Open AccessModelling Radiation Dose Distribution within Thorax using Monte Carlo Package Codes
Author(s) -
Sri Herwiningsih,
Andrew Fielding
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/546/3/032016
Subject(s) - monte carlo method , thorax (insect anatomy) , radiation treatment planning , nuclear medicine , radiation therapy , medical physics , data set , computer science , computed tomography , medicine , radiology , mathematics , statistics , artificial intelligence , anatomy
In radiotherapy practice, it is difficult to measure radiation dose within patient anatomy. Although it is possible to do so, the technique would cause discomfort and pain to the patient due to the insertion of the radiation detector inside the patient’s body. Monte Carlo simulation offer a non-invasive technique to estimate radiation dose distribution within the patient’s body. This paper presents a work on modelling the radiation dose distribution within the thorax region in lung cancer treatment cases. EGSnrc/DOSXYZnrc Monte Carlo codes were employed in this study. Patient anatomy was modelled by converting the images data obtained from Computed Tomography (CT) scan to EGSPHANT files. Three CT images set from three lung cancer patients were used in this study. The simulated data were compared with the treatment planning data by using a gamma analysis with selection criteria of 3% dose difference and 3 mm distance-to-agreement. The results show that a good agreement was obtained between the simulated data and the treatment planning data which is indicated by the gamma analysis results of > 95%.