Abstract

The important task of radiotherapy is to make sure that the radiation dose to the target tumour is accurate as prescribed and the dose to the organ at risk is minimized. Therefore, the aim of this study is to compare and evaluate the efficiency of the dose calculation algorithms: namely convolution, superposition, and fast superposition which installed in Treatment Planning System (TPS) (CMS XiO, USA). In this study, we modified protocols described in IAEATecdoc-1583, where four typical treatment techniques such as single field, multiple field, wedge field, and multi-leaf collimated (MLC) field were analysed from the system. The measurement data for calculated dose and measured dose were taken from thorax CIRS anthropomorphic phantom. The assessment of algorithms was done by comparing the point dose calculated with the measured dose. The study shows that the superposition algorithm produced relative error less than ± 3% which passed 100% of all reference points, whilst the convolution algorithm and fast superposition presented relative error more than ± 3% which passed 82% and 91% of reference points, respectively. In conclusion, the evaluation of radiotherapy treatment plan shall take into account the type of dose calculation algorithm model in order to optimize radiotherapy treatment and ensure the radiation safety to the patient.

Details

Title
Comparison of dose calculation algorithms model: Convolution, superposition, and fast superposition in 3-D Conformal Radiotherapy (3D-CRT) treatment plan
Author
Murat, H 1 ; Karim, M K A 2 ; Harun, H H 2 ; Kayun, Z 3 

 Department of Radiology, Hospital Sultanah Aminah, 80100 Johor Bharu, MALAYSIA; Department of Oncology, Institut Kanser Negara, 62590 Putrajaya, MALAYSIA 
 Department of Physics, Faculty of Science, Universiti Putra Malaysia, 43400 Serdang, MALAYSIA 
 Bahagian Kawalselia Radiasi Perubatan Kementerian Kesihatan Malaysia, 62590 Putrajaya, MALAYSIA 
Publication year
2019
Publication date
Jun 2019
Publisher
IOP Publishing
ISSN
17426588
e-ISSN
17426596
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2566271403
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.