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Treatment planning using MRI data: an analysis of the dose calculation accuracy for different treatment regions

BACKGROUND: Because of superior soft tissue contrast, the use of magnetic resonance imaging (MRI) as a complement to computed tomography (CT) in the target definition procedure for radiotherapy is increasing. To keep the workflow simple and cost effective and to reduce patient dose, it is natural to...

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Autores principales: Jonsson, Joakim H, Karlsson, Magnus G, Karlsson, Mikael, Nyholm, Tufve
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2909248/
https://www.ncbi.nlm.nih.gov/pubmed/20591179
http://dx.doi.org/10.1186/1748-717X-5-62
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author Jonsson, Joakim H
Karlsson, Magnus G
Karlsson, Mikael
Nyholm, Tufve
author_facet Jonsson, Joakim H
Karlsson, Magnus G
Karlsson, Mikael
Nyholm, Tufve
author_sort Jonsson, Joakim H
collection PubMed
description BACKGROUND: Because of superior soft tissue contrast, the use of magnetic resonance imaging (MRI) as a complement to computed tomography (CT) in the target definition procedure for radiotherapy is increasing. To keep the workflow simple and cost effective and to reduce patient dose, it is natural to strive for a treatment planning procedure based entirely on MRI. In the present study, we investigate the dose calculation accuracy for different treatment regions when using bulk density assignments on MRI data and compare it to treatment planning that uses CT data. METHODS: MR and CT data were collected retrospectively for 40 patients with prostate, lung, head and neck, or brain cancers. Comparisons were made between calculations on CT data with and without inhomogeneity corrections and on MRI or CT data with bulk density assignments. The bulk densities were assigned using manual segmentation of tissue, bone, lung, and air cavities. RESULTS: The deviations between calculations on CT data with inhomogeneity correction and on bulk density assigned MR data were small. The maximum difference in the number of monitor units required to reach the prescribed dose was 1.6%. This result also includes effects of possible geometrical distortions. CONCLUSIONS: The dose calculation accuracy at the investigated treatment sites is not significantly compromised when using MRI data when adequate bulk density assignments are made. With respect to treatment planning, MRI can replace CT in all steps of the treatment workflow, reducing the radiation exposure to the patient, removing any systematic registration errors that may occur when combining MR and CT, and decreasing time and cost for the extra CT investigation.
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spelling pubmed-29092482010-07-24 Treatment planning using MRI data: an analysis of the dose calculation accuracy for different treatment regions Jonsson, Joakim H Karlsson, Magnus G Karlsson, Mikael Nyholm, Tufve Radiat Oncol Research BACKGROUND: Because of superior soft tissue contrast, the use of magnetic resonance imaging (MRI) as a complement to computed tomography (CT) in the target definition procedure for radiotherapy is increasing. To keep the workflow simple and cost effective and to reduce patient dose, it is natural to strive for a treatment planning procedure based entirely on MRI. In the present study, we investigate the dose calculation accuracy for different treatment regions when using bulk density assignments on MRI data and compare it to treatment planning that uses CT data. METHODS: MR and CT data were collected retrospectively for 40 patients with prostate, lung, head and neck, or brain cancers. Comparisons were made between calculations on CT data with and without inhomogeneity corrections and on MRI or CT data with bulk density assignments. The bulk densities were assigned using manual segmentation of tissue, bone, lung, and air cavities. RESULTS: The deviations between calculations on CT data with inhomogeneity correction and on bulk density assigned MR data were small. The maximum difference in the number of monitor units required to reach the prescribed dose was 1.6%. This result also includes effects of possible geometrical distortions. CONCLUSIONS: The dose calculation accuracy at the investigated treatment sites is not significantly compromised when using MRI data when adequate bulk density assignments are made. With respect to treatment planning, MRI can replace CT in all steps of the treatment workflow, reducing the radiation exposure to the patient, removing any systematic registration errors that may occur when combining MR and CT, and decreasing time and cost for the extra CT investigation. BioMed Central 2010-06-30 /pmc/articles/PMC2909248/ /pubmed/20591179 http://dx.doi.org/10.1186/1748-717X-5-62 Text en Copyright ©2010 Jonsson et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Jonsson, Joakim H
Karlsson, Magnus G
Karlsson, Mikael
Nyholm, Tufve
Treatment planning using MRI data: an analysis of the dose calculation accuracy for different treatment regions
title Treatment planning using MRI data: an analysis of the dose calculation accuracy for different treatment regions
title_full Treatment planning using MRI data: an analysis of the dose calculation accuracy for different treatment regions
title_fullStr Treatment planning using MRI data: an analysis of the dose calculation accuracy for different treatment regions
title_full_unstemmed Treatment planning using MRI data: an analysis of the dose calculation accuracy for different treatment regions
title_short Treatment planning using MRI data: an analysis of the dose calculation accuracy for different treatment regions
title_sort treatment planning using mri data: an analysis of the dose calculation accuracy for different treatment regions
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2909248/
https://www.ncbi.nlm.nih.gov/pubmed/20591179
http://dx.doi.org/10.1186/1748-717X-5-62
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