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Meeting # 942 7359 5552

Zoom Meeting # 942 7359 5552

Abstract:

Accurate modeling of brain tumor growth holds great promise for improving radiotherapy planning by capturing microscopic infiltration that remains invisible on standard imaging. In this talk, I will present a series of advances toward patient-specific biophysical and data-driven models of glioma growth. Our work integrates mechanistic tumor modeling with machine learning to enable accurate, efficient, and individualized predictions of tumor spread. By combining reaction-diffusion formulations with structural information from diffusion tensor imaging, we capture how white matter architecture shapes glioma invasion. A learnable inference framework then bridges these biophysical models with data-driven parameter estimation, enabling fast and robust reconstruction of patient-specific tumor cell distributions from MRI. Together, these developments move toward clinically applicable tumor growth modeling for personalized radiotherapy planning.

Attachments:

File	Description	File size
Brain Tumor Growth Modeling for Radiotherapy Planning.png	Research	121 kB
Jonas_Weidner_headshot.jpg	Headshot	139 kB