Direct leaf trajectory optimization for volumetric modulated arc therapy planning with sliding window delivery
D\'avid Papp, Jan Unkelbach

TL;DR
This paper introduces a new optimization model for VMAT that directly computes deliverable leaf trajectories, streamlining the planning process and achieving high-quality treatment plans within practical delivery times.
Contribution
It presents a novel direct leaf trajectory optimization method that eliminates the need for separate arc sequencing in VMAT planning, accounting for machine constraints.
Findings
VMAT plans closely match IMRT quality within 3-4 minutes delivery time.
The method explicitly incorporates MLC constraints like leaf speed and interdigitation.
Optimized plans are feasible with constant gantry speed and adaptable to variable speed.
Abstract
We propose a novel optimization model for volumetric modulated arc therapy (VMAT) planning that directly optimizes deliverable leaf trajectories in the treatment plan optimization problem, and eliminates the need for a separate arc-sequencing step. In this model, a 360-degree arc is divided into a given number of arc segments in which the leaves move unidirectionally. This facilitates an algorithm that determines the optimal piecewise linear leaf trajectories for each arc segment, which are deliverable in a given treatment time. Multi-leaf collimator (MLC) constraints, including maximum leaf speed and interdigitation, are accounted for explicitly. The algorithm is customized to allow for VMAT delivery using constant gantry speed and dose rate, however, the algorithm generalizes to variable gantry speed if beneficial. We demonstrate the method for three different tumor sites: a…
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