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

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...

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Autores principales: Shen, Jiuling, Dai, Zhitao, Yu, Jing, Yuan, Qingqing, Kang, Kailian, Chen, Cheng, Liu, Hui, Xie, Conghua, Wang, Xiaoyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9487306/
https://www.ncbi.nlm.nih.gov/pubmed/36147903
http://dx.doi.org/10.3389/fonc.2022.987971
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author Shen, Jiuling
Dai, Zhitao
Yu, Jing
Yuan, Qingqing
Kang, Kailian
Chen, Cheng
Liu, Hui
Xie, Conghua
Wang, Xiaoyong
author_facet Shen, Jiuling
Dai, Zhitao
Yu, Jing
Yuan, Qingqing
Kang, Kailian
Chen, Cheng
Liu, Hui
Xie, Conghua
Wang, Xiaoyong
author_sort Shen, Jiuling
collection PubMed
description 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 cm(2)) 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.
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spelling pubmed-94873062022-09-21 Sub-arc collimator angle optimization based on the conformity index heatmap for VMAT planning of multiple brain metastases SRS treatments Shen, Jiuling Dai, Zhitao Yu, Jing Yuan, Qingqing Kang, Kailian Chen, Cheng Liu, Hui Xie, Conghua Wang, Xiaoyong Front Oncol Oncology 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 cm(2)) 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. Frontiers Media S.A. 2022-09-06 /pmc/articles/PMC9487306/ /pubmed/36147903 http://dx.doi.org/10.3389/fonc.2022.987971 Text en Copyright © 2022 Shen, Dai, Yu, Yuan, Kang, Chen, Liu, Xie and Wang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Shen, Jiuling
Dai, Zhitao
Yu, Jing
Yuan, Qingqing
Kang, Kailian
Chen, Cheng
Liu, Hui
Xie, Conghua
Wang, Xiaoyong
Sub-arc collimator angle optimization based on the conformity index heatmap for VMAT planning of multiple brain metastases SRS treatments
title Sub-arc collimator angle optimization based on the conformity index heatmap for VMAT planning of multiple brain metastases SRS treatments
title_full Sub-arc collimator angle optimization based on the conformity index heatmap for VMAT planning of multiple brain metastases SRS treatments
title_fullStr Sub-arc collimator angle optimization based on the conformity index heatmap for VMAT planning of multiple brain metastases SRS treatments
title_full_unstemmed Sub-arc collimator angle optimization based on the conformity index heatmap for VMAT planning of multiple brain metastases SRS treatments
title_short Sub-arc collimator angle optimization based on the conformity index heatmap for VMAT planning of multiple brain metastases SRS treatments
title_sort sub-arc collimator angle optimization based on the conformity index heatmap for vmat planning of multiple brain metastases srs treatments
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9487306/
https://www.ncbi.nlm.nih.gov/pubmed/36147903
http://dx.doi.org/10.3389/fonc.2022.987971
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