Literature DB >> 25832039

A deformable head and neck phantom with in-vivo dosimetry for adaptive radiotherapy quality assurance.

Yan Jiang Graves1, Arthur-Allen Smith2, David Mcilvena2, Zherrina Manilay2, Yuet Kong Lai2, Roger Rice3, Loren Mell3, Xun Jia4, Steve B Jiang4, Laura Cerviño3.   

Abstract

PURPOSE: Patients' interfractional anatomic changes can compromise the initial treatment plan quality. To overcome this issue, adaptive radiotherapy (ART) has been introduced. Deformable image registration (DIR) is an important tool for ART and several deformable phantoms have been built to evaluate the algorithms' accuracy. However, there is a lack of deformable phantoms that can also provide dosimetric information to verify the accuracy of the whole ART process. The goal of this work is to design and construct a deformable head and neck (HN) ART quality assurance (QA) phantom with in vivo dosimetry.
METHODS: An axial slice of a HN patient is taken as a model for the phantom construction. Six anatomic materials are considered, with HU numbers similar to a real patient. A filled balloon inside the phantom tissue is inserted to simulate tumor. Deflation of the balloon simulates tumor shrinkage. Nonradiopaque surface markers, which do not influence DIR algorithms, provide the deformation ground truth. Fixed and movable holders are built in the phantom to hold a diode for dosimetric measurements.
RESULTS: The measured deformations at the surface marker positions can be compared with deformations calculated by a DIR algorithm to evaluate its accuracy. In this study, the authors selected a Demons algorithm as a DIR algorithm example for demonstration purposes. The average error magnitude is 2.1 mm. The point dose measurements from the in vivo diode dosimeters show a good agreement with the calculated doses from the treatment planning system with a maximum difference of 3.1% of prescription dose, when the treatment plans are delivered to the phantom with original or deformed geometry.
CONCLUSIONS: In this study, the authors have presented the functionality of this deformable HN phantom for testing the accuracy of DIR algorithms and verifying the ART dosimetric accuracy. The authors' experiments demonstrate the feasibility of this phantom serving as an end-to-end ART QA phantom.

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Year:  2015        PMID: 25832039     DOI: 10.1118/1.4908205

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  4 in total

1.  MIRSIG position paper: the use of image registration and fusion algorithms in radiotherapy.

Authors:  Nicholas Lowther; Rob Louwe; Johnson Yuen; Nicholas Hardcastle; Adam Yeo; Michael Jameson
Journal:  Phys Eng Sci Med       Date:  2022-05-06

2.  Evaluation of a software module for adaptive treatment planning and re-irradiation.

Authors:  Anne Richter; Stefan Weick; Thomas Krieger; Florian Exner; Sonja Kellner; Bülent Polat; Michael Flentje
Journal:  Radiat Oncol       Date:  2017-12-28       Impact factor: 3.481

Review 3.  Adaptive Radiation Therapy (ART) Strategies and Technical Considerations: A State of the ART Review From NRG Oncology.

Authors:  Carri K Glide-Hurst; Percy Lee; Adam D Yock; Jeffrey R Olsen; Minsong Cao; Farzan Siddiqui; William Parker; Anthony Doemer; Yi Rong; Amar U Kishan; Stanley H Benedict; X Allen Li; Beth A Erickson; Jason W Sohn; Ying Xiao; Evan Wuthrick
Journal:  Int J Radiat Oncol Biol Phys       Date:  2020-10-24       Impact factor: 7.038

4.  Quantifying the accuracy of deformable image registration for cone-beam computed tomography with a physical phantom.

Authors:  Richard Y Wu; Amy Y Liu; Tyler D Williamson; Jinzhong Yang; Paul G Wisdom; Xiaorong R Zhu; Steven J Frank; Clifton D Fuller; Gary B Gunn; Song Gao
Journal:  J Appl Clin Med Phys       Date:  2019-09-21       Impact factor: 2.102

  4 in total

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