Journal
FRONTIERS IN ONCOLOGY
Volume 12, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2022.987971
Keywords
collimator angle optimization; volumetric modulated arc therapy; stereotactic radiosurgery; multiple brain metastases; sub-arc
Categories
Funding
- Sanming Project of Medicine in Shenzhen
- Shenzhen Key Medical Discipline Construction Fund
- Basic and Applied Basic Research Foundation of Guangdong Province
- Shenzhen Postdoctoral Research Funds
- [SZSM201612063]
- [SZXK013]
- [2020A1515110335]
- [25005]
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The aim of this study was to investigate the impact of collimator angle optimization in single-isocenter coplanar volumetric modulated arc therapy (VMAT) stereotactic radiosurgery (SRS) for multiple metastases. The results showed that the novel algorithm of sub-arc collimator angle optimization (SACAO) could improve the dosimetric quality and treatment delivery efficiency, leading to better conformity index (CI), homogeneity index (HI), and gradient index (GI) for the targets, as well as improved sparing of organs at risk (OARs). Furthermore, the SACAO method also increased treatment efficiency in terms of field size and monitoring units (MUs).
ObjectiveThe aim of this study was to investigate the impact of collimator angle optimization in single-isocenter coplanar volume modulated arc therapy (VMAT) stereotactic radiosurgery (SRS) for multiple metastases with respect to dosimetric quality and treatment delivery efficiency. In particular, this is achieved by a novel algorithm of sub-arc collimator angle optimization (SACAO). MethodsTwenty patients with multiple brain metastases were retrospectively included in this study. A multi-leaf collimator (MLC) conformity index (MCI) that is defined as the ratio of the area of target projection in the beam's eye view (BEV) to the related area fitted by MLC was applied. Accordingly, for each control point, 180 MCI values were calculated with a collimator angle interval of 1 degrees. A two-dimensional heatmap of MCI as a function of control point and collimator angle for each full arc was generated. The optimal segmentation of sub-arcs was achieved by avoiding the worst MCI at each control point. Then, the optimal collimator angle for each sub-arc would be determined by maximizing the summation of MCI. Each patient was scheduled to undergo single-center coplanar VMAT SRS based on either the novel SACAO algorithm or the conventional VMAT with static collimator angle (ST-VMAT). The dosimetric parameters, field sizes, and the monitoring units (Mus) were evaluated. ResultsThe mean dose-volumetric parameters for the target volume of SACAO were comparable to ST-VMAT, while the conformity index (CI), homogeneity index (HI), and gradient index (GI) were reduced by SACAO. Improved sparing of organs at risk (OARs) was also obtained by SACAO. In particular, the SACAO method significantly (p < 0.01) reduced the field size (76.59 +/- 32.55 vs. 131.95 +/- 56.71 cm(2)) and MUs (655.35 +/- 71.99 vs. 729.85 +/- 73.52) by 41.11%. ConclusionsThe SACAO method could be superior in improving the CI, HI, and GI of the targets as well as normal tissue sparing for multiple brain metastases SRS. In particular, SACAO has the potential of increasing treatment efficiency in terms of field size and MU.
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