We present an improved multileaf collimator(MLC) segmentation algorithm, denoted by (static leaf sequencing with no tongue-and-groove error), for step-and-shoot intensity-modulated radiation therapy(IMRT) delivery. is an improvement over the MLC segmentation algorithm called SLS that was developed by Luan et al. [Med. Phys.31(4), 695–707 (2004)], which did not consider tongue-and-groove error corrections. The aims of are (1) shortening the treatment times of IMRT plans by minimizing their numbers of segments and (2) minimizing the tongue-and-groove errors of the computed IMRT plans. The input to is intensity maps (IMs) produced by current planning systems, and its output is (modified) optimized leaf sequences without tongue-and-groove error. Like the previous SLS algorithm [Luan et al., Med. Phys.31(4), 695–707 (2004)], is also based on graph algorithmic techniques in computer science. It models the MLC segmentation problem as a weighted minimum-cost path problem, where the weight of the path is the number of segments and the cost of the path is the amount of tongue-and-groove error. Our comparisons of with CORVUS indicated that for the same intensity maps, the numbers of segments computed by are up to 50% less than those by CORVUS 5.0 on the Elekta LINAC system. Our clinical verifications have shown that the dose distributions of the plans do not have tongue-and-groove error and match those of the corresponding CORVUS plans, thus confirming the correctness of . Comparing with existing segmentation methods, also has two additional advantages: (1) can compute leaf sequences whose tongue-and-groove error is minimized subject to a constraint on the maximum allowed number of segments, which may be desirable in clinical situations where a treatment with the complete correction of tongue-and-groove error takes too much time, and (2) can be used to minimize a more general type of error called the tongue-or-groove error.
The authors are very grateful to the anonymous reviewers for their highly constructive comments and suggestions. This work was supported in part by the National Science Foundation under Grant Nos. CCR-9988468 and CCF-0515203 and by the Faculty Research Program of the University of Notre Dame. The work of the first author was also supported in part by a faculty start-up fund from the Department of Computer Science at University of New Mexico. The work of the second author was also supported in part by Fellowships in 2004–2006 from the Center for Applied Mathematics, University of Notre Dame.
II. METHODS AND MATERIALS
II.A. Preliminaries and problem statement
II.A.1. Constraints of multileaf collimators and their geometry
II.A.2. Errors due to the MLC tongue-and-groove feature
II.A.3. The step-and-shoot MLC segmentation problem
II.B. New MLC segmentation algorithms for tongue-or-groove error control
II.B.1. Algorithm for basic segmentation problem with tongue-or-groove error control
II.B.2. General MLC segmentation algorithm with tongue-or-groove error control
II.C. algorithms with tongue-and-groove error control
III.B. Clinical verification
III.B.1. The clinical feasibility of
III.B.2. The correction of tongue-and-groove error
III.B.3. Calculating the tradeoff between errors and the number of MLC apertures
V. FUTURE WORK
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