Cervical cancer is highly curable when caught early. But in a third of
cases, the tumor responds poorly to therapy or recurs later, when cure
is much less likely.
Quicker identification of non-responding tumors may be possible
using a new mathematical model developed by researchers at the Ohio
State University Comprehensive Cancer Center-Arthur G. James Cancer
Hospital and Richard J. Solove Research Institute.
The model uses information from magnetic resonance imaging (MRI)
scans taken before and during therapy to monitor changes in tumor 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," says principal
investigator Jian Z. Wang, assistant professor of radiation medicine
and a radiation physicist at the OSUCCC-James.
"The outcome predictions presented in this paper were solely based
on changes in tumor volume as derived from MRI scans, which can be
easily accessed even in community hospitals," 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 new model, says first author Zhibin Huang, is its
use of MRI data to estimate three factors that play key roles in tumor
shrinkage and that vary from patient to patient — 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.
Co-author Dr. Nina A. Mayr, professor of radiation medicine at Ohio
State, notes that the size of cervical tumors is currently estimated by
touch, or palpation, which is often imprecise. Furthermore, shrinkage
of a tumor may not be apparent until months after therapy has ended.
Other clinical factors currently used to predict a tumor’s response
to therapy include the tumor’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 tumor,"
Wang says. "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.
Source : Ohio State University Medical Center