2026-05-24T17:06:11Zhttps://keep.lib.asu.edu/oai/request

oai:keep.lib.asu.edu:node-1918882024-12-19T19:04:43Zoai_pmh:alloai_pmh:repo_items

191888 https://hdl.handle.net/2286/R.2.N.191888 http://rightsstatements.org/vocab/InC/1.0/ http://creativecommons.org/licenses/by-nc-sa/4.0 2024-05 24 pages Shayegan, Tara Kostelich, Eric Kuang, Yang Barrett, The Honors College School of Human Evolution & Social Change Text Glioblastoma Multiforme is a prevalent and aggressive brain tumor. It has an average 5-year survival rate of 6% and average survival time of 14 months. Using patient-specific MRI data from the Barrow Neurological Institute, this thesis investigates the impact of parameter manipulation on reaction-diffusion models for predicting and simulating glioblastoma growth. The study aims to explore key factors influencing tumor morphology and to contribute to enhancing prediction techniques for treatment. Brain Neurology Oncology tumor growth tumor prediction Glioblastoma Multiforme astrocytoma Analyzing Parameter Impact in Computational Modeling of Glioblastoma Multiforme Growth