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    Keywords: OPTIMIZATION ; radiotherapy ; tumor ; ALGORITHM ; ALGORITHMS ; INFORMATION ; SYSTEM ; SYSTEMS ; RISK ; treatment ; ASSOCIATION ; FORM ; TARGET ; NO ; DISTRIBUTIONS ; EQUIVALENT ; RADIATION-THERAPY ; HEAD ; NECK ; head and neck ; CONVEX-SETS ; equivalent uniform dose ; inverse planning ; optimization constraints ; projection onto convex sets ; PROJECTIONS
    Abstract: Optimization algorithms in inverse radiotherapy planning need information about the desired dose distribution. Usually the planner defines physical dose constraints for each structure of the treatment plan, either in form of minimum and maximum doses or as dose-volume constraints. The concept of equivalent uniform dose (EUD) was designed to describe dose distributions with a higher clinical relevance. In this paper, we present a method to consider the EUD as an optimization constraint by using the method of projections onto convex sets (POCS). In each iteration of the optimization loop, for the actual dose distribution of an organ that violates an EUD constraint a new dose distribution is calculated that satisfies the EUD constraint, leading to voxel-based physical dose constraints. The new dose distribution is found by projecting the current one onto the convex set of all dose distributions fulfilling the EUD constraint. The algorithm is easy to integrate into existing inverse planning systems, and it allows the planner to choose between physical and EUD constraints separately for each structure. A clinical case of a head and neck tumor is optimized using three different sets of constraints: physical constraints for all structures, physical constraints for the target and EUD constraints for the organs at risk, and EUD constraints for all structures. The results show that the POCS method converges stable and given EUD constraints are reached closely. (C) 2003 American Association of Physicists in Medicine
    Type of Publication: Journal article published
    PubMed ID: 14528955
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