A parameter optimization algorithm for intensity-modulated radiotherapy prostate treatment planning.
An iterative algorithm has been developed to analytically determine patient specific input parameters for intensity-modulated radiotherapy prostate treatment planning. The algorithm starts with a generic set of inverse planning parameters that include dose and volume constraints for the target and surrounding critical structures. The overlap region between the target volume and the rectum is used to determine the optimized target volume coverage goal. Sequential iterations are performed to vary the numerous parameters individually or in sets while other parameters remain fixed. A coarse grid search is first used to avoid convergence on a local maximum. Linear interpolation is then used to define a region for a fine grid search. Selected parameters are also tested for possible improvements in target coverage. In several representative test cases investigated the coverage of the planning target volume improved with the use of the algorithm while still meeting the clinical acceptability criteria for critical structures. The algorithm avoids time-consuming random trial and error variations that are often associated with difficult cases and also eliminates lengthy user learning curves. The methodology described in this paper can be applied to any treatment planning system that requires the user to select the input optimization parameters.
Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, 23 Pocono Rd., Denville, New Jersey 07834, USA. barbierj@mskcc.org
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Barbiere
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Chan
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Mechalakos
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Cann
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Schupak
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Burman
D000465:Algorithms; D004307:Dose-Response Relationship, Radiation; D006801:Humans; D008297:Male; D011471:Prostatic Neoplasms / Q000532:radiotherapy*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D020266:Radiotherapy, Conformal / Q000379:methods*; D012007:Rectum / Q000528:radiation effects; D001743:Urinary Bladder / Q000528:radiation effects