Cargando…
Assessment of the Sun Nuclear ArcCHECK to detect errors in 6MV FFF VMAT delivery of brain SABR using ROC analysis
Institutions use a range of different detector systems for patient‐specific quality assurance (QA) measurements conducted to assure that the dose delivered by a patient’s radiotherapy treatment plan matches the calculated dose distribution. However, the ability of different detectors to detect error...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8200516/ https://www.ncbi.nlm.nih.gov/pubmed/34021691 http://dx.doi.org/10.1002/acm2.13276 |
_version_ | 1783707621579030528 |
---|---|
author | Tattenberg, Sebastian Hyde, Derek Milette, Marie‐Pierre Parodi, Katia Araujo, Cynthia Carlone, Marco |
author_facet | Tattenberg, Sebastian Hyde, Derek Milette, Marie‐Pierre Parodi, Katia Araujo, Cynthia Carlone, Marco |
author_sort | Tattenberg, Sebastian |
collection | PubMed |
description | Institutions use a range of different detector systems for patient‐specific quality assurance (QA) measurements conducted to assure that the dose delivered by a patient’s radiotherapy treatment plan matches the calculated dose distribution. However, the ability of different detectors to detect errors from different sources is often unreported. This study contains a systematic evaluation of Sun Nuclear’s ArcCHECK in terms of the detectability of potential machine‐related treatment errors. The five investigated sources of error were multileaf collimator (MLC) leaf positions, gantry angle, collimator angle, jaw positions, and dose output. The study encompassed the clinical treatment plans of 29 brain cancer patients who received stereotactic ablative radiotherapy (SABR). Six error magnitudes were investigated per source of error. In addition, the Eclipse AAA beam model dosimetric leaf gap (DLG) parameter was varied with four error magnitudes. Error detectability was determined based on the area under the receiver operating characteristic (ROC) curve (AUC). Detectability of DLG errors was good or excellent (AUC >0.8) at an error magnitude of at least ±0.4 mm, while MLC leaf position and gantry angle errors reached good or excellent detectability at error magnitudes of at least 1.0 mm and 0.6°, respectively. Ideal thresholds, that is, gamma passing rates, to maximize sensitivity and specificity ranged from 79.1% to 98.7%. The detectability of collimator angle, jaw position, and dose output errors was poor for all investigated error magnitudes, with an AUC between 0.5 and 0.6. The ArcCHECK device’s ability to detect errors from treatment machine‐related sources was evaluated, and ideal gamma passing rate thresholds were determined for each source of error. The ArcCHECK was able to detect errors in DLG value, MLC leaf positions, and gantry angle. The ArcCHECK was unable to detect the studied errors in collimator angle, jaw positions, and dose output. |
format | Online Article Text |
id | pubmed-8200516 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82005162021-06-15 Assessment of the Sun Nuclear ArcCHECK to detect errors in 6MV FFF VMAT delivery of brain SABR using ROC analysis Tattenberg, Sebastian Hyde, Derek Milette, Marie‐Pierre Parodi, Katia Araujo, Cynthia Carlone, Marco J Appl Clin Med Phys Radiation Oncology Physics Institutions use a range of different detector systems for patient‐specific quality assurance (QA) measurements conducted to assure that the dose delivered by a patient’s radiotherapy treatment plan matches the calculated dose distribution. However, the ability of different detectors to detect errors from different sources is often unreported. This study contains a systematic evaluation of Sun Nuclear’s ArcCHECK in terms of the detectability of potential machine‐related treatment errors. The five investigated sources of error were multileaf collimator (MLC) leaf positions, gantry angle, collimator angle, jaw positions, and dose output. The study encompassed the clinical treatment plans of 29 brain cancer patients who received stereotactic ablative radiotherapy (SABR). Six error magnitudes were investigated per source of error. In addition, the Eclipse AAA beam model dosimetric leaf gap (DLG) parameter was varied with four error magnitudes. Error detectability was determined based on the area under the receiver operating characteristic (ROC) curve (AUC). Detectability of DLG errors was good or excellent (AUC >0.8) at an error magnitude of at least ±0.4 mm, while MLC leaf position and gantry angle errors reached good or excellent detectability at error magnitudes of at least 1.0 mm and 0.6°, respectively. Ideal thresholds, that is, gamma passing rates, to maximize sensitivity and specificity ranged from 79.1% to 98.7%. The detectability of collimator angle, jaw position, and dose output errors was poor for all investigated error magnitudes, with an AUC between 0.5 and 0.6. The ArcCHECK device’s ability to detect errors from treatment machine‐related sources was evaluated, and ideal gamma passing rate thresholds were determined for each source of error. The ArcCHECK was able to detect errors in DLG value, MLC leaf positions, and gantry angle. The ArcCHECK was unable to detect the studied errors in collimator angle, jaw positions, and dose output. John Wiley and Sons Inc. 2021-05-21 /pmc/articles/PMC8200516/ /pubmed/34021691 http://dx.doi.org/10.1002/acm2.13276 Text en © 2021 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://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 Tattenberg, Sebastian Hyde, Derek Milette, Marie‐Pierre Parodi, Katia Araujo, Cynthia Carlone, Marco Assessment of the Sun Nuclear ArcCHECK to detect errors in 6MV FFF VMAT delivery of brain SABR using ROC analysis |
title | Assessment of the Sun Nuclear ArcCHECK to detect errors in 6MV FFF VMAT delivery of brain SABR using ROC analysis |
title_full | Assessment of the Sun Nuclear ArcCHECK to detect errors in 6MV FFF VMAT delivery of brain SABR using ROC analysis |
title_fullStr | Assessment of the Sun Nuclear ArcCHECK to detect errors in 6MV FFF VMAT delivery of brain SABR using ROC analysis |
title_full_unstemmed | Assessment of the Sun Nuclear ArcCHECK to detect errors in 6MV FFF VMAT delivery of brain SABR using ROC analysis |
title_short | Assessment of the Sun Nuclear ArcCHECK to detect errors in 6MV FFF VMAT delivery of brain SABR using ROC analysis |
title_sort | assessment of the sun nuclear arccheck to detect errors in 6mv fff vmat delivery of brain sabr using roc analysis |
topic | Radiation Oncology Physics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8200516/ https://www.ncbi.nlm.nih.gov/pubmed/34021691 http://dx.doi.org/10.1002/acm2.13276 |
work_keys_str_mv | AT tattenbergsebastian assessmentofthesunnucleararcchecktodetecterrorsin6mvfffvmatdeliveryofbrainsabrusingrocanalysis AT hydederek assessmentofthesunnucleararcchecktodetecterrorsin6mvfffvmatdeliveryofbrainsabrusingrocanalysis AT milettemariepierre assessmentofthesunnucleararcchecktodetecterrorsin6mvfffvmatdeliveryofbrainsabrusingrocanalysis AT parodikatia assessmentofthesunnucleararcchecktodetecterrorsin6mvfffvmatdeliveryofbrainsabrusingrocanalysis AT araujocynthia assessmentofthesunnucleararcchecktodetecterrorsin6mvfffvmatdeliveryofbrainsabrusingrocanalysis AT carlonemarco assessmentofthesunnucleararcchecktodetecterrorsin6mvfffvmatdeliveryofbrainsabrusingrocanalysis |