Author: Kenny Guida, Hongyu Jiang, Harold Li, Hem Bahadur Moktan Tamang 👨🔬
Affiliation: University of Nebraska Medical Center, Department of Radiation Oncology, University of Kansas Medical Center 🌍
Purpose: Varian Eclipse v18.0 introduced Enhanced Leaf Model (ELM) of MLC, which provides better dose calculation accuracy than original DLG-based MLC model. The leaf-gap (LG) parameter for ELM represents the true mechanical calibration, whereas DLG varies with beam energy and flattening filter use. Therefore, differences between ELM and DLG modeling might demonstrate flattening filter dependance irrespective of plan optimization and delivery technique. This study compared the differences in calculated dose for IMRT and VMAT fields using both MLC models for 6X and 6FFF.
Methods: Dynamic zebra crosswalk (DZC) plans consisting of sweeping MLC gaps (1, 2 and 3mm) across a 3cm width at 0cm, 4cm, 8cm, and positions along x-axis were created for Varian Edge with HD-MLCs. Phantom dose was calculated in Eclipse using AAA v15.6 and v18.0 (with ELM) for 6X and 6X-FFF DZC plans. Additionally, 10 single-isocenter multiple-target (SIMT) VMAT cases were retrospectively planned with 6X and 6X-FFF and calculated using both AAA versions. Measurements were performed with SNC SRS MapCHECK.
Results: Both 6X and 6FFF DZC profile central dose differences (v18.0 vs v15.6) for all sweeping gaps increased with increasing off-axis distance, with larger differences seen for 6X, as compared to 6FFF. For sweeping gaps of 1mm, 2mm, and 3mm at 12cm off-axis, dose differences of 19.0% and 26.0%,13.5% and 18.1%, and 10.5% and 13.9% were seen for 6FFF and 6X, respectively. SIMT plans showed an average increase in PTV maximum dose of 1.9% for 6FFF VMAT (range 0.4-3.7%) and 2.9% for 6X VMAT (range 1.2-5.0%) when switching from v15.6 to v18.0. QA measurements demonstrated greater differences in gamma pass rates for 6X compared to 6FFF.
Conclusion: Our findings suggest that the differences between ELM and DLG modeling is more dependent on flattening filter than plan optimization and delivery technique.