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Implementation and validation of an in‐house geometry optimization software for SRS VMAT planning of multiple cranial metastases

PURPOSE: The implementation and evaluation of an in‐house developed geometry optimization (GO) software are described. The GO script provides optimal lesion clustering, isocenter placement, and collimator angle of each arc for cranial multi‐lesion stereotactic radiosurgery (SRS) volumetric modulated...

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Autores principales: Kuo, LiCheng, Zhang, PengPeng, Pham, Hai, Ballangrud, Åse M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497919/
https://www.ncbi.nlm.nih.gov/pubmed/32627925
http://dx.doi.org/10.1002/acm2.12961
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author Kuo, LiCheng
Zhang, PengPeng
Pham, Hai
Ballangrud, Åse M.
author_facet Kuo, LiCheng
Zhang, PengPeng
Pham, Hai
Ballangrud, Åse M.
author_sort Kuo, LiCheng
collection PubMed
description PURPOSE: The implementation and evaluation of an in‐house developed geometry optimization (GO) software are described. The GO script provides optimal lesion clustering, isocenter placement, and collimator angle of each arc for cranial multi‐lesion stereotactic radiosurgery (SRS) volumetric modulated arc therapy (VMAT) planning. MATERIALS AND METHODS: An Eclipse‐plugin program was developed to facilitate automatic plan geometry generation for multiple metastases SRS VMAT plans. A mixed, semi‐supervised exhaustive and k‐means clustering method is used to group lesions and place isocenters. The sum of squared euclidean distance (SSED) and the boundaries of lesions’ projection from beams’ eye view are used as supervised parameters to determine the optimal isocenter numbers. The collimator angle is optimized by minimizing the sum of the MLC opening area from all gantry angles for each arc. In all, 10 clinical cases treated during 2016–2017 were compared to plan quality of GO script generated plans. Paddick gradient index (GI), conformity index (CI), and local brain volume receiving 12 Gy (local V12 Gy) around each lesion were compared. RESULT: For four cases, the number of isocenters was reduced in the GO plans. For four other cases, the GO plans had the same number of isocenters as their corresponding clinical plans but with different lesion grouping. The GO plans had significantly lower GI (4.1 ± 1.0 vs 4.4 ± 0.9, P < 0.0001) and local V12 Gy (5.1 ± 4.2 vs 5.5 ± 4.3 in cm(3), P < 0.0001), but not significantly different mean normal brain dose or CI. The volume of normal brain receiving ≥6 Gy was significantly lower in the GO plans. The total time to run the GO script for each case was <2 min. CONCLUSION: The GO software automates lesion grouping, isocenter placement, and the collimator angles for SRS VMAT planning. When tested on 10 cases, the GO script resulted in improved plan quality and shorter planning time when compared to the clinical SRS VMAT plans.
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spelling pubmed-74979192020-09-25 Implementation and validation of an in‐house geometry optimization software for SRS VMAT planning of multiple cranial metastases Kuo, LiCheng Zhang, PengPeng Pham, Hai Ballangrud, Åse M. J Appl Clin Med Phys Radiation Oncology Physics PURPOSE: The implementation and evaluation of an in‐house developed geometry optimization (GO) software are described. The GO script provides optimal lesion clustering, isocenter placement, and collimator angle of each arc for cranial multi‐lesion stereotactic radiosurgery (SRS) volumetric modulated arc therapy (VMAT) planning. MATERIALS AND METHODS: An Eclipse‐plugin program was developed to facilitate automatic plan geometry generation for multiple metastases SRS VMAT plans. A mixed, semi‐supervised exhaustive and k‐means clustering method is used to group lesions and place isocenters. The sum of squared euclidean distance (SSED) and the boundaries of lesions’ projection from beams’ eye view are used as supervised parameters to determine the optimal isocenter numbers. The collimator angle is optimized by minimizing the sum of the MLC opening area from all gantry angles for each arc. In all, 10 clinical cases treated during 2016–2017 were compared to plan quality of GO script generated plans. Paddick gradient index (GI), conformity index (CI), and local brain volume receiving 12 Gy (local V12 Gy) around each lesion were compared. RESULT: For four cases, the number of isocenters was reduced in the GO plans. For four other cases, the GO plans had the same number of isocenters as their corresponding clinical plans but with different lesion grouping. The GO plans had significantly lower GI (4.1 ± 1.0 vs 4.4 ± 0.9, P < 0.0001) and local V12 Gy (5.1 ± 4.2 vs 5.5 ± 4.3 in cm(3), P < 0.0001), but not significantly different mean normal brain dose or CI. The volume of normal brain receiving ≥6 Gy was significantly lower in the GO plans. The total time to run the GO script for each case was <2 min. CONCLUSION: The GO software automates lesion grouping, isocenter placement, and the collimator angles for SRS VMAT planning. When tested on 10 cases, the GO script resulted in improved plan quality and shorter planning time when compared to the clinical SRS VMAT plans. John Wiley and Sons Inc. 2020-07-06 /pmc/articles/PMC7497919/ /pubmed/32627925 http://dx.doi.org/10.1002/acm2.12961 Text en © 2020 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Radiation Oncology Physics
Kuo, LiCheng
Zhang, PengPeng
Pham, Hai
Ballangrud, Åse M.
Implementation and validation of an in‐house geometry optimization software for SRS VMAT planning of multiple cranial metastases
title Implementation and validation of an in‐house geometry optimization software for SRS VMAT planning of multiple cranial metastases
title_full Implementation and validation of an in‐house geometry optimization software for SRS VMAT planning of multiple cranial metastases
title_fullStr Implementation and validation of an in‐house geometry optimization software for SRS VMAT planning of multiple cranial metastases
title_full_unstemmed Implementation and validation of an in‐house geometry optimization software for SRS VMAT planning of multiple cranial metastases
title_short Implementation and validation of an in‐house geometry optimization software for SRS VMAT planning of multiple cranial metastases
title_sort implementation and validation of an in‐house geometry optimization software for srs vmat planning of multiple cranial metastases
topic Radiation Oncology Physics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497919/
https://www.ncbi.nlm.nih.gov/pubmed/32627925
http://dx.doi.org/10.1002/acm2.12961
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