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Automated review of patient position in DIBH breast hybrid IMRT with EPID images
Deep Inspiration Breath Hold (DIBH) is a respiratory‐gating technique adopted in radiation therapy to lower cardiac irradiation. When performing DIBH treatments, it is important to have a monitoring system to ensure the patient's breath hold level is stable and reproducible at each fraction. In...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476989/ https://www.ncbi.nlm.nih.gov/pubmed/37449391 http://dx.doi.org/10.1002/acm2.14038 |
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author | Redekopp, Jonathan Rivest, Ryan Sasaki, David Pistorius, Stephen Alpuche Aviles, Jorge E. |
author_facet | Redekopp, Jonathan Rivest, Ryan Sasaki, David Pistorius, Stephen Alpuche Aviles, Jorge E. |
author_sort | Redekopp, Jonathan |
collection | PubMed |
description | Deep Inspiration Breath Hold (DIBH) is a respiratory‐gating technique adopted in radiation therapy to lower cardiac irradiation. When performing DIBH treatments, it is important to have a monitoring system to ensure the patient's breath hold level is stable and reproducible at each fraction. In this retrospective study, we developed a system capable of monitoring DIBH breast treatments by utilizing cine EPID images taken during treatment. Setup error and intrafraction motion were measured for all fractions of 20 left‐sided breast patients. All patients were treated with a hybrid static‐IMRT technique, with EPID images from the static fields analyzed. Ten patients had open static fields and the other ten patients had static fields partially blocked with the multileaf collimator (MLC). Three image‐processing algorithms were evaluated on their ability to accurately measure the chest wall position (CWP) in EPID images. CWP measurements were recorded along a 61‐pixel region of interest centered along the midline of the image. The median and standard deviation of the CWP were recorded for each image. The algorithm showing the highest agreement with manual measurements was then used to calculate intrafraction motion and setup error. To measure intrafraction motion, the median CWP of the first EPID frame was compared with that of the subsequent EPID images of the treatment. The maximum difference was recorded as the intrafraction motion. The setup error was calculated as the difference in median CWP between the MV DRR and the first EPID image of the lateral tangential field. The results showed that the most accurate image‐processing algorithm can identify the chest wall within 1.2 mm on both EPID and MV DRR images, and measures intrafraction motion and setup errors within 1.4 mm. |
format | Online Article Text |
id | pubmed-10476989 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104769892023-09-05 Automated review of patient position in DIBH breast hybrid IMRT with EPID images Redekopp, Jonathan Rivest, Ryan Sasaki, David Pistorius, Stephen Alpuche Aviles, Jorge E. J Appl Clin Med Phys Radiation Oncology Physics Deep Inspiration Breath Hold (DIBH) is a respiratory‐gating technique adopted in radiation therapy to lower cardiac irradiation. When performing DIBH treatments, it is important to have a monitoring system to ensure the patient's breath hold level is stable and reproducible at each fraction. In this retrospective study, we developed a system capable of monitoring DIBH breast treatments by utilizing cine EPID images taken during treatment. Setup error and intrafraction motion were measured for all fractions of 20 left‐sided breast patients. All patients were treated with a hybrid static‐IMRT technique, with EPID images from the static fields analyzed. Ten patients had open static fields and the other ten patients had static fields partially blocked with the multileaf collimator (MLC). Three image‐processing algorithms were evaluated on their ability to accurately measure the chest wall position (CWP) in EPID images. CWP measurements were recorded along a 61‐pixel region of interest centered along the midline of the image. The median and standard deviation of the CWP were recorded for each image. The algorithm showing the highest agreement with manual measurements was then used to calculate intrafraction motion and setup error. To measure intrafraction motion, the median CWP of the first EPID frame was compared with that of the subsequent EPID images of the treatment. The maximum difference was recorded as the intrafraction motion. The setup error was calculated as the difference in median CWP between the MV DRR and the first EPID image of the lateral tangential field. The results showed that the most accurate image‐processing algorithm can identify the chest wall within 1.2 mm on both EPID and MV DRR images, and measures intrafraction motion and setup errors within 1.4 mm. John Wiley and Sons Inc. 2023-07-14 /pmc/articles/PMC10476989/ /pubmed/37449391 http://dx.doi.org/10.1002/acm2.14038 Text en © 2023 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The 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 Redekopp, Jonathan Rivest, Ryan Sasaki, David Pistorius, Stephen Alpuche Aviles, Jorge E. Automated review of patient position in DIBH breast hybrid IMRT with EPID images |
title | Automated review of patient position in DIBH breast hybrid IMRT with EPID images |
title_full | Automated review of patient position in DIBH breast hybrid IMRT with EPID images |
title_fullStr | Automated review of patient position in DIBH breast hybrid IMRT with EPID images |
title_full_unstemmed | Automated review of patient position in DIBH breast hybrid IMRT with EPID images |
title_short | Automated review of patient position in DIBH breast hybrid IMRT with EPID images |
title_sort | automated review of patient position in dibh breast hybrid imrt with epid images |
topic | Radiation Oncology Physics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476989/ https://www.ncbi.nlm.nih.gov/pubmed/37449391 http://dx.doi.org/10.1002/acm2.14038 |
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