University of Washington researchers have discovered a way to more accurately predict life expectancy in patients newly diagnosed with Glioblastoma Multiforme, the most aggressive form of primary brain tumors — and the type that took the life of Senator Ted Kennedy earlier this year.
This type of tumor accounts for 70% of malignant brain tumors diagnosed in the U.S. each year, and patients on average live only 12 to 18 months following diagnosis.
Researchers in the lab of Dr. Kristin Swanson, UW associate professor of pathology, have found the combination of biomathematical modeling and routinely available pre-treatment magnetic resonance images (MRI) allows physicians — for the first time — to quantify and visualize patient-specific tumor growth patterns and dynamics. The results are published in the Dec. 1, 2009 issue of Cancer Research.
Specifically, the researchers have shown that by using certain measurement information from the patient’s MRIs, they can apply the biomathematical model and correctly estimate how fast the glioma (cancer) cells are growing and where they will spread in each patient. The study shows that these calculated rates predict how long patients will survive, even when taking into account the current standard clinical predictors of survival, such as age.
With this information, clinicians have the ability to more accurately predict the clinical course of each patient’s disease.
“This ground-breaking approach will allow patients to receive uniquely tailored treatments specific to their individual tumor,” said Swanson, who led the study.
Although additional clinical research is ongoing, Swanson said these results show this biomathematical model to be a unique tool for quantifying and predicting malignant brain tumor growth patterns, and suggests a role for the development of personalized, patient-specific treatment and management of these aggressive tumors.