Two-step validation of a Monte Carlo dosimetry framework for general radiology

被引:5
作者
Dedulle, An [1 ,2 ]
Fitousi, Niki [1 ]
Zhang, Guozhi [3 ]
Jacobs, Jurgen [1 ]
Bosmans, Hilde [2 ,3 ]
机构
[1] Qaelum NV, Gaston Geenslaan 9, B-3001 Leuven, Belgium
[2] Univ Leuven, Div Med Phys & Qual Assessment, Dept Imaging & Pathol, Herestr 49, B-3000 Leuven, Belgium
[3] Univ Hosp Leuven, Dept Radiol, Herestr 49, B-3000 Leuven, Belgium
来源
PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS | 2018年 / 53卷
关键词
Monte Carlo; Dosimetry; General radiology; CONE-BEAM CT; ORGAN; SIMULATION; TOOL; MODELS; PHOTON; ADULT;
D O I
10.1016/j.ejmp.2018.08.005
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
The Monte Carlo technique is considered gold standard when it comes to patient-specific dosimetry. Any newly developed Monte Carlo simulation framework, however, has to be carefully calibrated and validated prior to its use. For many researchers this is a tedious work. We propose a two-step validation procedure for our newly built Monte Carlo framework and provide all input data to make it feasible for future related application by the wider community. The validation was at first performed by benchmarking against simulation data available in literature. The American Association of Physicists in Medicine (AAPM) report of task group 195 (case 2) was considered most appropriate for our application. Secondly, the framework was calibrated and validated against experimental measurements for trunk X-ray imaging protocols using a water phantom. The dose results obtained from all simulations and measurements were compared. Our Monte Carlo framework proved to agree with literature data, by showing a maximal difference below 4% to the AAPM report. The mean difference with the water phantom measurements was around 7%. The statistical uncertainty for clinical applications of the dosimetry model is expected to be within 10%. This makes it reliable for clinical dose calculations in general radiology. Input data and the described procedure allow for the validation of other Monte Carlo frameworks.
引用
收藏
页码:72 / 79
页数:8
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