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

作者信息

Liu Eva Sau Fan, Wu Vincent Wing Cheung, Harris Benjamin, Foote Matthew, Lehman Margot, Chan Lawrence Wing Chi

机构信息

Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane, Australia; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong.

Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong.

出版信息

Med Dosim. 2017;42(2):85-89. doi: 10.1016/j.meddos.2017.01.002. Epub 2017 Mar 18.

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 while maintaining plan quality.

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