Comparison of VMAT complexity-reduction strategies for single-target cranial radiosurgery with the Eclipse treatment...

Complexity in MLC-based radiosurgery treatment delivery can be characterized by the efficiency of monitor unit (MU) utilization and the average MLC leaf separation distance for a treatment plan. A reduction in plan complexity may be desirable if plan quality is not impacted. In this study, a number of strategies are explored to determine how plan quality is affected by efforts to reduce plan complexity. Ten radiosurgery cases of varying complexity are retrospectively planned using six optimization strategies: an unconstrained volumetric modulated arc therapy (VMAT) technique, a MU-constrained VMAT technique, three techniques using various strengths of the aperture shape controller (ASC), and a hybrid technique consisting of a final-stage VMAT optimization applied to a dynamic conformal arc leaf sequence (ODCA). The plans are compared in terms of MU efficiency, MLC leaf-separation, conformity index (CI), gradient index (GI), and QA measurement results. The five VMAT techniques exhibited only minor differences in CI and GI values, though the ASC and MU-constrained techniques did require 6-20% fewer MU and had mean field apertures 5-19% larger. On average, the ODCA technique had CI values 3.5% lower and GI values 1.0-2.5% higher than the VMAT techniques, but also had a mean field aperture 24-47% larger and required 16-32% fewer MU. The QA measurement results showed a 0.61% variation in mean per-field 2%/1 mm gamma passing rates across all techniques (range 96.81%-97.42%), with no observed correlation between passing rate and technique. For simple targets, the ODCA technique achieved CI results that were equivalent to the unconstrained VMAT technique with an average 30% reduction in required MU, an average 50% increase in mean leaf separation distance, and brain V12_Gy values within 0.38 cc of the VMAT technique for targets up to approximately 2 cm diameter. For MLC-based single-target radiosurgery, plan complexity can often be significantly reduced without an equivalent reduction in plan quality.