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

Published online by Cambridge University Press:  29 July 2016

Yelda Elcim*
Affiliation:
Department of Radiation Oncology, Gülhane Military Medical Academy, Ankara, Turkey
Bahar Dirican
Affiliation:
Department of Radiation Oncology, Gülhane Military Medical Academy, Ankara, Turkey
Omer Yavas
Affiliation:
Department of Engineering Physics, Ankara University, Ankara, Turkey
*
Correspondence to: Yelda Elcim, Department of Radiation Oncology, Gülhane Military Medical Academy, 06018 Ankara, Turkey. Tel: +90 533 085 6635. E-mail: yeldaelcim@gmail.com
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Abstract

Purpose

The 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 materials

Target 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 conclusions

Comparative 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.

Information

Type
Original Articles
Copyright
© Cambridge University Press 2016 
Figure 0

Figure 1 Head and neck treatment fields.

Figure 1

Figure 2 Location number, Rando phantom slice number, Thermoluminescent Dosimeter (TLD) number and TLD location for head and neck treatment fields.

Figure 2

Table 1 Demonstrating comparative analysis of point doses and Thermoluminescent Dosimeter (TLD) measured doses acquired from treatment planning systems with pencil beam (PB) and collapsed cone convolution (CCC) algorithms for head and neck treatment plannings

Figure 3

Figure 3 Comparative analysis of point doses with pencil beam (PB) and collapsed cone convolution (CCC) algorithms for head and neck treatment plannings.

Figure 4

Figure 4 Chest wall–supraclavicular region treatment fields.

Figure 5

Figure 5 Location number, Rando phantom slice number, Thermoluminescent Dosimeter (TLD) number, TLD location for chest wall–supraclavicular region treatment fields.

Figure 6

Table 2 Demonstrating comparative analysis of point doses and Thermoluminescent Dosimeter (TLD) measured doses acquired from treatment planning systems with pencil beam (PB) and collapsed cone convolution (CCC) algorithms for chest wall–supraclavicular region treatment plannings

Figure 7

Figure 6 Comparative analysis of point doses with pencil beam (PB) and collapsed cone convolution (CCC) algorithms for chest wall–supraclavicular region treatment plannings.

Figure 8

Figure 7 Lung treatment fields.

Figure 9

Figure 8 Location number, Rando phantom slice number, Thermoluminescent Dosimeter (TLD) number, TLD location for lung treatment fields.

Figure 10

Table 3 Demonstrating comparative analysis of point doses and Thermoluminescent Dosimeter (TLD) measured doses acquired from treatment planning systems with pencil beam (PB) and collapsed cone convolution (CCC) algorithms for lung treatment plannings

Figure 11

Figure 9 Comparative analysis of point doses with pencil beam (PB) and collapsed cone convolution (CCC) algorithms for lung treatment plannings.

Figure 12

Figure 10 Prostate treatment fields.

Figure 13

Figure 11 Location number, Rando phantom slice number, Thermoluminescent Dosimeter (TLD) number, TLD location for prostate treatment plannings.

Figure 14

Table 4 Demonstrating comparative analysis of point doses and Thermoluminescent Dosimeter (TLD) measured doses acquired from treatment planning systems with pencil beam (PB) and collapsed cone convolution (CCC) algorithms for prostate treatment plannings

Figure 15

Figure 12 Comparative analysis of point doses with pencil beam (PB) and collapsed cone convolution (CCC) algorithms for prostate treatment plannings.