Automated beam model optimization.
OBJECTIVE
The beam model in a three dimensional treatment planning system (TPS) defines virtually the mechanical and dosimetric characteristics of a treatment unit. The manual optimization of a beam model during commissioning can be a time consuming task due to its iterative nature. Furthermore, the quality of the beam model commissioning depends on the user's ability to manage multiple parameters and assess their impact on the agreement between measured and calculated dose. The objective of this work is to develop and validate the performance of an automated beam model optimization system (ABMOS) based on intensity modulated radiotherapy (IMRT) beam measurements to improve beam model accuracy while streamlining the commissioning process.


METHODS
The ABMOS was developed to adjust selected TPS beam model parameters iteratively to maximize the agreement between measured and calculated 2D dose maps obtained for an IMRT beam pattern. A 2D diode array with high spatial resolution detectors was used to sample the entire IMRT beam pattern in a single dose measurement. The use of an IMRT beam pattern with large number of monitor units was selected to highlight the difference between planned and delivered dose and improve the signal to noise ratio in the low dose regions. ABMOS was applied to the optimization of a beam model for an Elekta Synergy S treatment unit. The optimized beam model was validated for two anatomical sites (25 paraspinal and 25 prostate cases) using two independent patient-specific IMRT quality control (QC) methods based on ion chamber and 2D diode array measurements, respectively. The conventional approach of comparing calculated and measured beam profiles and percent-depth dose curves was also used to assess improvement in beam model after ABMOS optimization. Elements of statistical process control were applied to the process of patient-specific QC performed with the ion chamber and the 2D array to complement the model comparison.


RESULTS
After beam model optimization with ABMOS, improvement in planned to delivered dose agreement was demonstrated with both patient-specific IMRT QC methods and the calculated to measured profile comparison. In terms of ion chamber measurements, the largest improvement was observed for the paraspinal cases with the mean measured to calculated dose difference at the low dose points decreasing from - 13.8% to 2.0% with the optimized beam model. The 2D diode array patient-specific QC also demonstrated clearly the improvement in beam model for both paraspinal and prostate cases with, on average, more than 96% of the diodes satisfying tolerances of 3% of dose difference or 2 mm of distance to agreement after ABMOS optimization. The capability index (C(pk)) for both patient-specific QC methods also increased with the optimized beam model.


CONCLUSIONS
In this work, ABMOS was developed to use 2D diode array measurements of an IMRT beam pattern for the automated multivariable optimization of a TPS beam model. Based on the observed improvements in patient-specific QC results for 25 paraspinal and 25 prostate plans, optimization of the remaining clinical beam models using ABMOS is now ongoing in the institution.
Radiation Medicine Program, Princess Margaret Hospital, Toronto, Ontario, Canada. daniel.letourneau@rmp.uh.on.ca
Daniel
D
Létourneau
Michael B
MB
Sharpe
Amir
A
Owrangi
David A
DA
Jaffray
D001331:Automation; D006801:Humans; D011874:Radiometry; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated