Sub-arc collimator angle optimization based on the conformity index heatmap for VMAT planning of multiple brain metastases SRS treatments

Jiuling Shen; Zhitao Dai; Jing Yu; Qingqing Yuan; Kailian Kang; Cheng Chen; Hui Liu; Conghua Xie; Xiaoyong Wang

doi:10.3389/fonc.2022.987971

Sub-arc collimator angle optimization based on the conformity index heatmap for VMAT planning of multiple brain metastases SRS treatments

Front Oncol. 2022 Sep 6:12:987971. doi: 10.3389/fonc.2022.987971. eCollection 2022.

Authors

Jiuling Shen^{1

2}, Zhitao Dai³, Jing Yu^{1

2}, Qingqing Yuan³, Kailian Kang³, Cheng Chen^{1

2}, Hui Liu^{1

2}, Conghua Xie^{1

2}, Xiaoyong Wang^{1

2}

Affiliations

¹ Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China.
² Hubei Radiotherapy Quality Control Center, Wuhan University, Wuhan, China.
³ National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.

Abstract

Objective: The 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).

Methods: Twenty 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°. 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.

Results: The 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 cm²) and MUs (655.35 ± 71.99 vs. 729.85 ± 73.52) by 41.11%.

Conclusions: The 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.

Keywords: collimator angle optimization; multiple brain metastases; stereotactic radiosurgery; sub-arc; volumetric modulated arc therapy.