Modeling Tumor-Associated Edema in Gliomas during Anti-Angiogenic Therapy and Its Impact on Imageable Tumor

Abstract

Glioblastoma, the most aggressive form of primary brain tumor, is predominantly assessed with gadolinium-enhanced T1-weighted (T1Gd) and T2-weighted magnetic resonance imaging (MRI). Pixel intensity enhancement on the T1Gd image is understood to correspond to the gadolinium contrast agent leaking from the tumor-induced neovasculature, while hyperintensity on the T2/FLAIR images corresponds with edema and infiltrated tumor cells. None of these modalities directly show tumor cells; rather, they capture abnormalities in the microenvironment caused by the presence of tumor cells. Thus, assessing disease response after treatments impacting the microenvironment remains challenging through the obscuring lens of MR imaging. Anti-angiogenic therapies have been used in the treatment of gliomas with spurious results ranging from no apparent response to significant imaging improvement with the potential for extremely diffuse patterns of tumor recurrence on imaging and autopsy. Anti-angiogenic treatment normalizes the vasculature, effectively decreasing vessel permeability and thus reducing tumor-induced edema, drastically altering T2-weighted MRI. We extend a previously developed mathematical model of glioma growth to explicitly incorporate edema formation allowing us to directly characterize and potentially predict the effects of anti-angiogenics on imageable tumor growth. A comparison of simulated glioma growth and imaging enhancement with and without bevacizumab supports the current understanding that anti-angiogenic treatment can serve as a surrogate for steroids and the clinically driven hypothesis that anti-angiogenic treatment may not have any significant effect on the growth dynamics of the overall tumor cell populations. However, the simulations do illustrate a potentially large impact on the level of edematous extracellular fluid, and thus on what would be imageable on T2/FLAIR MR. Additionally, by evaluating virtual tumors with varying growth kinetics, we see tumors with lower proliferation rates will have the most reduction in swelling from such treatments.

Oedema‐based model for diffuse low‐grade gliomas: application to clinical cases under radiotherapy

“…However, it appears that the basic migration–proliferation model, such as the one used by Rockne and collaborators for high‐grade gliomas , cannot account for the most striking feature of clinical follow up – radii following RT; reduction of tumour radius lasts much longer than the treatment itself. The same group has proposed a migration–proliferation model with oedema and angiogenesis for high‐grade gliomas that is closer to our approach .…”

Emergence of spatial structure in the tumor microenvironment due to the Warburg effect

“…Experimental Validation with a Tissue Mimetic System. Computational model predictions can be compared with in vivo data, such as imaging (43,44), but models are difficult to test experimentally. In vivo manipulations are technically challenging and in vitro models often neglect important features such as spatial structure.…”

A spatial model predicts that dispersal and cell turnover limit intratumour heterogeneity

“…Several models of the genetic evolution of expanding tumours have been developed in the past 11–14 , but they assume either very few mutations 11,12 or one- or two-dimensional growth 13,14 . Conversely, models that incorporate spatial limitations have been developed to help to understand processes such as tumour metabolism 15 , angiogenesis 16,17 and cell migration 12 , but these models ignore genetics. Here, we formulate a model that combines spatial growth and genetic evolution, and use the model to describe the growth of primary tumours and metastases, as well as the development of resistance to therapeutic agents.…”