Purpose: To evaluate obliquity and irregular surfaces as addressed by a commercial electron Monte Carlo dose calculation algorithm using custom made phantoms.
Methods: GAFChromic EBT-3 film was exposed using a Varian Linac and an edge-on orientation between acrylic slabs in order to validate obliquity factors as calculated by RayStation’s eMC algorithm along the central axis of the beam for 6, 9, 12, 16, and 20 MeV electron beams. Calculated and measured obliquity factors are tabulated in increments of 10 percent of each beam’s practical range. Calculated and measured shifts in dmax, d80, and d50 were also recorded. Next, phantoms approximating the challenging patient geometries of a nose and forearm were created out of beeswax (-100 HU). Additionally, an acrylic phantom approximating the curvature of a chest wall was used. Again, GAFChromic EBT-3 film was exposed using the edge-on orientation – this time to compare dose distributions in an axial slice along the beam’s central axis. Gamma analysis was performed using RIT’s Complete Patient QA tool.
Results: The majority of obliquity factors matched calculated values within 5 percent, and oblique incidence of 45 degrees was sufficient to result in dmax shifting upstream by over 5 mm in 6 MeV and 9 MeV beams, while shifting downstream approximately 20 MeV beams. An average of 88.72 percent of pixels passed gamma analysis (criteria between 3%/3mm and 5%/5mm).
Conclusion: This work demonstrates that custom-made phantoms can be constructed out of inexpensive materials in order to determine the performance of a TPS in challenging clinically relevant situations. Access to complex phantoms allows the user to go beyond the minimum requirements for a commercial system outlined in MPPG 5a. RayStation’s eMC algorithm handled the complexity introduced by oblique patient geometries effectively. Future work could benefit from added complexity by introducing heterogeneities within the same wax phantoms.
Commissioning, Obliquity Effect, Electron Therapy
TH- External Beam- Electrons: Computational dosimetry: Monte Carlo