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Dosimetric evaluation of two phases of respiratory movement using a lung equivalent material for radiotherapy treatment planning

Published online by Cambridge University Press:  18 July 2019

Aysun Inal*
Affiliation:
Antalya Training and Research Hospital, Radiation Oncology Department, Antalya, Turkey
*
Author for correspondence: Aysun Inal, Antalya Training and Research Hospital, Radiation Oncology Department, Antalya, Turkey. E-mail: [email protected]

Abstract

Background/aim:

Radiation dosimetry requires special phantoms which are comparable with organs and tissues of a human body. The lung is one of the organs with a low density. Therefore, it is important to create and use lung equivalent phantoms in dosimetric controls. The aim of this study was to investigate the importance of using lung equivalent phantoms for different respiratory phases during measurements with both computed tomography (CT) and linear accelerator.

Materials and methods:

The maximum lung inhalation phantom (LIP) and lung exhalation phantom (LEP) were created for two respiratory phases. The Hounsfield Unit (HU) values based on the selected slice thickness and CT tube voltages were investigated, as well as the difference between energy and algorithms used in the treatment planning system.

Results:

It was found that the change in HU values according to slice thickness were more significant in measurements for respiratory phases. The dose difference between LEP and LIP at a point which is located 1 cm below the surface of the phantoms was found as 1·0% for 6 megavolt (MV) and 2·8% for 18 MV. The highest difference between the two algorithms was found to be 7·22% for 6 MV and 10·93% for 18 MV for LIP phantom.

Conclusion:

It can be said that the LIP and LEP phantoms prepared in accordance with respiratory phases can be a simple and inexpensive method to investigate any difference in dosimetry during respiratory phases. Also, measured and calculated dose values are in good agreement when thinner slice thickness was chosen.

Type
Original Article
Copyright
© Cambridge University Press 2019

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