A new MLC segmentation algorithm/software for step-and-shoot IMRT delivery

We present a new MLC segmentation algorithm/software for step-and-shoot IMRT delivery. Our aim in this work is to shorten the treatment time by minimizing the number of segments. Our new segmentation algorithm, called SLS (an abbreviation for static leaf sequencing), is based on graph algorithmic techniques in computer science. It takes advantage of the geometry of intensity maps. In our SLS approach, intensity maps are viewed as three-dimensional (3-D) "mountains" made of unit-sized "cubes." Such a 3-D "mountain" is first partitioned into special-structured submountains using a new mixed partitioning scheme. Then the optimal leaf sequences for each submountain are computed by either a shortest-path algorithm or a maximum-flow algorithm based on graph models. The computations of SLS take only a few minutes. Our comparison studies of SLS with CORVUS (both the 4.0 and 5.0 versions) and with the Xia and Verhey segmentation methods on Elekta Linac systems showed substantial improvements. For instance, for a pancreatic case, SLS used only one-fifth of the number of segments required by CORVUS 4.0 to create the same intensity maps, and the SLS sequences took only 25 min to deliver on an Elekta SL 20 Linac system in contrast to the 72 min for the CORVUS 4.0 sequences (a three-fold improvement). To verify the accuracy of our new leaf sequences, we conducted film and ion-chamber measurements on phantom. The results showed that both the intensity distributions as well as dose distributions of the SLS delivery match well with those of CORVUS delivery. SLS can also be extended to other types of Linac systems. (C) 2004 American Association of Physicists in Medicine.