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Accelerated Quantitative 3D UTE-Cones Imaging Using Compressed Sensing
In this study, the feasibility of accelerated quantitative Ultrashort Echo Time Cones (qUTE-Cones) imaging with compressed sensing (CS) reconstruction is investigated. qUTE-Cones sequences for variable flip angle-based UTE T(1) mapping, UTE adiabatic T(1ρ) mapping, and UTE quantitative magnetization...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9573555/ https://www.ncbi.nlm.nih.gov/pubmed/36236557 http://dx.doi.org/10.3390/s22197459 |
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author | Athertya, Jiyo S. Ma, Yajun Masoud Afsahi, Amir Lombardi, Alecio F. Moazamian, Dina Jerban, Saeed Sedaghat, Sam Jang, Hyungseok |
author_facet | Athertya, Jiyo S. Ma, Yajun Masoud Afsahi, Amir Lombardi, Alecio F. Moazamian, Dina Jerban, Saeed Sedaghat, Sam Jang, Hyungseok |
author_sort | Athertya, Jiyo S. |
collection | PubMed |
description | In this study, the feasibility of accelerated quantitative Ultrashort Echo Time Cones (qUTE-Cones) imaging with compressed sensing (CS) reconstruction is investigated. qUTE-Cones sequences for variable flip angle-based UTE T(1) mapping, UTE adiabatic T(1ρ) mapping, and UTE quantitative magnetization transfer modeling of macromolecular fraction (MMF) were implemented on a clinical 3T MR system. Twenty healthy volunteers were recruited and underwent whole-knee MRI using qUTE-Cones sequences. The k-space data were retrospectively undersampled with different undersampling rates. The undersampled qUTE-Cones data were reconstructed using both zero-filling and CS reconstruction. Using CS-reconstructed UTE images, various parameters were estimated in 10 different regions of interests (ROIs) in tendons, ligaments, menisci, and cartilage. Structural similarity, percentage error, and Pearson’s correlation were calculated to assess the performance. Dramatically reduced streaking artifacts and improved SSIM were observed in UTE images from CS reconstruction. A mean SSIM of ~0.90 was achieved for all CS-reconstructed images. Percentage errors between fully sampled and undersampled CS-reconstructed images were below 5% for up to 50% undersampling (i.e., 2× acceleration). High linear correlation was observed (>0.95) for all qUTE parameters estimated in all subjects. CS-based reconstruction combined with efficient Cones trajectory is expected to achieve a clinically feasible scan time for qUTE imaging. |
format | Online Article Text |
id | pubmed-9573555 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95735552022-10-17 Accelerated Quantitative 3D UTE-Cones Imaging Using Compressed Sensing Athertya, Jiyo S. Ma, Yajun Masoud Afsahi, Amir Lombardi, Alecio F. Moazamian, Dina Jerban, Saeed Sedaghat, Sam Jang, Hyungseok Sensors (Basel) Article In this study, the feasibility of accelerated quantitative Ultrashort Echo Time Cones (qUTE-Cones) imaging with compressed sensing (CS) reconstruction is investigated. qUTE-Cones sequences for variable flip angle-based UTE T(1) mapping, UTE adiabatic T(1ρ) mapping, and UTE quantitative magnetization transfer modeling of macromolecular fraction (MMF) were implemented on a clinical 3T MR system. Twenty healthy volunteers were recruited and underwent whole-knee MRI using qUTE-Cones sequences. The k-space data were retrospectively undersampled with different undersampling rates. The undersampled qUTE-Cones data were reconstructed using both zero-filling and CS reconstruction. Using CS-reconstructed UTE images, various parameters were estimated in 10 different regions of interests (ROIs) in tendons, ligaments, menisci, and cartilage. Structural similarity, percentage error, and Pearson’s correlation were calculated to assess the performance. Dramatically reduced streaking artifacts and improved SSIM were observed in UTE images from CS reconstruction. A mean SSIM of ~0.90 was achieved for all CS-reconstructed images. Percentage errors between fully sampled and undersampled CS-reconstructed images were below 5% for up to 50% undersampling (i.e., 2× acceleration). High linear correlation was observed (>0.95) for all qUTE parameters estimated in all subjects. CS-based reconstruction combined with efficient Cones trajectory is expected to achieve a clinically feasible scan time for qUTE imaging. MDPI 2022-10-01 /pmc/articles/PMC9573555/ /pubmed/36236557 http://dx.doi.org/10.3390/s22197459 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Athertya, Jiyo S. Ma, Yajun Masoud Afsahi, Amir Lombardi, Alecio F. Moazamian, Dina Jerban, Saeed Sedaghat, Sam Jang, Hyungseok Accelerated Quantitative 3D UTE-Cones Imaging Using Compressed Sensing |
title | Accelerated Quantitative 3D UTE-Cones Imaging Using Compressed Sensing |
title_full | Accelerated Quantitative 3D UTE-Cones Imaging Using Compressed Sensing |
title_fullStr | Accelerated Quantitative 3D UTE-Cones Imaging Using Compressed Sensing |
title_full_unstemmed | Accelerated Quantitative 3D UTE-Cones Imaging Using Compressed Sensing |
title_short | Accelerated Quantitative 3D UTE-Cones Imaging Using Compressed Sensing |
title_sort | accelerated quantitative 3d ute-cones imaging using compressed sensing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9573555/ https://www.ncbi.nlm.nih.gov/pubmed/36236557 http://dx.doi.org/10.3390/s22197459 |
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