Mathematical Model

Curing cervical cancer cases may be in the numbers

Jian WangCervical cancer is curable when caught early, but in a third of cases the tumor either responds poorly to therapy or recurs later, when it is more difficult to cure.

Quicker identification of nonresponding tumors may be possible using a new mathematical model developed by researchers at the OSUCCC – James. The model uses information from MRI scans taken before, during and after therapy to monitor changes in tumor size. That information is plugged into the model to predict much earlier whether a case is responding well to treatment. If not, the patient can sooner be offered a more aggressive or experimental therapy.

The study used MRI scans and outcome information from 80 cervical cancer patients receiving a standard curative course of radiation. “The model enables us to better interpret clinical data and predict treatment outcomes for individual patients,” says principal investigator and radiation physicist Jian Wang, PhD.

“The outcome predictions presented in this paper were based solely on changes in tumor volume as derived from MRI scans, which can be easily accessed,” Wang says. “The model is very robust and can provide a prediction accuracy of 90 percent for local tumor control and recurrence.”

A strength of the model, says first author Zhibin Huang, PhD, is its use of MRI data to estimate three factors that play key roles in tumor shrinkage and that vary among patients: the proportion of tumor cells that survive radiation exposure; the speed at which the body removes dead cells from the tumor; and the growth rate of surviving tumor 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, Wang says.

Published Jan. 15, 2010, in Cancer Research.

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