Author: D. Michael Lovelock, Charlotte Elizabeth Read, Ren-Dih Sheu, Jing Wang, Tingyu Wang 👨🔬
Affiliation: Icahn School of Medicine at Mount Sinai, Jersey Shore University Medical Center 🌍
Purpose:
Early Eclipse models use rectangular fluence profiles (widened by the dosimetric leaf gap (DLG) to account for the fact that leaf tips are rounded). Eclipse Version 18 (V18) uses enhanced leaf modeling (ELM). ELM modeling eliminates the DLG by modeling the dose through rounded leaf tips. With the updated modeling, dosimetric differences between machines should, theoretically, only depend on the mechanical offset of the leaf tips (physical gap). Our investigation seeks to determine if V18 ELM modeling reduces dose differences between planned and delivered doses.
Methods:
On nine Millennium MLC-equipped machines, the following steps were taken: (1) Measure physical gap by setting a 1 mm gap and using a feeler gauge. (2) Conduct LoSasso’s sweeping gap measurement for ELM commissioning. (3) Measure dose from two IMRT small-field lung plans (3.5x4cm) on MapCHECK3. Small-field plans were selected as subtle MLC position differences would most strongly affect dose to small targets. (4) Compare measured dose to calculated dose (V15 and V18).
Results:
In the plan’s center (1x1.5cm), dose differences were around 1% between measured and calculated doses for both V15 and V18 for all plans. Strong correlation was observed between the physical gap and PTV90 dose for both lung plans (p=0.009, 0.001; Spearman’s Rank). Weaker correlation was found between LoSasso’s sweeping gap measurement and PTV90 dose for one of the plans (p=0.011; Spearman’s Rank). For, the other plan, no correlation was observed between LoSasso’s sweeping gap measurement and PTV90 dose.
Conclusion:
Dose differences were slightly smaller when calculating with ELM compared to DLG models. Physical gap measurements correlate with PTV90 dose in static IMRT plans. A 0.40 mm variation in a 1 mm gap leads to a maximum dose difference of up to 3.85%. We recommend incorporating physical gap into clinical QA programs to reduce intra-departmental machine dose differences.