AuthorRutter, Erica M.
Stepien, Tracy L.
Anderies, Barrett J.
Plasencia, Jonathan D.
Woolf, Eric C.
Scheck, Adrienne C.
Turner, Gregory H.
Preul, Mark C.
Kostelich, Eric J.
AffiliationUniv Arizona, Dept Math
MetadataShow full item record
PublisherNATURE PUBLISHING GROUP
CitationMathematical Analysis of Glioma Growth in a Murine Model 2017, 7 (1) Scientific Reports
RightsOpen Access: This article is licensed under a Creative Commons Attribution 4.0 International License
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at firstname.lastname@example.org.
AbstractFive immunocompetent C57BL/6-cBrd/cBrd/Cr (albino C57BL/6) mice were injected with GL261-luc2 cells, a cell line sharing characteristics of human glioblastoma multiforme (GBM). The mice were imaged using magnetic resonance (MR) at five separate time points to characterize growth and development of the tumor. After 25 days, the final tumor volumes of the mice varied from 12 mm(3) to 62 mm(3), even though mice were inoculated from the same tumor cell line under carefully controlled conditions. We generated hypotheses to explore large variances in final tumor size and tested them with our simple reaction-diffusion model in both a 3-dimensional (3D) finite difference method and a 2-dimensional (2D) level set method. The parameters obtained from a best-fit procedure, designed to yield simulated tumors as close as possible to the observed ones, vary by an order of magnitude between the three mice analyzed in detail. These differences may reflect morphological and biological variability in tumor growth, as well as errors in the mathematical model, perhaps from an oversimplification of the tumor dynamics or nonidentifiability of parameters. Our results generate parameters that match other experimental in vitro and in vivo measurements. Additionally, we calculate wave speed, which matches with other rat and human measurements.
VersionFinal published version
SponsorsGraduate Assistance of Areas in National Need (GAANN) [P200A120120]; NSF [DMS-1148771]; National Science Foundation [DGE-1311230, 1512553, DMS-1518529, DMS-1615879]; Barrow Neurological Foundation and Arizona State University; Newsome United Kingdom Chair in Neurosurgery Research
- Improved model prediction of glioma growth utilizing tissue-specific boundary effects.
- Authors: Jacobs J, Rockne RC, Hawkins-Daarud AJ, Jackson PR, Johnston SK, Kinahan P, Swanson KR
- Issue date: 2019 Jun