could improve the RT response by changing its delivery. We will harness tools from the realm of artificial intelligence (AI) and mathematical modeling to achieve three specific goals:
Predicting RT Effectiveness: The first goal is to develop tools to predict how each child’s tumor will respond to standard RT before treatment begins. By identifying children who may benefit from different RT schedules, clinicians can make more informed decisions tailored to each patient’s needs.
Customizing Treatment Timing: The second goal isto explore how changing the timing and dose of RT sessions could improve its effectiveness. Using patient data, the team will model how tumors grow and respond to different treatment schedules, helping to design personalized RT protocols that maximize benefits.
Tailoring radiation dose distribution: The final goal focuses on optimizing where the RT dose is delivered.
By analyzing imaging data, the project aims to identify areas within the tumor that are most likely to grow back after treatment. This will enable precise delivery of RT to these high-risk areas while sparing healthy tissue.

This research is groundbreaking because it uses cutting-edge techniques to analyze rare and complex data sets from children with DMG, overcoming challenges of limited patient numbers. By building on noninvasive imaging the project seeks to transform RT from a generalized treatment into a precise, personalized therapy. This could improve survival, reduce treatment side effects, and enhance quality of life for children with DMG.