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SU‐E‐T‐850: Selection of Initial DVH Constraints for IMRT Planning Based on Target Dose Gradient Characteristics
Author(s) -
Zhang L,
Court L,
Choi B,
Palmer M,
Dong L
Publication year - 2011
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3612814
Subject(s) - radiation treatment planning , nuclear medicine , dosimetry , isocenter , pinnacle , medical physics , field (mathematics) , computer science , mathematics , radiation therapy , medicine , imaging phantom , radiology , pure mathematics
Purpose: One major obstacle for IMRT planning is to set up proper DVH constraints for organs at risk (OARs). Inexperienced IMRT planners often set OAR constraints using generic clinical guidelines, which may not always produce the best organ sparing. The goal of this study is to incorporate dose gradient information to set up the most likely achievable OAR dose tolerance. Methods: We investigated the dose falloff characteristics from typical IMRT plans. We found that the fastest dose falloff from a prostate plan can be universally used to describe the best scenario of dose gradient near the PTV. We also found the multi‐field near‐field dose falloff is different from the far‐field dose falloff, which is usually described by the attenuation of a single beam. We used an open‐field un‐modulated dose calculation to simulate the far‐field dose falloff. Also, we calculated the Euclidean distance map to translate the dose fall‐off to regional dose distribution. This dose distribution solely based on the distance from PTV and dose gradient information was reloaded back into the original plan. The DVHs calculated from this dose‐gradient plan represents the best scenario of OAR sparing. Those DVH values for OARs were used as initial estimation of DVH objective function for IMRT planning. Results: We applied our approach to 2 head‐and‐neck patients, 2 lung patients, and 2 prostate patients. We found the 40% dose falloff from the target dose prescription best represents the dose distribution in the near‐field. IMRT plans re‐optimized based on OAR constraints set by the dose‐gradient method produced better OAR sparing than the clinical plans for bladder (in prostate plans), heart (in lung plans), and oral cavity (in head‐and‐neck plans). All other organs produced similar results. Conclusions: We have designed a novel approach to incorporate dose gradient information as dose constraints for IMRT optimization.