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Long term responses of in-silico tumors to an anti-proliferative drug.

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posted on 2020-02-26, 18:36 authored by Jill A. Gallaher, Susan C. Massey, Andrea Hawkins-Daarud, Sonal S. Noticewala, Russell C. Rockne, Sandra K. Johnston, Luis Gonzalez-Cuyar, Joseph Juliano, Orlando Gil, Kristin R. Swanson, Peter Canoll, Alexander R. A. Anderson

The drug was applied continuously at 14d until 42d. A) From the growth dynamics, tumors are categorized into 4 outcomes given the final diameter at the end of treatment. We compare the same top 300 fits from Fig 4 and 4 example tumors (including the same 3 tumors from Fig 4) averaged over 10 runs. B-C) Imaging metrics and phenotypes for different outcomes. B) Top: Tumor rim size (dr distance from tumor core to 1% cellular density) vs. tumor core diameter (dc average diameter of at least 50% density) prior to treatment. Bottom: The change in dr vs. the change in dc before and after treatment. C) Top: Standard deviation in measured proliferation rate (σ) vs. average measured proliferation rate (p) prior to treatment. Bottom: The change in σ vs. the change in p before and after treatment. D) Top: Potential σ vs. potential p prior to treatment. Bottom: Change in potential σ vs. change in potential p before and after treatment. E) The spatial distributions for the recurrent tumors before and after treatment shown as densities and measured/potential phenotype combinations. Phenotypes are colored according to their combination of proliferation (P) and migration (M) rates according to the color key. Movies are available at jillagal.github.io/multiscaleGBM.