title: An improved MLC segmentation algorithm and software for step-and-shoot IMRT delivery without tongue-and-groove error.
abstract: We present an improved multileaf collimator (MLC) segmentation algorithm, denoted by SLS(NOTG) (static leaf sequencing with no tongue-and-groove error), for step-and-shoot intensity-modulated radiation therapy (IMRT) delivery. SLS(NOTG) 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 SLS(NOTG) 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 SLS(NOTG) 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)], SLS(NOTG) 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 SLS(NOTG) with CORVUS indicated that for the same intensity maps, the numbers of segments computed by SLS(NOTG) 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 SLS(NOTG) plans do not have tongue-and-groove error and match those of the corresponding CORVUS plans, thus confirming the correctness of SLS(NOTG). Comparing with existing segmentation methods, SLS(NOTG) also has two additional advantages: (1) SLS(NOTG) 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) SLS(NOTG) can be used to minimize a more general type of error called the tongue-or-groove error.
authors.affiliation: Department of Computer Science, University of New Mexico, Albuquerque, New Mexico 87131, USA. sluan@cs.unm.edu
authors.forename: Shuang
authors.initials: S
authors.lastname: Luan
authors.forename: Chao
authors.initials: C
authors.lastname: Wang
authors.forename: Danny Z
authors.initials: DZ
authors.lastname: Chen
authors.forename: Xiaobo S
authors.initials: XS
authors.lastname: Hu
authors.forename: Shahid A
authors.initials: SA
authors.lastname: Naqvi
authors.forename: Xingen
authors.initials: X
authors.lastname: Wu
authors.forename: Cedric X
authors.initials: CX
authors.lastname: Yu
mesh_terms: D000465:Algorithms; D016477:Artifacts; D019583:Dose Fractionation, Radiation; D011786:Quality Control; D011829:Radiation Dosage; D011874:Radiometry / Q000379:methods*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D011881:Radiotherapy, Computer-Assisted / Q000379:methods*; D020266:Radiotherapy, Conformal / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity