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Performance of gimbal-based dynamic tumor tracking for treating liver carcinoma

BACKGROUND: Since the introduction of tumor tracking in radiotherapy, it is possible to ensure a precise irradiation of moving targets. To follow the tumor movement, most systems rely on the detection of implanted markers and correlation models between the internal and external patient movement. Thi...

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Autores principales: Ziegler, Marc, Brandt, Tobias, Lettmaier, Sebastian, Fietkau, Rainer, Bert, Christoph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6280466/
https://www.ncbi.nlm.nih.gov/pubmed/30518398
http://dx.doi.org/10.1186/s13014-018-1180-1
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author Ziegler, Marc
Brandt, Tobias
Lettmaier, Sebastian
Fietkau, Rainer
Bert, Christoph
author_facet Ziegler, Marc
Brandt, Tobias
Lettmaier, Sebastian
Fietkau, Rainer
Bert, Christoph
author_sort Ziegler, Marc
collection PubMed
description BACKGROUND: Since the introduction of tumor tracking in radiotherapy, it is possible to ensure a precise irradiation of moving targets. To follow the tumor movement, most systems rely on the detection of implanted markers and correlation models between the internal and external patient movement. This study reports the clinical workflow and first results of the dynamic tumor tracking (DTT) performance for patients with liver carcinoma at the Vero SBRT system of the University Hospital Erlangen regarding the detection of the internal marker and the changes of the determined correlation models. METHODS: So far 13 liver patients were treated with DTT. For each patient, two fiducial markers (FM), which are monitored with X-rays during treatment, were implanted in the vicinity of the tumor. All patients received a fraction dose of 4–6 Gy with 8 to 12 fractions. Treatment and patient data is evaluated by processing the acquired log-files of the DTT treatment. Based on this, the marker detection and the changes of the correlation model between the internal and external movement is investigated. RESULTS: The median treatment time was 19:42 min. During treatment a median of 173 X-ray stereoscopic images were acquired. The marker detection was successful in 64.6% of the images. The FM detection is independent of the relative angle between the marker and the imager, but shows a dependency on the average intensity surrounding the FM position within the kV images. The number of correlation models needed during treatment increases in the presence of baseline shifts. The comparison of the correlation models shows large differences in the internal-external correlation between the different models acquired for one patient. CONCLUSION: Thirteen liver patients were treated with DTT at the Vero SBRT system and the marker detection was analyzed. Furthermore, the importance of regularly monitoring the internal target motion could be shown, since the correlation between the internal and external motion changes considerably over the course of the treatment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13014-018-1180-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-62804662018-12-10 Performance of gimbal-based dynamic tumor tracking for treating liver carcinoma Ziegler, Marc Brandt, Tobias Lettmaier, Sebastian Fietkau, Rainer Bert, Christoph Radiat Oncol Research BACKGROUND: Since the introduction of tumor tracking in radiotherapy, it is possible to ensure a precise irradiation of moving targets. To follow the tumor movement, most systems rely on the detection of implanted markers and correlation models between the internal and external patient movement. This study reports the clinical workflow and first results of the dynamic tumor tracking (DTT) performance for patients with liver carcinoma at the Vero SBRT system of the University Hospital Erlangen regarding the detection of the internal marker and the changes of the determined correlation models. METHODS: So far 13 liver patients were treated with DTT. For each patient, two fiducial markers (FM), which are monitored with X-rays during treatment, were implanted in the vicinity of the tumor. All patients received a fraction dose of 4–6 Gy with 8 to 12 fractions. Treatment and patient data is evaluated by processing the acquired log-files of the DTT treatment. Based on this, the marker detection and the changes of the correlation model between the internal and external movement is investigated. RESULTS: The median treatment time was 19:42 min. During treatment a median of 173 X-ray stereoscopic images were acquired. The marker detection was successful in 64.6% of the images. The FM detection is independent of the relative angle between the marker and the imager, but shows a dependency on the average intensity surrounding the FM position within the kV images. The number of correlation models needed during treatment increases in the presence of baseline shifts. The comparison of the correlation models shows large differences in the internal-external correlation between the different models acquired for one patient. CONCLUSION: Thirteen liver patients were treated with DTT at the Vero SBRT system and the marker detection was analyzed. Furthermore, the importance of regularly monitoring the internal target motion could be shown, since the correlation between the internal and external motion changes considerably over the course of the treatment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13014-018-1180-1) contains supplementary material, which is available to authorized users. BioMed Central 2018-12-05 /pmc/articles/PMC6280466/ /pubmed/30518398 http://dx.doi.org/10.1186/s13014-018-1180-1 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Ziegler, Marc
Brandt, Tobias
Lettmaier, Sebastian
Fietkau, Rainer
Bert, Christoph
Performance of gimbal-based dynamic tumor tracking for treating liver carcinoma
title Performance of gimbal-based dynamic tumor tracking for treating liver carcinoma
title_full Performance of gimbal-based dynamic tumor tracking for treating liver carcinoma
title_fullStr Performance of gimbal-based dynamic tumor tracking for treating liver carcinoma
title_full_unstemmed Performance of gimbal-based dynamic tumor tracking for treating liver carcinoma
title_short Performance of gimbal-based dynamic tumor tracking for treating liver carcinoma
title_sort performance of gimbal-based dynamic tumor tracking for treating liver carcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6280466/
https://www.ncbi.nlm.nih.gov/pubmed/30518398
http://dx.doi.org/10.1186/s13014-018-1180-1
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