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SU‐E‐T‐659: Inverse Treatment Planning for MERT Using Monte Carlo Calculations
Author(s) -
Henzen D,
Manser P,
Frei D,
Volken W,
Neuenschwander H,
Joosten A,
Born EJ,
Fix MK,
Stampai M
Publication year - 2013
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4815086
Subject(s) - monte carlo method , inverse , radiation treatment planning , simulated annealing , aperture (computer memory) , dosimetry , voxel , computer science , nuclear medicine , mathematical optimization , medical physics , algorithm , physics , mathematics , radiation therapy , medicine , surgery , statistics , artificial intelligence , geometry , acoustics
Purpose: The use of electron beams to treat shallow tumors cou ld reduce the dose to the distal organs at risk. To employ modulated electron radiotherapy (MERT) an inverse treatment planning strategy which bases on a Monte Carlo (MC) Electron Beam Model (EBM) has been developed. Methods: The inverse planning process starts with the selection of the SSD, gantry angle and co llimator rotation for each electron field. These fields are then divided into a grid of beamlets. An MC EBM together with the macro MC (MMC) dose calculation algorithm is employed to pre‐calculate the dose distribution for each beamlet. Afterwards a direct aperture optimization (DAO) using simulated annealing minimizes a co st function which is the sum of the squared dose differences in all voxels of the PTV and the OARs between the actual value and a given upper or lower limit. For each step either a weight change or an aperture change is initiated. As the beamlet dose calculation neglects the MLC interaction a post processing weight optimization and MLC aperture adjustment has been carried out after the DAO has been finished. To test the algorithm an inverse treatment plan has been created for an academic situation and co mpared to the obtained results using a previously developed forward planning strategy. Results: The implementation of an inverse optimization inco rporating the home made EBM has been completed successfully. The time needed for the DAO of the academic situation is about 30 min. Compared to the forward planning the inverse optimization is able to reduce the dose to the OAR (mean dose from 41% to 38%) for the academic case. Conclusion: The developed inverse optimization employing the EBM and MMC can be used for treatment planning of MERT. This work was supported by Varian Medical Systems. This work was supported by Varian Medical Systems.