Hostname: page-component-84b7d79bbc-2l2gl Total loading time: 0 Render date: 2024-07-28T22:49:25.140Z Has data issue: false hasContentIssue false
  • English
  • Français

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 Open the ORCID record for Aysun Inal [Opens in a new window]
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: aysuntoy@yahoo.com
Get access Rights & Permissions [Opens in a new window]

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.

Keywords

radiotherapycorkdosimetrylung phantomrespiratory phase
Type
Original Article
Information
Journal of Radiotherapy in Practice , Volume 19 , Issue 2 , June 2020 , pp. 157 - 162
Copyright
© Cambridge University Press 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Karimi, R, Tornling, G, Forsslund, Het al.Lung density on high resolution computer tomography (HRCT) reflects degree of inflammation in smokers. Respir Res 2014; 15 (1): 23–33. doi:10.1186/1465-9921-15-23.CrossRefGoogle ScholarPubMed
Fraass, B, Doppke, K, Hunt, Met al.American Association of Physicists in Medicine Radiation Therapy Committee Task Group 53: quality assurance for clinical radiotherapy treatment planning. Med Phys 1998; 25 (10): 1773–1829. doi :10.1118/1.598373CrossRefGoogle Scholar
Ma, C M, Jiang, S B, Pawlicki, Tet al.A quality assurance phantom for IMRT dose verification. Phys Med Biol 2003; 48 (5): 561–572. doi:10.1088/0031-9155/48/5/301CrossRefGoogle ScholarPubMed
Ravichandran, R, Binukumar, J P, Sivakumar, S S, Krishnamurthy, K, Davis, C AA method for estimation of accuracy of dose delivery with dynamic slit windows in medical linear accelerators. J Med Phys 2008; 33: 127–129. doi:10.4103/0971-6203.42768CrossRefGoogle ScholarPubMed
Chang, K P, Hung, S H, Chie, Y H, Shiau, A C, Huang, R JA comparison of physical and dosimetric properties of lung substitute materials. J Med Phys 2012; 39 (4): 2013–2020. doi:10.1118/1.3694097CrossRefGoogle ScholarPubMed
Cloutier, R JTissue substitutes in radiation dosimetry and measurement. Radiat Res 1989; 119 (3): 582.doi:10.2307/3577533.CrossRefGoogle Scholar
Hurkmans, C W, van Lieshout, M, Schuring, Det al.Quality assurance of 4D-CT scan techniques in multicenter phase III trial of surgery versus stereotactic radiotherapy (Radiosurgery or Surgery for operable early stage (Stage 1A) non-small-cell Lung cancer [Rosel] Study). Int J Radiat Oncol Biol Phys 2011; 80 (3): 918–927. doi:10.1016/j.ijrobp.2010.08.017.CrossRefGoogle Scholar
Aarup, L R, Nahum, A E, Zacharatou, Cet al.The effect of different lung densities on the accuracy of various radiotherapy dose calculation methods: implications for tumour coverage. Radiother Oncol 2009; 91: 405–414.doi:10.1016/j.radonc.2009.01.008.CrossRefGoogle ScholarPubMed
Lee, J J, Kim, N, Seo, J B, Lee, H, Shin, Y G.Automatic non-rigid lung registration method for the visualization of regional air trapping in chest CT scans. Proceedings of the 11th International Conference on Medical Imaging Computing and Computer 10 Assisted Intervention MICCAI, New York, NY, USA, September 6–10, 2008, pp. 195–201.Google Scholar
Batho, H FLung corrections in cobalt 60 beam therapy. J Can Assoc Radiol 1964; 15: 79–83.Google ScholarPubMed
Al-Hallaq, H A, Reft, C S, Roeske, J C (2006) The dosimetric effects of tissue heterogeneities in intensity-modulated radiation therapy (IMRT) of the head and neck. Phys Med Biol 2006; 51 (5): 1145–1156. doi:10.1088/0031-9155/51/5/007.CrossRefGoogle ScholarPubMed
Papanikolaou, N, Battista, J J, Boyer, A Let al. Tissue inhomogeneity correction for megavoltage photon beams: Report of the Task Group No. 65 of the Radiation Therapy Committee of the American Association of Physicist in Medicine. AAPM Report No 85. Madison, WI: AAPM, 2004.Google Scholar
Ahnesjö, A, Weber, L, Murman, Aet al.Beam modeling and verification of a photon beam multisource model. Med Phys 2005; 32 (6): 1722–1737. doi:10.1118/1.1898485.CrossRefGoogle ScholarPubMed
Knöös, T, Ceberg, C, Weber, L, Nilsson, P (1994) The dosimetric verification of a pencil beam based treatment planning system. Phys Med Biol 1994; 39 (10): 1609–1628. doi:10.1088/0031-9155/39/10/007CrossRefGoogle ScholarPubMed
Watanabe, YDerivation of linear attenuation coefficients from CT numbers for low-energy photons. Phys Med Biol 1999; 44 (9): 2201–2211. doi:10.1088/0031-9155/44/9/308.CrossRefGoogle ScholarPubMed
Groell, R, Rienmueller, R, Schaffler, G Jet al.CT number variations due to different image acquisition and reconstruction parameters: a thorax phantom study. Comput Med Imag Grap 2000; 24 (2): 53–58. doi:10.1016/s0895-6111(99)00043-9.CrossRefGoogle ScholarPubMed
Kilby, W, Sage, J, Rabett, VTolerance levels for quality assurance of electron density values generated from CT in radiotherapy treatment planning. Phys Med Biol 2002; 47 (9): 1485–1492. doi:10.1088/0031-9155/47/9/304 18.CrossRefGoogle ScholarPubMed
Millner, M R, McDavid, W D, Waggener, R Get al.Extraction of information from CT scans at different energies. Med Phys 1979; 6 (1): 70–71. doi:10.1118/1.594555.CrossRefGoogle ScholarPubMed
Cozzi, L, Fogliata, A, Buffa, F, Bieri, SDosimetric impact of computed tomography calibration on a commercial treatment planning system for external radiation therapy. Radiother Oncol 1998; 48 (3): 335–338. doi:10.1016/s0167-8140(98)00072-3.CrossRefGoogle ScholarPubMed
Guan, H, Yin, F F, Kim, J H (2002) Accuracy of inhomogeneity correction in photon radiotherapy from CT scans with different settings. Phys Med Biol 2002; 47 (17): N223–N231. doi:10.1088/0031-9155/47/17/402.CrossRefGoogle ScholarPubMed
Kendall, R L, Gifford, K A, Kirsner, S MThe impact of peak-kilovoltage settings on heterogeneity-corrected photon-beam treatment plans. Radiother Oncol 2006; 81 (2): 206–208. doi:10.1016/j.radonc.2006.10.005.CrossRefGoogle ScholarPubMed
Zurl, B, Tiefling, R, Winkler, P, Kindl, P, Kapp, K SHounsfield units variations: impact on CT-density based conversion tables and their effects on dose distribution. Strahlenther Onkol 2014; 90 (1): 88–93. doi:10.1007/s00066-013-0464-523.CrossRefGoogle Scholar
Ebert, M A, Lambert, J, Greer, P BCT-ED conversion on a GE Lightspeed-RT scanner: influence of scanner settings. Australas Phys Eng Sci Med 2008; 31 (2): 154–159. doi:10.1007/bf03178591.CrossRefGoogle ScholarPubMed