| Abstract | Mathematical modeling of tumor growth has been an active area of research for the past several decades. One of the holy grails of the field is to develop a simulation tool that can be utilized in the clinic to predict tumor progression and propose individualized treatment strategies. In this talk, I will discuss the work we have done with this long-term goal in mind. In particular, I will focus on both the implementation of, and the results drawn from, several of the models we have developed. Questions we have addressed through our modeling efforts include: 1. How do the geometry and topology of the environment in which a tumor grows impact the shape, size and spread of a tumor? What are the consequences for patient prognosis? 2. Under what conditions can a tumor overcome its limited blood supply and grow to a macroscopic size? 3. What is the likelihood that advantageous or deleterious genetic mutations arise within a tumor and how do these mutations impact growth dynamics? After looking at a set of model variants that allows each of these questions to be addressed, I talk about recent efforts to merge these models into one comprehensive cancer simulation tool. I use the merged model to highlight biological features that must be considered in a clinically-relevant tumor growth algorithm, and to test the impact of vascular-targeting treatment strategies. |
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