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Monte Carlo Validation of Simple Geometry in Homogeneous Medium for Pencil Beam Scanning

M Hobson*, L Coutinho, Miami Cancer Institute, Miami, FL


(Sunday, 7/12/2020)   [Eastern Time (GMT-4)]

Room: AAPM ePoster Library

Purpose: validate Monte Carlo (MC) calculations with RayStation (v. for proton pencil beam scanning for simple geometry in homogeneous medium with and without the presence of the range shifter.

Methods: plans were created using a synthetic water phantom. Rectangular right prisms of different positions and sizes were used as target volumes for calculation of various square field sizes for a set of energies and modulations. Treatment plans were optimized to create uniform doses in the target volume regions using Pencil Beam Algorithm (PBA) for open field and with the range shifter in three different snout positions. The MC plans were copies of the PBA plans and calculated with 0.1% uncertainty. The spot map and MU/spot were the same in the open field plans and range shifter plans as well as between the two algorithms. Measurements of the SOBP curves were performed using the Zebra (a multilayer ionization chamber). Absolute dosimetry measurements were performed in the middle of the SOBP and in water with a PPC05 ion chamber.

Results: field measurements compared to PBA and MC calculations were less than 0.7%. When the range shifter was present, the maximum and minimum percent differences for the PBA versus measurements at the same depth were 6.109% and -0.623%, respectfully, while for MC were 1.000% and -0.870%, respectfully.

Conclusion: larger discrepancies between calculated and measured data occurred for PBA when the range shifter was present. The discrepancy was gradually reduced between the measurement and PBA when the snout position was closer to the water tank (i.e. minimizing the air gap). MC calculations typically had smaller discrepancies from measurements regardless of snout position.


Monte Carlo, Treatment Planning, Validation


TH- External Beam- Particle/high LET therapy: Proton therapy – computational dosimetry-Monte Carlo

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