Utilization of Log File Analysis to Determine Deliverability of VMAT Plans As a Function of Plan Complexity 📝

Author: Jameson T. Baker, Sean T Grace, Cindy Pham, Michael A. Trager 👨‍🔬

Affiliation: Northwell 🌍

Abstract:

Purpose:
In VMAT planning, increasing complexity in MLC motion and modulation may improve dose distributions and OAR sparing while maintaining PTV coverage. However, increasing complexity can create complications with accurate machine delivery. Often, challenges in deliverability can be mitigated by limiting plan complexity defined by Modulation Factor (MUF; plan MUs/fractional dose [cGy]) or relying on high gamma pass rates on patient specific IMRT QA (PSQA). PSQA may not show the full picture since it is limited by detector resolution, affected by user-setup, and uses simplified patient geometry. An alternative approach is using log files containing delivered parameters along with Monte Carlo calculations to recreate a realistic, 3D, high-definition dose distribution on patient geometry. This work aims to determine VMAT plan deliverability through gamma analysis results as a function of MUF using log file analysis (LFA) with Monte Carlo dose calculations.
Methods:
Eight plans were created (2 patients with 4 plans each; one pancreas and one prostate+nodes) with MUFs of approximately 2, 4, 6 and 8. Desired MUF was obtained with the MU min/max control in Eclipse (V16.1) inverse optimization. Deliverability was measured using gamma passing rates (γ values: 2%/2mm, 3%/2mm, 4%/2mm, 4%/3mm, 5%/2mm, 5%/3mm). These rates compared the planned Eclipse dose with the dose calculated by Monte Carlo methods using LFA in Radformation’s ClearCalc software (V2.5.14). Gamma passing rates were compared against the MUF.
Results:
Across all plans and MUFs there was minimal and clinically insignificant change in gamma pass rate, indicating that MUF is not indicative of plan deliverability up to MUF=8 for plans tested with forced MUF.
Conclusion:
Next steps will focus on expanding this work to include more treatment sites, other metrics of plan complexity beyond MUF, and determine the impact of field-specific MUF and use of field sizes smaller than those commissioned on plan deliverability.