Northwestern researchers develop method for predicting brain tumor growth, enhancing therapy
February 3, 2013 •
Northwestern researchers have developed a method to predict brain tumor growth, allowing for a quicker way to determine how well therapy is working, according to a University news release published in January.
Researchers carried out a study on the method, which was published Jan. 23 in the journal PLOS ONE, the release said. The study involved 33 patients with glioblastoma, the most common and aggressive type of brain cancer.
By allowing physicians to quickly pinpoint the effectiveness of a certain therapy, the method gives them a vehicle by which they can know to start using a new treatment, something important in time-sensitive cancer treatment, the release said.
“When a hurricane is approaching, weather models tell us where it’s going,” said the study’s senior author Kristin Swanson, professor and vice chair of research for neurological surgery at NU’s Feinberg School of Medicine, in the release. “Our brain tumor model does the same thing. We know how much and where the tumor will grow. Then we can know how much the treatment deflected that growth and directly relate that to impact on patient survival.”
To measure the effectiveness of a treatment, researchers used a computer-based prediction model. The model was based on MRI scans of each patient’s tumor on the day of diagnosis and the day of surgery and predicted how the tumor would grow without treatment, said the study’s lead author Maxwell Neal, a post-doctoral researcher in bioengineering at the University of Washington.
This method took into account the tumor’s three-dimensional shape, density and growth rate, attributes that current methods do not consider, according to the release.
Researchers determined the effectiveness of treatments by comparing the size of the tumor post-treatment to the predicted size of the tumor had it not been treated, the release said.
“The study demonstrated that higher-scoring patients survived significantly longer than lower-scoring patients and their tumors took significantly longer to recur,” Neal said in the release. “The score can guide clinicians in determining the effectiveness of the therapy.”
According to the release, NU researchers hope to make the model an iPad app or give access to it online.
— Jillian Sandler