A numerical framework for interstitial fluid pressure imaging in poroelastic MRE
A numerical framework for interstitial fluid pressure imaging (IFPI) in biphasic materials is investigated based on three-dimensional nonlinear finite element poroelastic inversion. The objective is to reconstruct the time-harmonic pore-pressure field from tissue excitation in addition to the elastic parameters commonly associated with magnetic resonance elastography (MRE). The unknown pressure boundary conditions (PBCs) are estimated using the available full-volume displacement data from MRE. A subzone-based nonlinear inversion (NLI) technique is then used to update mechanical and hydrodynamical properties, given the appropriate subzone PBCs, by solving a pressure forward problem (PFP). The algorithm was evaluated on a single-inclusion phantom in which the elastic property and hydraulic conductivity images were recovered. Pressure field and material property estimates had spatial distributions reflecting their true counterparts in the phantom geometry with RMS errors around 20% for cases with 5% noise, but degraded significantly in both spatial distribution and property values for noise levels > 10%. When both shear moduli and hydraulic conductivity were estimated along with the pressure field, property value error rates were as high as 58%, 85% and 32% for the three quantities, respectively, and their spatial distributions were more distorted. Opportunities for improving the algorithm are discussed.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2017 |
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| Erschienen: |
2017 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:12 |
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| Enthalten in: |
PloS one - 12(2017), 6 vom: 28., Seite e0178521 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Tan, Likun [VerfasserIn] |
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| Anmerkungen: |
Date Completed 14.09.2017 Date Revised 16.02.2024 published: Electronic-eCollection Citation Status MEDLINE |
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| doi: |
10.1371/journal.pone.0178521 |
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| Förderinstitution / Projekttitel: |
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NLM272665975 |
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| 245 | 1 | 2 | |a A numerical framework for interstitial fluid pressure imaging in poroelastic MRE |
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| 500 | |a Date Revised 16.02.2024 | ||
| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a A numerical framework for interstitial fluid pressure imaging (IFPI) in biphasic materials is investigated based on three-dimensional nonlinear finite element poroelastic inversion. The objective is to reconstruct the time-harmonic pore-pressure field from tissue excitation in addition to the elastic parameters commonly associated with magnetic resonance elastography (MRE). The unknown pressure boundary conditions (PBCs) are estimated using the available full-volume displacement data from MRE. A subzone-based nonlinear inversion (NLI) technique is then used to update mechanical and hydrodynamical properties, given the appropriate subzone PBCs, by solving a pressure forward problem (PFP). The algorithm was evaluated on a single-inclusion phantom in which the elastic property and hydraulic conductivity images were recovered. Pressure field and material property estimates had spatial distributions reflecting their true counterparts in the phantom geometry with RMS errors around 20% for cases with 5% noise, but degraded significantly in both spatial distribution and property values for noise levels > 10%. When both shear moduli and hydraulic conductivity were estimated along with the pressure field, property value error rates were as high as 58%, 85% and 32% for the three quantities, respectively, and their spatial distributions were more distorted. Opportunities for improving the algorithm are discussed | ||
| 650 | 4 | |a Journal Article | |
| 700 | 1 | |a McGarry, Matthew D J |e verfasserin |4 aut | |
| 700 | 1 | |a Van Houten, Elijah E W |e verfasserin |4 aut | |
| 700 | 1 | |a Ji, Ming |e verfasserin |4 aut | |
| 700 | 1 | |a Solamen, Ligin |e verfasserin |4 aut | |
| 700 | 1 | |a Zeng, Wei |e verfasserin |4 aut | |
| 700 | 1 | |a Weaver, John B |e verfasserin |4 aut | |
| 700 | 1 | |a Paulsen, Keith D |e verfasserin |4 aut | |
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