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Dosimetric Comparison of Carbon and Proton Radiotherapy for Recurrent Nasopharynx Carcinoma

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Y Sheng

Y Sheng1*, J Zhao1 , W Wang1 , L Lin1 , X Liu1 , K Shahnazi1 (1) Shanghai Proton and Heavy Ion Center, SHANGHAI, CHINA


SU-F-T-198 (Sunday, July 31, 2016) 3:00 PM - 6:00 PM Room: Exhibit Hall

Various radiotherapy planning methods for locally recurrent nasopharynx carcinoma (R-NPC) have been proposed. The purpose of this study was to compare carbon and proton therapy for the treatment of R-NPC in terms of dose coverage for target volume and sparing for organs at risk (OARs).
Six patients who were suffering from R-NPC and treated using carbon therapy were selected for this study. Treatment plans with a total dose of 57.5Gy (RBE) in 23 fractions were made using SIEMENS Syngo V11. An intensity-modulated radiotherapy optimization method was chosen for carbon plans (IMCT) while for proton plans both intensity-modulated radiotherapy (IMPT) and single beam optimization (proton-SBO) methods were chosen. Dose distributions, dose volume parameters, and selected dosimetric indices for target volumes and OARs were compared for all treatment plans.
All plans provided comparable PTV coverage. The volume covered by 95% of the prescribed dose was comparable for all three plans. The average values were 96.11%, 96.24% and 96.11% for IMCT, IMPT, and proton-SBO respectively. A significant reduction of the 80% and 50% dose volumes were observed for the IMCT plans compared to the IMPT and proton-SBO plans. Critical organs lateral to the target such as brain stem and spinal cord were better spared by IMPT than by proton-SBO, while IMCT spared those organs best. For organs in the beam path, such as parotid glands, the mean dose results were similar for all three plans.
Carbon plans yielded better dose conformity than proton plans. They provided similar or better target coverage while significantly lowering the dose for normal tissues. Dose sparing for critical organs in IMPT plans was better than proton-SBO, however, IMPT is known to be more sensitive to range uncertainties. For proton plans it is essential to find a balance between the two optimization methods.

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