507 research outputs found
Multicriteria VMAT optimization
Purpose: To make the planning of volumetric modulated arc therapy (VMAT)
faster and to explore the tradeoffs between planning objectives and delivery
efficiency.
Methods: A convex multicriteria dose optimization problem is solved for an
angular grid of 180 equi-spaced beams. This allows the planner to navigate the
ideal dose distribution Pareto surface and select a plan of desired target
coverage versus organ at risk sparing. The selected plan is then made VMAT
deliverable by a fluence map merging and sequencing algorithm, which combines
neighboring fluence maps based on a similarity score and then delivers the
merged maps together, simplifying delivery. Successive merges are made as long
as the dose distribution quality is maintained. The complete algorithm is
called VMERGE.
Results: VMERGE is applied to three cases: a prostate, a pancreas, and a
brain. In each case, the selected Pareto-optimal plan is matched almost exactly
with the VMAT merging routine, resulting in a high quality plan delivered with
a single arc in less than five minutes on average.
VMERGE offers significant improvements over existing VMAT algorithms. The
first is the multicriteria planning aspect, which greatly speeds up planning
time and allows the user to select the plan which represents the most desirable
compromise between target coverage and organ at risk sparing. The second is the
user-chosen epsilon-optimality guarantee of the final VMAT plan. Finally, the
user can explore the tradeoff between delivery time and plan quality, which is
a fundamental aspect of VMAT that cannot be easily investigated with current
commercial planning systems
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