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Title: Vector-model-supported optimization in volumetric-modulated arc stereotactic radiotherapy planning for brain metastasis

Abstract

Long planning time in volumetric-modulated arc stereotactic radiotherapy (VMA-SRT) cases can limit its clinical efficiency and use. A vector model could retrieve previously successful radiotherapy cases that share various common anatomic features with the current case. The prsent study aimed to develop a vector model that could reduce planning time by applying the optimization parameters from those retrieved reference cases. Thirty-six VMA-SRT cases of brain metastasis (gender, male [n = 23], female [n = 13]; age range, 32 to 81 years old) were collected and used as a reference database. Another 10 VMA-SRT cases were planned with both conventional optimization and vector-model-supported optimization, following the oncologists' clinical dose prescriptions. Planning time and plan quality measures were compared using the 2-sided paired Wilcoxon signed rank test with a significance level of 0.05, with positive false discovery rate (pFDR) of less than 0.05. With vector-model-supported optimization, there was a significant reduction in the median planning time, a 40% reduction from 3.7 to 2.2 hours (p = 0.002, pFDR = 0.032), and for the number of iterations, a 30% reduction from 8.5 to 6.0 (p = 0.006, pFDR = 0.047). The quality of plans from both approaches was comparable. From these preliminary results, vector-model-supported optimization can expedite the optimization of VMA-SRT for brain metastasis whilemore » maintaining plan quality.« less

Authors:
 [1];  [2];  [3];  [1]; ;  [1];  [4];  [3]
  1. Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia)
  2. (Hong Kong)
  3. Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong)
  4. (Australia)
Publication Date:
OSTI Identifier:
22685187
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Dosimetry; Journal Volume: 42; Journal Issue: 2; Other Information: Copyright (c) 2017 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
61 RADIATION PROTECTION AND DOSIMETRY; 62 RADIOLOGY AND NUCLEAR MEDICINE; BRAIN; MEDICAL PERSONNEL; METASTASES; OPTIMIZATION; PLANNING; RADIATION DOSES; RADIOTHERAPY; VECTORS

Citation Formats

Liu, Eva Sau Fan, Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Wu, Vincent Wing Cheung, Harris, Benjamin, Foote, Matthew, Lehman, Margot, School of Medicine, University of Queensland, and Chan, Lawrence Wing Chi, E-mail: wing.chi.chan@polyu.edu.hk. Vector-model-supported optimization in volumetric-modulated arc stereotactic radiotherapy planning for brain metastasis. United States: N. p., 2017. Web. doi:10.1016/J.MEDDOS.2017.01.002.
Liu, Eva Sau Fan, Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Wu, Vincent Wing Cheung, Harris, Benjamin, Foote, Matthew, Lehman, Margot, School of Medicine, University of Queensland, & Chan, Lawrence Wing Chi, E-mail: wing.chi.chan@polyu.edu.hk. Vector-model-supported optimization in volumetric-modulated arc stereotactic radiotherapy planning for brain metastasis. United States. doi:10.1016/J.MEDDOS.2017.01.002.
Liu, Eva Sau Fan, Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Wu, Vincent Wing Cheung, Harris, Benjamin, Foote, Matthew, Lehman, Margot, School of Medicine, University of Queensland, and Chan, Lawrence Wing Chi, E-mail: wing.chi.chan@polyu.edu.hk. Sat . "Vector-model-supported optimization in volumetric-modulated arc stereotactic radiotherapy planning for brain metastasis". United States. doi:10.1016/J.MEDDOS.2017.01.002.
@article{osti_22685187,
title = {Vector-model-supported optimization in volumetric-modulated arc stereotactic radiotherapy planning for brain metastasis},
author = {Liu, Eva Sau Fan and Department of Health Technology and Informatics, The Hong Kong Polytechnic University and Wu, Vincent Wing Cheung and Harris, Benjamin and Foote, Matthew and Lehman, Margot and School of Medicine, University of Queensland and Chan, Lawrence Wing Chi, E-mail: wing.chi.chan@polyu.edu.hk},
abstractNote = {Long planning time in volumetric-modulated arc stereotactic radiotherapy (VMA-SRT) cases can limit its clinical efficiency and use. A vector model could retrieve previously successful radiotherapy cases that share various common anatomic features with the current case. The prsent study aimed to develop a vector model that could reduce planning time by applying the optimization parameters from those retrieved reference cases. Thirty-six VMA-SRT cases of brain metastasis (gender, male [n = 23], female [n = 13]; age range, 32 to 81 years old) were collected and used as a reference database. Another 10 VMA-SRT cases were planned with both conventional optimization and vector-model-supported optimization, following the oncologists' clinical dose prescriptions. Planning time and plan quality measures were compared using the 2-sided paired Wilcoxon signed rank test with a significance level of 0.05, with positive false discovery rate (pFDR) of less than 0.05. With vector-model-supported optimization, there was a significant reduction in the median planning time, a 40% reduction from 3.7 to 2.2 hours (p = 0.002, pFDR = 0.032), and for the number of iterations, a 30% reduction from 8.5 to 6.0 (p = 0.006, pFDR = 0.047). The quality of plans from both approaches was comparable. From these preliminary results, vector-model-supported optimization can expedite the optimization of VMA-SRT for brain metastasis while maintaining plan quality.},
doi = {10.1016/J.MEDDOS.2017.01.002},
journal = {Medical Dosimetry},
number = 2,
volume = 42,
place = {United States},
year = {Sat Jul 01 00:00:00 EDT 2017},
month = {Sat Jul 01 00:00:00 EDT 2017}
}