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

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

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)85-89
Number of pages5
JournalMedical Dosimetry
Issue number2
Publication statusPublished - 2 Feb 2017


  • Brain metastasis
  • Optimization
  • Stereotactic radiotherapy
  • Vector model
  • Volumetric modulated

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Oncology
  • Radiology Nuclear Medicine and imaging


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