Dosimetric comparison of treatment planning systems using collapsed cone convolution and pencil beam algorithms

Author:

Elcim Yelda,Dirican Bahar,Yavas Omer

Abstract

AbstractPurposeThe aim of this study is the dosimetric verification and comparative analysis of two different treatment planning systems (TPS) using collapsed cone convolution (CCC) and pencil beam (PB) algorithms for treatment sites of head and neck, chest wall–supraclavicular region, lung and prostate.Methods and materialsTarget volumes and critical organs for treatment sites mentioned above were delineated according to relevant The Radiation Therapy Oncology Group protocols. Treatment plans were generated using 6 MV photon energy with medical linear accelerator and Thermoluminescent Dosimeter-100 dosimeters were used to perform dosimetric verification, which were placed at appropriate locations in the Alderson Rando phantom.Results and conclusionsComparative analysis of CCC and PB algorithms for treatment sites revealed that point dose measurement values were higher with the PB algorithm compared with CCC algorithm, in both head and neck and chest wall–supraclavicular region plans. The most significant difference between two algorithms were found at the supraclavicular region which includes the lung point dose within the treatment field and 7–12 mm depth from the skin, respectively. Unlike the head and neck and chest wall–supraclavicular region plans, CCC and PB algorithms show overall comparable results in lung and prostate plans in terms of point dose measurement values; however, the most prominent difference was found in 7 mm and 6 cm depth from skin, respectively. The CCC algorithm values were higher. Our study confirms that the main reason of PB algorithm calculates less absorbed dose than CCC algorithm in medium transitions, skin entrance and irregular treatment regions is the underestimation of lateral equilibrium’s contribution to the total absorbed dose.

Publisher

Cambridge University Press (CUP)

Subject

Oncology,Radiology, Nuclear Medicine and imaging

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