2-s2.0-85083653823

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[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2020 Greater Poland Cancer CentreImplementation of a modern treatment technique, such as IMRT, has been improved. In line with that, Monte Carlo (MC) simulations of this technique require the ability of complex beam configurations modelling with respect to the patient. The source 20 DOSXYZnrc with the dynamic and step and shoot technique can be used to simulate the modality. However, they have a different process to obtain the dose distribution in a certain phantom. This study aimed to compare the simulation efficiency and isodose dose distribution in a water phantom from various beam angles and multileaf collimator (MLC) positions in an IMRT plan using source 20. The 30 × 30 × 30 cm3 phantom was irradiated by Varian Clinac iX10MV photon beam with various field sizes from 2 × 2 to 6 × 6 cm2 using some beam angles 5°, 30°, 90°, 180°, and 300° and maintaining the source to surface distance (SSD) of 100 cm. The field-by-field and five-field methods were used to obtain the 3-dimensional (3D) dose distribution. The dose distribution of these methods was compared using the gamma index, DVH analysis, and simulation efficiency. Higher efficiency is better because it implies that it takes less time to reach a given uncertainty. The implementation of source 20 has been validated, with similar results, with validated source in DOSXYZnrc. The identical 3D-dimensions dose distributions using source 20 for dynamic and step and shoot were observed. Two simulations used the same number of histories with the statistical uncertainty of less than 3%. The step and shoot technique was more efficient than the dynamic simulation.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]Authors would like to thanks In house Insentif In House Post Doctoral 2018, World Class University Program, Institut Teknologi Bandung, Indonesia.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1016/j.rpor.2020.03.022[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]