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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...

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Autores principales: Athertya, Jiyo S., Ma, Yajun, Masoud Afsahi, Amir, Lombardi, Alecio F., Moazamian, Dina, Jerban, Saeed, Sedaghat, Sam, Jang, Hyungseok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
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.
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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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