Predictive mathematical modeling to individualize radiation treatment margins for prostate cancer patients treated with image-guided radiation therapy (IGRT).
- Predicts patient specific prostate motion for treatment planning with multi-fractionated intensity modulated radiotherapy (IMRT).
- More accurate than conventional fixed treatment margin approaches which may over treat or undertreat some patients
- Potentially decreases toxicity by reducing radiation dose to the bladder and rectum.
Prostate cancer is the most common cancer in American men. Recent trends in imaging software and radiotherapy have been to improve treatment planning while simultaneously increasing safety and target accuracy for the patient during radiation. The prostate moves both between fractions of treatment (inter-fraction) and during treatment fractions themselves (intra-fraction) so there is a margin of error added around the clinical target volume to be treated. Although there are a number of methods to reduce the error associated with the motion of the prostate, none of these processes are adaptive and individualized for each patient’s pattern of organ motion.
Emory researchers have developed an adaptive treatment process in which predictive models are used to determine treatment margins that are specific to each prostate cancer patient during multi-fractionated intensity modulated radiotherapy (IMRT). The model is more accurate than current approaches that rely on fixed treatment margins which may over or under treat some patients. When the non-patient specific method is used ( 2mm uniform margin), future prostate motion was predicted for only 50% of patients (12 of 24 patients) tested. However using the models developed here, prostate motion during future treatment sessions was predicted for 91.7% of patients (2 of 24 patients). These new prediction models are an improvement over current approaches, allow for patient-specific customization of planning treatment margins, and may result in lower toxicity and radiation dose to surrounding organs.
Model was developed using data from the first five IMRT treatments and validated using the remaining data set in twenty-four patients.
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