ECCOMAS 2022

6/6/22    11:00 - 13:00
Image-informed computational models and methods for prediction of cancer growth and treatment response I  
Minisymposium organized by Guillermo Lorenzo, David A. Hormuth II, Chengyue Wu, Ernesto A.B.F. Lima, Michael R. A. Abdelmalik, Alessandro Reali, Thomas J.R. Hughes and Thomas E. Yankeelov
Room: O – 3
MS16A
Chair: Guillermo Lorenzo
CoChair: Michael R. A. Abdelmalik
A Cahn-Hilliard Keller-Segel model for tumor growth with angiogenesis
Abramo Agosti, Alice Giotta Lucifero, Sabino Luzzi and Elisabetta Rocca

Image-informed biomechanical model for glioblastoma growth: a combined descriptive and predictive model
Meryem Abbad Andaloussi, Andreas Hursch, Frank Hertel, Stéphane Urcun and Stéphane Bordas

Fitting the evolution of glioma‘s mean radius before and after radiotherapy with a simple biophysical model
Leo Adenis, Stephane Plaszczynski, Basile Grammaticos, Johan Pallud and Mathilde Badoual

Patient-specific prediction of the growth of asymptotic meningiomas using spatial mechanistic modeling and deep learning
Annabelle Collin, Oliver Saut and Virginie Montalibet

Modeling and simulation of vascular tumors embedded in evolving capillary networks
Marvin Fritz, Prashant K. Jha, Tobias Köppl, J. Tinsley Oden, Andreas Wagner and Barbara Wohlmuth

Personalized computational forecasting of prostate cancer growth during active surveillance
Guillermo Lorenzo, Jon S. Heiselman, Michael A. Liss, Michael I. Miga, Hector Gomez, Thomas E. Yankeelov, Thomas J. R. Hughes and Alessandro Reali