Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/3503961.3503974acmotherconferencesArticle/Chapter ViewAbstractPublication PagesvsipConference Proceedingsconference-collections
research-article

Influence of Attenuation Coefficient and Exit Gap on EPID Measurement in Radiotherapy

Published: 08 March 2022 Publication History

Abstract

In order to improve the safety and treatment quality of patients in radiotherapy, it is necessary to verify the dose delivery in radiotherapy. EPID has the advantages of fast acquisition speed, large imaging area, high resolution, good linear response and long-term stability, and has been used in the quality verification of radiotherapy. EPID is used to place under the patient during in vivo dose verification. The distance between the patient and the EPID will affect the pixel value of the EPID. In order to accurately use EPID for radiation therapy dose verification, we used a series of measurement data to model the attenuation coefficient and exit gap of the EPID. The EPID transmission image calculated using the modeling data is compared with the actual measured EPID transmission image to verify the accuracy of the model.

References

[1]
P. B. Greer. 2005. Correction of pixel sensitivity variation and off-axis response for amorphous silicon EPID dosimetry. Med Phys, vol. 32, pp. 3558-68.
[2]
H. Gustafsson, P. Vial, Z. Kuncic, C. Baldock, J. W. Denham, and P. B. Greer. 2011. Direct dose to water dosimetry for pretreatment IMRT verification using a modified EPID. Med Phys, vol. 38, pp. 6257-64.
[3]
P. M. McCowan, E. Van Uytven, T. Van Beek, G. Asuni, and B. M. McCurdy. 2015. An in vivo dose verification method for SBRT-VMAT delivery using the EPID. Med Phys, vol. 42, pp. 6955-63.
[4]
W. J. van Elmpt, S. M. Nijsten, B. J. Mijnheer, and A. W. Minken, "Experimental verification of a portal dose prediction model," (in eng), Med Phys, vol. 32, pp. 2805-18, Sep 2005.
[5]
W. van Elmpt, S. Nijsten, S. Petit, B. Mijnheer, P. Lambin, and A. Dekker. 2009. 3D in vivo dosimetry using megavoltage cone-beam CT and EPID dosimetry. Int J Radiat Oncol Biol Phys, vol. 73, pp. 1580-7.
[6]
D. W. Bailey, L. Kumaraswamy, M. Bakhtiari, H. K. Malhotra, and M. B. Podgorsak. 2012. EPID dosimetry for pretreatment quality assurance with two commercial systems. J Appl Clin Med Phys, vol. 13, p. 3736.
[7]
A. Mans 2010. 3D Dosimetric verification of volumetric-modulated arc therapy by portal dosimetry. Radiother Oncol, vol. 94, pp. 181-7.
[8]
M. Wendling, R. J. Louwe, L. N. McDermott, J. J. Sonke, M. van Herk, and B. J. Mijnheer. 2006. Accurate two-dimensional IMRT verification using a back-projection EPID dosimetry method. (in eng), Med Phys, vol. 33, pp. 259-73.
[9]
A. Alhazmi 2018. A novel approach to EPID-based 3D volumetric dosimetry for IMRT and VMAT QA. Phys Med Biol, vol. 63, p. 115002.
[10]
K. Chytyk and B. M. McCurdy. 2009. Comprehensive fluence model for absolute portal dose image prediction," Med Phys, vol. 36, pp. 1389-98.
[11]
K. Chytyk-Praznik, E. VanUytven, T. A. vanBeek, P. B. Greer, and B. M. McCurdy, 2013."Model-based prediction of portal dose images during patient treatment," Med Phys, vol. 40, p. 031713.
[12]
H. C. Woodruff .2015. "First Experience With Real-Time EPID-Based Delivery Verification During IMRT and VMAT Sessions," Int J Radiat Oncol Biol Phys, vol. 93, pp. 516-22.
[13]
S. Deshpande, S. J. Blake, A. Xing, P. E. Metcalfe, L. C. Holloway, and P. Vial.2018."A simple model for transit dosimetry based on a water equivalent EPID," Med Phys, vol. 45, pp. 1266-1275.
[14]
J. Martinez Ortega .2018. "A collapsed-cone based transit EPID dosimetry method," Phys Med, vol. 46, pp. 75-80.
[15]
R. Boellaard, M. van Herk, and B. J. Mijnheer.1997.A convolution model to convert transmission dose images to exit dose distributions. Med Phys, vol. 24, pp. 189-99.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
VSIP '21: Proceedings of the 2021 3rd International Conference on Video, Signal and Image Processing
November 2021
143 pages
ISBN:9781450385886
DOI:10.1145/3503961
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 March 2022

Permissions

Request permissions for this article.

Check for updates

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Funding Sources

Conference

VSIP 2021

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 15
    Total Downloads
  • Downloads (Last 12 months)2
  • Downloads (Last 6 weeks)0
Reflects downloads up to 04 Oct 2024

Other Metrics

Citations

View Options

Get Access

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media