The model uses information from magnetic resonance imaging (MRI) scans taken before and during therapy to monitor changes in tumour size. That information is plugged into the model to predict whether a particular case is responding well to treatment. If not, the patient can be changed to a more aggressive or experimental therapy midway through treatment, something not possible now.
The study, published in the journal Cancer Research, uses MRI scans and outcome information from 80 cervical cancer patients receiving a standard course of radiation therapy designed to cure their cancer. "The model enables us to better interpret clinical data and predict treatment outcomes for individual patients", stated principal investigator Jian Z. Wang, assistant professor of radiation medicine and a radiation physicist at the James Cancer Hospital and Solove Research Institute.
"The outcome predictions presented in this paper were solely based on changes in tumour volume as derived from MRI scans, which can be easily accessed even in community hospitals", Jian Z. Wang stated. "The model is very robust and can provide a prediction accuracy of 90 percent for local tumour control and recurrence."
A strength of the new model, said first author Zhibin Huang, is its use of MRI data to estimate three factors that play key roles in tumour shrinkage and that vary from patient to patient - the proportion of tumour cells that survive radiation exposure, the speed at which the body removes dead cells from the tumour, and the growth rate of surviving tumour cells.
The model is applicable to all cervical cancer patients, and the investigators are developing a model that can be applied to other cancer sites, Jian Z. Wang said.
Co-author Dr. Nina A. Mayr, professor of radiation medicine at Ohio State, noted that the size of cervical tumours is currently estimated by touch, or palpation, which is often imprecise. Furthermore, shrinkage of a tumour may not be apparent until months after therapy has ended. Other clinical factors currently used to predict a tumour's response to therapy include the tumour's stage, whether it has invaded nearby lymph nodes and its microscopic appearance.
"Our kinetic model helps us understand the underlying biological mechanisms of the rather complicated living tissue that is a tumour", Jian Z. Wang stated. "It enables us to better interpret clinical data and predict treatment outcomes, which is critical for identifying the most effective therapy for personalized medicine."
This study was supported by a grant from the National Cancer Institute. Other Ohio State researchers involved in this study were William T.C. Yuh, Simon S. Lo, Joseph F. Montebello, John C. Grecula, Lanchun Lu, Kaile Li, Hualin Zhang and Nilendu Gupta.
The Ohio State University Comprehensive Cancer Center - Arthur G. James Cancer Hospital and Richard J. Solove Research Institute is one of only 40 Comprehensive Cancer Centers in the United States designated by the National Cancer Institute. Ranked by U.S. News & World Report among the top 20 cancer hospitals in the nation, the James is the 180-bed adult patient-care component of the cancer programme at the Ohio State University. The OSUCCC-James is one of only seven programmes in the country approved by the NCI to conduct both Phase I and Phase II clinical trials.