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MR thermometry for focused ultrasound monitoring utilizing model predictive filtering and ultrasound beam modeling

BACKGROUND: A major challenge in using magnetic resonance temperature imaging (MRTI) to monitor focused ultrasound (FUS) applications is achieving high spatio-temporal resolution over a large field of view (FOV). This is important to accurately monitor all ultrasound (US) power depositions. Magnetic...

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Autores principales: Odéen, Henrik, Almquist, Scott, de Bever, Joshua, Christensen, Douglas A., Parker, Dennis L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5032243/
https://www.ncbi.nlm.nih.gov/pubmed/27688881
http://dx.doi.org/10.1186/s40349-016-0067-6
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author Odéen, Henrik
Almquist, Scott
de Bever, Joshua
Christensen, Douglas A.
Parker, Dennis L.
author_facet Odéen, Henrik
Almquist, Scott
de Bever, Joshua
Christensen, Douglas A.
Parker, Dennis L.
author_sort Odéen, Henrik
collection PubMed
description BACKGROUND: A major challenge in using magnetic resonance temperature imaging (MRTI) to monitor focused ultrasound (FUS) applications is achieving high spatio-temporal resolution over a large field of view (FOV). This is important to accurately monitor all ultrasound (US) power depositions. Magnetic resonance (MR) subsampling in conjunction with thermal model-based reconstruction of the MRTI utilizing Pennes bioheat transfer equation (PBTE) is one promising approach. The thermal properties used in the thermal model are often estimated from a pre-treatment, low-power sonication. METHODS: In this proof-of-concept study we investigate the use of US simulations computed using the hybrid angular spectrum (HAS) method to estimate the US power deposition density Q, thereby avoiding the pre-treatment sonication and any potential tissue damage. MRTI reconstructions are performed using a thermal model-based reconstruction method called model predictive filtering (MPF). Experiments are performed in a homogeneous gelatin phantom and in a gelatin phantom with embedded plastic skull. MPF reconstructions are compared to separate sonications imaged with fully sampled data over a smaller FOV. Temperature root-mean-square errors (RMSE) and focal spot positions and shapes are evaluated. RESULTS: HAS simulations accurately predict the location of the focal spot (to within 1 mm) in both phantoms. Accurate temperature maps (RMSE below 1 °C), where the location of the focal spot agrees well with fully sampled “truth” (to within 1 mm), are also achieved in both phantoms. CONCLUSIONS: HAS simulations can be used to accurately predict the focal spot location in homogeneous media and when focusing through an aberrating plastic skull. The HAS simulated power deposition (Q) patterns can be used in the MPF thermal model-based reconstruction to obtain accurate temperature maps with high spatio-temporal resolution over large FOVs.
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spelling pubmed-50322432016-09-29 MR thermometry for focused ultrasound monitoring utilizing model predictive filtering and ultrasound beam modeling Odéen, Henrik Almquist, Scott de Bever, Joshua Christensen, Douglas A. Parker, Dennis L. J Ther Ultrasound Research BACKGROUND: A major challenge in using magnetic resonance temperature imaging (MRTI) to monitor focused ultrasound (FUS) applications is achieving high spatio-temporal resolution over a large field of view (FOV). This is important to accurately monitor all ultrasound (US) power depositions. Magnetic resonance (MR) subsampling in conjunction with thermal model-based reconstruction of the MRTI utilizing Pennes bioheat transfer equation (PBTE) is one promising approach. The thermal properties used in the thermal model are often estimated from a pre-treatment, low-power sonication. METHODS: In this proof-of-concept study we investigate the use of US simulations computed using the hybrid angular spectrum (HAS) method to estimate the US power deposition density Q, thereby avoiding the pre-treatment sonication and any potential tissue damage. MRTI reconstructions are performed using a thermal model-based reconstruction method called model predictive filtering (MPF). Experiments are performed in a homogeneous gelatin phantom and in a gelatin phantom with embedded plastic skull. MPF reconstructions are compared to separate sonications imaged with fully sampled data over a smaller FOV. Temperature root-mean-square errors (RMSE) and focal spot positions and shapes are evaluated. RESULTS: HAS simulations accurately predict the location of the focal spot (to within 1 mm) in both phantoms. Accurate temperature maps (RMSE below 1 °C), where the location of the focal spot agrees well with fully sampled “truth” (to within 1 mm), are also achieved in both phantoms. CONCLUSIONS: HAS simulations can be used to accurately predict the focal spot location in homogeneous media and when focusing through an aberrating plastic skull. The HAS simulated power deposition (Q) patterns can be used in the MPF thermal model-based reconstruction to obtain accurate temperature maps with high spatio-temporal resolution over large FOVs. BioMed Central 2016-09-22 /pmc/articles/PMC5032243/ /pubmed/27688881 http://dx.doi.org/10.1186/s40349-016-0067-6 Text en © The Author(s). 2016 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
Odéen, Henrik
Almquist, Scott
de Bever, Joshua
Christensen, Douglas A.
Parker, Dennis L.
MR thermometry for focused ultrasound monitoring utilizing model predictive filtering and ultrasound beam modeling
title MR thermometry for focused ultrasound monitoring utilizing model predictive filtering and ultrasound beam modeling
title_full MR thermometry for focused ultrasound monitoring utilizing model predictive filtering and ultrasound beam modeling
title_fullStr MR thermometry for focused ultrasound monitoring utilizing model predictive filtering and ultrasound beam modeling
title_full_unstemmed MR thermometry for focused ultrasound monitoring utilizing model predictive filtering and ultrasound beam modeling
title_short MR thermometry for focused ultrasound monitoring utilizing model predictive filtering and ultrasound beam modeling
title_sort mr thermometry for focused ultrasound monitoring utilizing model predictive filtering and ultrasound beam modeling
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5032243/
https://www.ncbi.nlm.nih.gov/pubmed/27688881
http://dx.doi.org/10.1186/s40349-016-0067-6
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