Purpose: The purpose of this work is to study the Bragg peak shifts and degradation caused by density and boundary changes in proton beam dose calculation Method and Material: Proton beam delivery provides promising dose characteristics as radiation dose can conform tightly to tumor while sparing surrounding healthy tissues. Proton particles deposit energy in a narrow range around the Bragg peak and as such the dose calculation is more challenging for that the Bragg peak is sensitive to tissue density, tissue composition and organ boundaries along the proton track path. We simulated a few scenarios to study the proton Bragg peak shift due to density and Bragg peak degradation due to change and boundary changes. The calculation of the three dimension dose matrix was performed using a 2 × 2 × 1 mm3 voxels in the depth peak dose range in water phantom after some rough simulation for the dose peak estimation. Results: Bragg peak shift at the iso‐center slice were found to follow a linear relationship with the density of heterogeneity insert based on our simulations with density ranging [0.4 2.0] g/cm∧3 which we studied. Bragg peak degradation and proton dose changed significantly due to low density and small beams size. Proton dose degraded when high energy proton beam irradiated to low density material. Proton dose degraded also when small beam with beam radius at several mm range. Conclusion: Proton dose calculation depends on many factors as Bragg peak is sensitive to tissue density and composition. Besides that, there exist several scenarios causing Bragg peak shift due to density change, causing Bragg peak degradation due to low density and small proton beam. The Monte Carlo simulation is a very accurate solution to provide precise dose distribution in inhomogeneous structures by simulating transport and energy deposition.

Purpose: In this study, we performed dependency study of proton dose on tissue composition using Monte Carlo models of Hounsfield number conversion and cadaver‐based anatomical data Method and Materials: Monte Carlo methods provide the most accurate radiation dose calculation technology as it take into account detailed materials properties, such as materials composition, mass density and interaction cross section. Monte Carlo simulation calculates the energy deposit per mass of each small volume (voxel) after a patient is presented by a large number of voxels. Two methods of building patient‐specified Monte Carlo models have been used in this study: one is to convert patient's CT Hounsfield numbers to materials; the other way is assign anatomical detailed materials using cadavers' segments. Dose distribution and dose volume histogram were compared based on the Monte Carlo models. Results: The dose distribution at the iso‐center slice, the 95% did not cover conformally to the ROI for Hounsfield MC model with shifting 2∼3 mm superior to the ROI. Dose volume history for planning tumor volume (PTV), Brain, Pituitary and Chiasm were used for evaluating the effect of tissue composition. The mean doses difference for PTV was 2.1% for the cadaver‐based MC and Hounsfield conversion MC model. The mean dose difference for Brain, Pituitary and Chiasm was less than 1.0%. Conclusion: Proton radiation dose was calculated and closely compared using two Monte Carlo models: one from CT Hounsfield number conversion and the other from human anatomically detailed Cadaver segments. It is found that the effect of different tissue composition on proton radiation dose calculation is complex involving organs at risk. Our method using cadaver‐based Monte Carlo model for proton dose calculation was shown to be suitable for benchmarking other Monte Carlo dose calculation methods and for providing tissue heterogeneity correction due to the effect of tissue composition.