Mathematical modeling of tumor response to radiation therapy (RT) has great potential for designing therapy plans that are more personalized, more adaptive, and more reliable for outcome predictions. A preexisting model of tumor response to radiation therapy for cervical cancer has been shown to generate model parameters that correlate strongly with both tumor local control and disease-specific survival. This model is further developed through incorporation of another effect of RT not previously accounted for: the oxygen effect. An easily obtainable form of input data, hemoglobin level, enables simulation of the oxygen effect simultaneously with the other major model effects. For the Local Control (LC) patient group, the changes in the model parameters caused by incorporation of the oxygen effect are found to significantly improve the agreement of those parameters with actual patient data. For the Local Failure (LF) group and the overall patient group, the oxygen effect is incorporated without significant change to the agreement between the model-simulated output parameters and the actual patient data. Also, a strategy is presented for solving the main model equations to obtain analytic expressions for surviving cell fraction and regression volume ratio as functions of time.
|Commitee:||Day, Orville, Dingfelder, Michael, Lin, Zi-Wei|
|School:||East Carolina University|
|School Location:||United States -- North Carolina|
|Source:||MAI 53/06M(E), Masters Abstracts International|
|Subjects:||Applied Mathematics, Nuclear physics, Oncology|
|Keywords:||Cervical cancer, Medical physics, Oxygen effect, Patient model, Radiation oncology|
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