Intensity Based Optimization Using Monte Carlo Dose Distribution for VMAT Plans
N Miri1*, A Pant2, S Bhagroo3, J Mathews4, D Nazareth1,2, (1) Roswell Park Comprehensive Cancer Center, Buffalo, NY (2) University at Buffalo, Buffalo, NY (3) University of Utah, Salt Lake City, UT (4) The Ohio State University, Columbus, OH
Presentations
PO-GePV-T-255 (Sunday, 7/10/2022) [Eastern Time (GMT-4)]
ePoster Forums
Purpose: To present an innovative method for VMAT dose optimization, based on Monte Carlo (MC) dose calculations and intensity modifications. The method improves quality of Eclipse-Generated plans by delivering more dose to targets and providing more sparing of OARs.
Methods: After a complete VMAT plan has been created in Eclipse, the DICOM files are exported. A primary dose calculation is performed, using the EGSnrc MC system, to calculate the dose contributions from individual control points (CPs). An optimization method then tunes the weight/intensity of each CP, based on a normalized clinical objective function. A DICOM plan file, containing the modified weights, is then imported into Eclipse for a final calculation. The new plan may be compared with the original and approved by the physician. The method was evaluated using 4 brain and 3 prostate VMAT clinical cases, with 6X, 6XFFF, and 10X energies.
Results: Using the new method, mean OAR doses decreased by 2.27% and 0.06%, and target doses increased by 0.28% and 0.6% for brain and prostate cases, respectively. For brain cases, more sparing was observed in at least one eye, lens, cochlea, and optic nerve for each plan. Some patients also demonstrated dose improvement in brainstem, optic tract, optic chiasm, and RA. The prostate plans did not benefit as much, with slight improvements seen in the penile bulb, femoral heads, and/or targets. The 6FFF patients received 150 less MUs while for the 6X and 10X cases, the average MU changes were 0 and +4 MUs, respectively.
Conclusion: Our intensity-based method improved VMAT treatment plan quality, with the most improvement observed for 6XFFF brain plans. Lung and head and neck plans will be investigated next. The method is currently being evaluated for potential clinical implementation.
Funding Support, Disclosures, and Conflict of Interest: We thank the University at Buffalo Center for Computational Research (UBCCR) for providing the high-performance computational resources for this project. We also thank Dr. Shawn Matott for helpful discussions. This work was supported by a grant from Fujitsu Corporation.
Keywords
Optimization, Treatment Planning, Monte Carlo
Taxonomy
TH- External Beam- Photons: IMRT/VMAT dose optimization algorithms
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