Abstract

Simple Summary Understanding how brain tumors grow over time is important for improving and personalizing treatment. In this study, we used mathematical models to simulate tumor growth in the brain and tested how well these models can predict future changes using standard MRI scans. We looked at how different levels of image quality—such as noise, detail, and timing—affect the accuracy of these predictions. Our results show that even when the MRI data is not perfect, the models can still make reliable predictions about tumor growth, especially if the images are not noisy. This research may help guide the design of future imaging experiments to make useable predictions, potentially reducing the need for frequent or high-quality scans while still providing valuable insights into tumor behavior.