Program
| CTF3b | |
|---|---|
| Russ Rockne | |
| University of Washington | |
| Title | The role of delay and observation timing in assessing glioma response to radiation therapy. |
| Abstract | Gliomas are malignant brain tumors characterized by their high proliferation rate and diffuse invasion of surrounding tissue. High grade gliomas known as glioblastoma multiforme (GBM) are uniformly fatal with a median survival of 12 months from diagnosis. Radiation therapy is widely considered a first-line treatment for gliomas and is conventionally given in daily doses, with target volumes based on the imageable disease burden assessed on post surgical magnetic resonance imaging (MRI). Response to radiation therapy is typically quantified clinically as the change in MRI imageable tumor volume from pre to post therapy -in addition to mental status and the doctor's clinical experience. The problem of quantifying disease response to therapy is compounded by the delay between the administration of therapy and the resulting changes in tumor volume in conjunction with the timing of the MRI observations relative to treatment. Moreover, increases in tumor volume immediately post treatment, known as 'pseudo progression' of disease, have been attributed to treatment effect rather than actual disease progression. We extend a model for glioma response to radiation therapy previously presented by us (model I) (Rockne et al) and others (Powathil et al) to include a sub population of tumor cells affected by radiation therapy–determined by a spatially defined survival probability–that decay at a rate related to the pre-treatment proliferation rate (model II). Using the brainweb brain atlas (Cocosco et al) and in vivo parameter values taken from an actual glioma patient, we construct a fully 3 dimensional, anatomically accurate in silico virtual glioma patient. Using the clinically-defined spatial and temporal radiation dose prescription for that patient, we simulate radiation therapy on the virtual patient using both models I) and II). Results from model II) suggests that an optimal time for observing tumor response to therapy can be assessed on a patient-specific basis such that pseudo progression or treatment effect can more accurately be distinguished from actual tumor progression. Moreover, pseudo progression may be the result of observation timing relative to the rate of treatment response. Results from both model implementations are systematically compared and contrasted to each other and also to the actual patient data. ________________________________________ Rockne R, Alvord EC, Jr., Rockhill JK, Swanson KR. A mathematical model for brain tumor response to radiation therapy. J Math Biol 2009; 58: 561-78. Powathil G, Kohandel M, Sivaloganathan S, Oza A, Milosevic M. Mathematical modeling of brain tumors: effects of radiotherapy and chemotherapy. Phys Med Biol 2007; 52: 3291-306. Cocosco CA, Kollokian V, K.-S. KR, Evans AC. Brainweb: Online interface to a 3D simulated brain database. Neuroimage 1997; 5: S425. |
| Coauthors | Kristin R Swanson |
| Location | Woodward 3 |