PURPOSE: To present a methodology to estimate optimal treatment margins for radiotherapy of prostate cancer based on interfraction imaging. MATERIALS AND METHODS: Cone beam CT images of a prostate cancer patient undergoing fractionated radiotherapy were acquired at all treatment sessions. The clinical target volume (CTV) and organs at risk (OARs; bladder and rectum) were delineated in the images. Random sampling from the CTV-OAR library was performed in order to simulate fractionated radiotherapy including intra- and interpatient variability in setup and organ motion/deformation. For each simulated patient, four treatment fields defined by multileaf collimators were automatically generated around the planning CTV. The treatment margin (the distance from the CTV to the field border) was varied between 2.5 and 20 mm. Resulting dose distributions were calculated by a convolution method. Doses to OARs were reconstructed by polynomial warping, while the CTV was assumed to be a rigid body. The equivalent uniform dose (EUD), the tumor control probability (TCP) and the normal tissue complication probability (NTCP) were used to estimate the clinical effect. Patient repositioning strategies at treatment were compared. RESULTS: The simulations produced population based EUD histograms for the CTV and the OARs. The number of patients receiving an optimal target EUD increased with increasing margins, but at the cost of an increasing number receiving a high EUD to the OARs. Calculations of the probability of complication-free tumor control and subsequent analysis gave an optimal treatment margin of about 10mm for the simulated population, if no correction strategy was undertaken. CONCLUSIONS: The current work illustrates the principle of optimal treatment margins based on interfraction imaging. Clinically applicable margins may be obtained if a large patient image database is available.
PURPOSE: To present a methodology to estimate optimal treatment margins for radiotherapy of prostate cancer based on interfraction imaging. MATERIALS AND METHODS: Cone beam CT images of a prostate cancerpatient undergoing fractionated radiotherapy were acquired at all treatment sessions. The clinical target volume (CTV) and organs at risk (OARs; bladder and rectum) were delineated in the images. Random sampling from the CTV-OAR library was performed in order to simulate fractionated radiotherapy including intra- and interpatient variability in setup and organ motion/deformation. For each simulated patient, four treatment fields defined by multileaf collimators were automatically generated around the planning CTV. The treatment margin (the distance from the CTV to the field border) was varied between 2.5 and 20 mm. Resulting dose distributions were calculated by a convolution method. Doses to OARs were reconstructed by polynomial warping, while the CTV was assumed to be a rigid body. The equivalent uniform dose (EUD), the tumor control probability (TCP) and the normal tissue complication probability (NTCP) were used to estimate the clinical effect. Patient repositioning strategies at treatment were compared. RESULTS: The simulations produced population based EUD histograms for the CTV and the OARs. The number of patients receiving an optimal target EUD increased with increasing margins, but at the cost of an increasing number receiving a high EUD to the OARs. Calculations of the probability of complication-free tumor control and subsequent analysis gave an optimal treatment margin of about 10mm for the simulated population, if no correction strategy was undertaken. CONCLUSIONS: The current work illustrates the principle of optimal treatment margins based on interfraction imaging. Clinically applicable margins may be obtained if a large patient image database is available.