title: Leaf position optimization for step-and-shoot IMRT.
abstract: OBJECTIVE
  To describe the theoretical basis, the algorithm, and implementation of a tool that optimizes segment shapes and weights for step-and-shoot intensity-modulated radiation therapy delivered by multileaf collimators.
  
  
  METHODS
  The tool, called SOWAT (Segment Outline and Weight Adapting Tool) is applied to a set of segments, segment weights, and corresponding dose distribution, computed by an external dose computation engine. SOWAT evaluates the effects of changing the position of each collimating leaf of each segment on an objective function, as follows. Changing a leaf position causes a change in the segment-specific dose matrix, which is calculated by a fast dose computation algorithm. A weighted sum of all segment-specific dose matrices provides the dose distribution and allows computation of the value of the objective function. Only leaf position changes that comply with the multileaf collimator constraints are evaluated. Leaf position changes that tend to decrease the value of the objective function are retained. After several possible positions have been evaluated for all collimating leaves of all segments, an external dose engine recomputes the dose distribution, based on the adapted leaf positions and weights. The plan is evaluated. If the plan is accepted, a segment sequencer is used to make the prescription files for the treatment machine. Otherwise, the user can restart SOWAT using the new set of segments, segment weights, and corresponding dose distribution. The implementation was illustrated using two example cases. The first example is a T1N0M0 supraglottic cancer case that was distributed as a multicenter planning exercise by investigators from Rotterdam, The Netherlands. The exercise involved a two-phase plan. Phase 1 involved the delivery of 46 Gy to a concave-shaped planning target volume (PTV) consisting of the primary tumor volume and the elective lymph nodal regions II-IV on both sides of the neck. Phase 2 involved a boost of 24 Gy to the primary tumor region only. SOWAT was applied to the Phase 1 plan. Parotid sparing was a planning goal. The second implementation example is an ethmoid sinus cancer case, planned with the intent of bilateral visus sparing. The median PTV prescription dose was 70 Gy with a maximum dose constraint to the optic pathway structures of 60 Gy.
  
  
  RESULTS
  The initial set of segments, segment weights, and corresponding dose distribution were obtained, respectively, by an anatomy-based segmentation tool, a segment weight optimization tool, and a differential scatter-air ratio dose computation algorithm as external dose engine. For the supraglottic case, this resulted in a plan that proved to be comparable to the plans obtained at the other institutes by forward or inverse planning techniques. After using SOWAT, the minimum PTV dose and PTV dose homogeneity increased; the maximum dose to the spinal cord decreased from 38 Gy to 32 Gy. The left parotid mean dose decreased from 22 Gy to 19 Gy and the right parotid mean dose from 20 to 18 Gy. For the ethmoid sinus case, the target homogeneity increased by leaf position optimization, together with a better sparing of the optical tracts.
  
  
  CONCLUSIONS
  By using SOWAT, the plans improved with respect to all plan evaluation end points. Compliance with the multileaf collimator constraints is guaranteed. The treatment delivery time remains almost unchanged, because no additional segments are created.
authors.affiliation: Division of Radiotherapy, Ghent University Hospital, Ghent, Belgium.
authors.forename: W
authors.initials: W
authors.lastname: De Gersem
authors.forename: F
authors.initials: F
authors.lastname: Claus
authors.forename: C
authors.initials: C
authors.lastname: De Wagter
authors.forename: B
authors.initials: B
authors.lastname: Van Duyse
authors.forename: W
authors.initials: W
authors.lastname: De Neve
mesh_terms: D006801:Humans; D011878:Radiotherapy / Q000379:methods*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted