An improved MLC segmentation algorithm and software for step-and-shoot IMRT delivery without tongue-and-groove error

Academic Article

Abstract

  • We present an improved multileaf collimator (MLC) segmentation algorithm, denoted by SLSNOTG (static leaf sequencing with no tongue-and-groove error), for step-and-shoot intensity-modulated radiation therapy (IMRT) delivery. SLSNOTG is an improvement over the MLC segmentation algorithm called SLS that was developed by Luan [Med. Phys. 31(4), 695-707 (2004)], which did not consider tongue-and-groove error corrections. The aims of SLSNOTG 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 SLSNOTG 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, Med. Phys. 31(4), 695-707 (2004)], SLSNOTG 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 SLSNOTG with CORVUS indicated that for the same intensity maps, the numbers of segments computed by SLSNOTG 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 SLSNOTG plans do not have tongue-and-groove error and match those of the corresponding CORVUS plans, thus confirming the correctness of SLSNOTG. Comparing with existing segmentation methods, SL SNOTG also has two additional advantages: (1) SLSNOTG 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) SLSNOTG can be used to minimize a more general type of error called the tongue-or-groove error. © 2006 American Association of Physicists in Medicine.
  • Authors

    Published In

  • Medical Physics  Journal
  • Digital Object Identifier (doi)

    Author List

  • Luan S; Wang C; Chen DZ; Hu XS; Naqvi SA; Wu X; Yu CX
  • Start Page

  • 1199
  • End Page

  • 1212
  • Volume

  • 33
  • Issue

  • 5