Comprehensive Monte Carlo study of patient doses from cone-beam CT imaging in radiotherapy
1The University of Manchester, Manchester Academic Health Science Centre, The Christie NHS Foundation Trust, Manchester, M20 4BX, UK. Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, M20 4BX, UK.
Abstract:
Accurate knowledge of ionizing radiation dose from cone-beam CT (CBCT) imaging in radiotherapy is important to allow concomitant risks to be estimated and for justification of imaging exposures. This study uses a Monte Carlo CBCT model to calculate imaging dose for a wide range of imaging protocols for male and female patients. The Elekta XVI CBCT system was modeled using GATE and simulated doses were validated against measurements in a water tank and thorax phantom. Imaging dose was simulated in the male and female ICRP voxel phantoms for a variety of anatomical sites and imager settings (different collimators, filters, full and partial rotation). The resulting dose distributions were used to calculate effective doses for each scan protocol. The Monte Carlo simulated doses agree with validation measurements within 5% and 10% for water tank and thorax phantom respectively. Effective dose for head CBCT scans was generally lower for scans centred on the pituitary than the larynx (0.03 mSv versus 0.06 mSv for male ICRP phantom). Pelvis CBCT scan effective dose was higher for the female than male phantom (5.11 mSv versus 2.80 mSv for M15 collimator scan), principally due to the higher dose received by gonads for the female scan. Medium field of view thorax scan effective doses ranged from 1.38-3.19 mSv depending on scan length and phantom sex. Effective dose for half rotation thorax scans with offset isocentre varied by almost a factor of three depending on laterality of the isocentre, patient sex and imaged field length. The CBCT imaging doses simulated here reveal large variations in dose depending on imaging isocentre location, patient sex and partial rotation angles. This information may be used to estimate risks from CBCT and to optimize CBCT imaging protocols.
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