SU‐GG‐J‐05: Monte Carlo Investigation and Measurements of Distal Edge Degradation in Lung Phantoms with Therapeutic Proton Beams

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Abstract

Purpose: To validate a computational lung model and investigate distal edge degradation of therapeutic proton beams. Methods and Materials: We used the Monte Carlo code MCNPX to simulate therapeutic proton beams traversing a computational lung model. The computational lung model consisted of a slab constituted of randomly distributed voxels of air and plastic resin. Two computational lung slabs with different voxel resolutions were studied including: i) a high resolution slab (0.5 mm cubic voxels), which was assembled by randomly distributing the air and plastic resin voxels. This slab assembly reproduces the density gradient found in real lung‐equivalent plastic slabs (realistic lung‐equivalent slab); and ii) a low resolution slab (2 mm cubic voxels), which was generated by merging neighbor voxels and appropriately scaling the density and atomic fractions. This slab has a similar density distribution to a CT image (CT‐equivalent slab). All simulations were done using a validated MCNPX model of the passive scattering beam line from the Proton Therapy Center at M.D. Anderson Cancer Center. Our simulations were compared to measured depth doses of a therapeutic proton beam traversing a lung‐equivalent plastic slab. Results: The distal edge degradation predicted by the simulations of the realistic lung‐equivalent slab was in agreement with the experimental data. However simulations of proton doses from beams traversing the CT‐equivalent lung slab did not show any distal edge degradation. Conclusion: Our findings show that a computational lung phantom model with high resolution is needed to accurately predict the distal edge of proton dose distributions.

Original languageEnglish (US)
Pages (from-to)3145
Number of pages1
JournalMedical physics
Volume37
Issue number6
DOIs
StatePublished - Jun 2010

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

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