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Optimization of Tagged MRI for Quantification of Liver Stiffness Using Computer Simulated Data

The heartbeat has been proposed as an intrinsic source of motion that can be used in combination with tagged Magnetic Resonance Imaging (MRI) to measure displacements induced in the liver as an index of liver stiffness. Optimizing a tagged MRI acquisition protocol in terms of sensitivity to these di...

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Autores principales: Monti, Serena, Palma, Giuseppe, Ragucci, Monica, Mannelli, Lorenzo, Mancini, Marcello, Prinster, Anna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4216130/
https://www.ncbi.nlm.nih.gov/pubmed/25360557
http://dx.doi.org/10.1371/journal.pone.0111852
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author Monti, Serena
Palma, Giuseppe
Ragucci, Monica
Mannelli, Lorenzo
Mancini, Marcello
Prinster, Anna
author_facet Monti, Serena
Palma, Giuseppe
Ragucci, Monica
Mannelli, Lorenzo
Mancini, Marcello
Prinster, Anna
author_sort Monti, Serena
collection PubMed
description The heartbeat has been proposed as an intrinsic source of motion that can be used in combination with tagged Magnetic Resonance Imaging (MRI) to measure displacements induced in the liver as an index of liver stiffness. Optimizing a tagged MRI acquisition protocol in terms of sensitivity to these displacements, which are in the order of pixel size, is necessary to develop the method as a quantification tool for staging fibrosis. We reproduced a study of cardiac-induced strain in the liver at 3T and simulated tagged MR images with different grid tag patterns to evaluate the performance of the Harmonic Phase (HARP) image analysis method and its dependence on the parameters of tag spacing and grid angle. The Partial Volume Effect (PVE), T1 relaxation, and different levels of noise were taken into account. Four displacement fields of increasing intensity were created and applied to the tagged MR images of the liver. These fields simulated the deformation at different liver stiffnesses. An Error Index (EI) was calculated to evaluate the estimation accuracy for various parameter values. In the absence of noise, the estimation accuracy of the displacement fields increased as tag spacings decreased. EIs for each of the four displacement fields were lower at 0° and the local minima of the EI were found to correspond to multiples of pixel size. The accuracy of the estimation decreased for increasing levels of added noise; as the level increased, the improved estimation caused by decreasing the tag spacing tended to zero. The optimal tag spacing turned out to be a compromise between the smallest tag period that is a multiple of the pixel size and is achievable in a real acquisition and the tag spacing that guarantees an accurate liver displacement measure in the presence of realistic levels of noise.
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spelling pubmed-42161302014-11-05 Optimization of Tagged MRI for Quantification of Liver Stiffness Using Computer Simulated Data Monti, Serena Palma, Giuseppe Ragucci, Monica Mannelli, Lorenzo Mancini, Marcello Prinster, Anna PLoS One Research Article The heartbeat has been proposed as an intrinsic source of motion that can be used in combination with tagged Magnetic Resonance Imaging (MRI) to measure displacements induced in the liver as an index of liver stiffness. Optimizing a tagged MRI acquisition protocol in terms of sensitivity to these displacements, which are in the order of pixel size, is necessary to develop the method as a quantification tool for staging fibrosis. We reproduced a study of cardiac-induced strain in the liver at 3T and simulated tagged MR images with different grid tag patterns to evaluate the performance of the Harmonic Phase (HARP) image analysis method and its dependence on the parameters of tag spacing and grid angle. The Partial Volume Effect (PVE), T1 relaxation, and different levels of noise were taken into account. Four displacement fields of increasing intensity were created and applied to the tagged MR images of the liver. These fields simulated the deformation at different liver stiffnesses. An Error Index (EI) was calculated to evaluate the estimation accuracy for various parameter values. In the absence of noise, the estimation accuracy of the displacement fields increased as tag spacings decreased. EIs for each of the four displacement fields were lower at 0° and the local minima of the EI were found to correspond to multiples of pixel size. The accuracy of the estimation decreased for increasing levels of added noise; as the level increased, the improved estimation caused by decreasing the tag spacing tended to zero. The optimal tag spacing turned out to be a compromise between the smallest tag period that is a multiple of the pixel size and is achievable in a real acquisition and the tag spacing that guarantees an accurate liver displacement measure in the presence of realistic levels of noise. Public Library of Science 2014-10-31 /pmc/articles/PMC4216130/ /pubmed/25360557 http://dx.doi.org/10.1371/journal.pone.0111852 Text en © 2014 Monti et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Monti, Serena
Palma, Giuseppe
Ragucci, Monica
Mannelli, Lorenzo
Mancini, Marcello
Prinster, Anna
Optimization of Tagged MRI for Quantification of Liver Stiffness Using Computer Simulated Data
title Optimization of Tagged MRI for Quantification of Liver Stiffness Using Computer Simulated Data
title_full Optimization of Tagged MRI for Quantification of Liver Stiffness Using Computer Simulated Data
title_fullStr Optimization of Tagged MRI for Quantification of Liver Stiffness Using Computer Simulated Data
title_full_unstemmed Optimization of Tagged MRI for Quantification of Liver Stiffness Using Computer Simulated Data
title_short Optimization of Tagged MRI for Quantification of Liver Stiffness Using Computer Simulated Data
title_sort optimization of tagged mri for quantification of liver stiffness using computer simulated data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4216130/
https://www.ncbi.nlm.nih.gov/pubmed/25360557
http://dx.doi.org/10.1371/journal.pone.0111852
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