Computer models of tumor growth help target effective cancer treatment
Northwestern University researchers have taken inspiration from storm forecasting to gauge how well treatment is working for patients with brain cancer.
That information can prompt doctors to more quickly switch to a different treatment and ultimately improve patient survival. In a study published this week in the journal PLOS One, researchers focused on treatment for glioblastoma multiforme (GBM), the most malignant type of primary brain tumor.
"When a hurricane is approaching, weather models tell us where it's going. Our brain tumor model does the same thing. We know how much and where the tumor will grow," senior author Kristin Swanson, professor and vice chair of research for neurological surgery at Northwestern University Feinberg School of Medicine, said in an announcement. "Then we can know how much the treatment deflected that growth and directly relate that to impact on patient survival."
The researchers first compared MRI scans the patient received on the day of diagnosis and on the day of first treatment, then created a computer model of the tumor based on its three-dimensional shape, density and growth rate. The model forecast how the tumor would grow if left untreated. Then doctors could compare the rate of growth after treatment with the predicted rate from the model.
The study involved 33 patients, all of whom underwent individualized treatment plans, and scored them on a metric the researchers created called "Days Gained"--the number of days a therapy delayed tumor progression. Higher-scoring patients in the study survived significantly longer than lower-scoring patients, and their tumors took significantly longer to recur.
In addition to providing the ability to gauge the effectiveness of treatment, the work illustrates the value of patient-specific computational modeling, the authors wrote.
Researchers in Pakistan combined weather-forecasting techniques with Google Flu Trends to show how predictive modeling could pinpoint flu outbreaks in specific areas up to seven weeks beforehand.
As the means for delivering personalized medicine growth, 3-D technology has played an emerging role. Researchers at the University of Manchester have developed a 3-D model of the heart to learn more about the development of atrial fibrillation, while biomedical engineering researchers at Arizona State University and physicians at Phoenix Children's Hospital and St. Joseph's Hospital and Medical Center have created custom heart models for surgery planning to reduce the likelihood of complications.
Doctors in France used a 3-D model from previous CT scans to guide them during surgery to avoid damage to a nerve that ran along an abnormal path in a patient's neck as they removed a tumor.
Prediction model combines Google Flu Trends, weather forecasting techniques
3-D heart models used to improve surgery planning
3-D imaging guides doctors during surgery
Researchers develop virtual heart to study atrial fibrillation