Dynamics of a model for brain tumors reveals a small window for therapeutic intervention

Glioblastomas are the most malignant and most common glioma, a type of primary brain tumor with the unfortunate ability to recur despite extensive treatment. Even with the advent of medical imaging technology during the last two decades, successful treatment of glioblastomas has remained elusive. It has become increasingly clear that, along with the proliferative potential of these neoplasms, it is the subclinically diffuse invasion of glioblastomas that primarily contributes to their resistance to treatment. In other words, the inevitable recurrence of these tumors is the result of diffusely invaded but invisible tumor cells peripheral to the abnormal signal on medical imaging and to the current limits of surgical, radiological and chemical treatments.
Mathematical modeling has presented itself as a viable tool for studying complex biological processes (Murray, 1993, 2002). We have developed a mathematical model that portrays the growth and extension of theoretical glioblastoma cells in a matrix that accurately describes the brain's anatomy to a resolution of 1 cu mm (Swanson, et al, 1999, 2000, 2002, 2003a, 2003b). The model assumes that only two factors need be considered for such predictions: net growth rate and infiltrative ability. The model has already provided illustrations of theoretical glioblastomas that not only closely resemble the MRIs (magnetic resonance imaging) of actual patients, but also show the distribution of the diffusely infiltrating cells.