Author: Ian J. Butterwick, Sumudu Katugampola, ChangSeon Kim, Evan G. Meekins, Zhengdong Zhang 👨🔬
Affiliation: Mount Sinai Beth Israel, Gesinger Medical Center, Geisinger Medical Center 🌍
Purpose: To evaluate the dosimetric impact of enhanced dynamic leaf gap (EDLG) modeling in Eclipse V18.0 on small-field dosimetry within VMAT plans.
Methods: Plans with small fields (1 cm x 1 cm to 4 cm x 4 cm) and sweeping gap sizes (0.4 cm, 0.6 cm, and 2.0 cm) were created to assess dosimetric effects. Verification plans were analyzed using 2D gamma index (SNC Patient, Sun Nuclear) for small fields and using 3D gamma index (3D Slicer, slicer.org) for sweeping beams. Three clinical VMAT plans (head and neck, lung and brain) were generated, and their Dose Volume Histograms (DVHs) and target conformity indices were compared to assess the impact of enhanced leaf modeling.
Results: The EDLG modeling measurements showed improvement in accuracy in small-field dosimetry. Comparison of verification plans revealed a gamma passing rate of >99.5% for 1 cm x 1 cm fields between EDLG and conventional DLG models. The enhanced leaf gap settings (0.4 cm) in V18 resulted in a more controlled out-of-field dose falloff for the narrow sweeping beam, as assessed through 3D gamma analysis. For the three clinical cases, the conformity indices were higher in EDLG modeling by 15.9%, 3.7% and 6.7% compared to conventional DLG modeling, for the sites H&N, Brain and Lung, respectively.
Conclusion: This study shows that EDLG gap modeling adapted in Eclipse V18.0 improves small-field dosimetry in VMAT plans. The results demonstrate higher accuracy for small and narrow fields. Both small field and narrow sweeping beams improved out-of-field dose falloff, ensuring more precise target dose delivery and better sparing of healthy tissues. These findings highlight EDLG model’s potential to optimize small-field dosimetry and improve clinical treatment precision.