A tool to automatically analyze electromagnetic tracking data from high dose rate brachytherapy of breast cancer patients.
During High Dose Rate Brachytherapy (HDR-BT) the spatial position of the radiation source inside catheters implanted into a female breast is determined via electromagnetic tracking (EMT). Dwell positions and dwell times of the radiation source are established, relative to the patient's anatomy,...
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doaj-c6c0b58045b0431e9f2ebd3f9fa5bf242020-11-24T22:06:37ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01129e018360810.1371/journal.pone.0183608A tool to automatically analyze electromagnetic tracking data from high dose rate brachytherapy of breast cancer patients.Th I GötzG LahmerV StrnadCh BertB HenselA M ToméE W LangDuring High Dose Rate Brachytherapy (HDR-BT) the spatial position of the radiation source inside catheters implanted into a female breast is determined via electromagnetic tracking (EMT). Dwell positions and dwell times of the radiation source are established, relative to the patient's anatomy, from an initial X-ray-CT-image. During the irradiation treatment, catheter displacements can occur due to patient movements. The current study develops an automatic analysis tool of EMT data sets recorded with a solenoid sensor to assure concordance of the source movement with the treatment plan. The tool combines machine learning techniques such as multi-dimensional scaling (MDS), ensemble empirical mode decomposition (EEMD), singular spectrum analysis (SSA) and particle filter (PF) to precisely detect and quantify any mismatch between the treatment plan and actual EMT measurements. We demonstrate that movement artifacts as well as technical signal distortions can be removed automatically and reliably, resulting in artifact-free reconstructed signals. This is a prerequisite for a highly accurate determination of any deviations of dwell positions from the treatment plan.http://europepmc.org/articles/PMC5608198?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Th I Götz G Lahmer V Strnad Ch Bert B Hensel A M Tomé E W Lang |
spellingShingle |
Th I Götz G Lahmer V Strnad Ch Bert B Hensel A M Tomé E W Lang A tool to automatically analyze electromagnetic tracking data from high dose rate brachytherapy of breast cancer patients. PLoS ONE |
author_facet |
Th I Götz G Lahmer V Strnad Ch Bert B Hensel A M Tomé E W Lang |
author_sort |
Th I Götz |
title |
A tool to automatically analyze electromagnetic tracking data from high dose rate brachytherapy of breast cancer patients. |
title_short |
A tool to automatically analyze electromagnetic tracking data from high dose rate brachytherapy of breast cancer patients. |
title_full |
A tool to automatically analyze electromagnetic tracking data from high dose rate brachytherapy of breast cancer patients. |
title_fullStr |
A tool to automatically analyze electromagnetic tracking data from high dose rate brachytherapy of breast cancer patients. |
title_full_unstemmed |
A tool to automatically analyze electromagnetic tracking data from high dose rate brachytherapy of breast cancer patients. |
title_sort |
tool to automatically analyze electromagnetic tracking data from high dose rate brachytherapy of breast cancer patients. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2017-01-01 |
description |
During High Dose Rate Brachytherapy (HDR-BT) the spatial position of the radiation source inside catheters implanted into a female breast is determined via electromagnetic tracking (EMT). Dwell positions and dwell times of the radiation source are established, relative to the patient's anatomy, from an initial X-ray-CT-image. During the irradiation treatment, catheter displacements can occur due to patient movements. The current study develops an automatic analysis tool of EMT data sets recorded with a solenoid sensor to assure concordance of the source movement with the treatment plan. The tool combines machine learning techniques such as multi-dimensional scaling (MDS), ensemble empirical mode decomposition (EEMD), singular spectrum analysis (SSA) and particle filter (PF) to precisely detect and quantify any mismatch between the treatment plan and actual EMT measurements. We demonstrate that movement artifacts as well as technical signal distortions can be removed automatically and reliably, resulting in artifact-free reconstructed signals. This is a prerequisite for a highly accurate determination of any deviations of dwell positions from the treatment plan. |
url |
http://europepmc.org/articles/PMC5608198?pdf=render |
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