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Multi‐parametric liver tissue characterization using MR fingerprinting: Simultaneous T1, T2, T2, and fat fraction mapping

Purpose Quantitative T1, T2, T2*, and fat fraction (FF) maps are promising imaging biomarkers for the assessment of liver disease, however these are usually acquired in sequential scans. Here we propose an extended MR fingerprinting (MRF) framework enabling simultaneous liver T1, T2, T2*, and FF map...

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Published in:Magnetic resonance in medicine 2020-11, Vol.84 (5), p.2625-2635
Main Authors: Jaubert, Olivier, Arrieta, Cristobal, Cruz, Gastão, Bustin, Aurélien, Schneider, Torben, Georgiopoulos, Georgios, Masci, Pier‐Giorgio, Sing‐Long, Carlos, Botnar, Rene M., Prieto, Claudia
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container_issue 5
container_start_page 2625
container_title Magnetic resonance in medicine
container_volume 84
creator Jaubert, Olivier
Arrieta, Cristobal
Cruz, Gastão
Bustin, Aurélien
Schneider, Torben
Georgiopoulos, Georgios
Masci, Pier‐Giorgio
Sing‐Long, Carlos
Botnar, Rene M.
Prieto, Claudia
description Purpose Quantitative T1, T2, T2*, and fat fraction (FF) maps are promising imaging biomarkers for the assessment of liver disease, however these are usually acquired in sequential scans. Here we propose an extended MR fingerprinting (MRF) framework enabling simultaneous liver T1, T2, T2*, and FF mapping from a single ~14 s breath‐hold scan. Methods A gradient echo (GRE) liver MRF sequence with nine readouts per TR, low flip angles (5‐15°), varying magnetisation preparation and golden angle radial trajectory is acquired at 1.5T to encode T1, T2, T2*, and FF simultaneously. The nine‐echo time‐series are reconstructed using a low‐rank tensor constrained reconstruction and used to fit T2*, B0 and to separate the water and fat signals. Water‐ and fat‐specific T1, T2, and M0 are obtained through dictionary matching, whereas FF estimation is extracted from the M0 maps. The framework was evaluated in a standardized T1/T2 phantom, a water‐fat phantom, and 12 subjects in comparison to reference methods. Preliminary clinical feasibility is shown in four patients. Results The proposed water T1, water T2, T2*, and FF maps in phantoms showed high coefficients of determination (r2 > 0.97) relative to reference methods. Measured liver MRF values in vivo (mean ± SD) for T1, T2, T2*, and FF were 671 ± 60 ms, 43.2 ± 6.8 ms, 29 ± 6.6 ms, and 3.2 ± 2.6% with biases of 92 ms, −7.1 ms, −1.4 ms, and 0.63% when compared to conventional methods. Conclusion A nine‐echo liver MRF sequence allows for quantitative multi‐parametric liver tissue characterization in a single breath‐hold scan of ~14 s. Future work will aim to validate the proposed approach in patients with liver disease.
doi_str_mv 10.1002/mrm.28311
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Here we propose an extended MR fingerprinting (MRF) framework enabling simultaneous liver T1, T2, T2*, and FF mapping from a single ~14 s breath‐hold scan. Methods A gradient echo (GRE) liver MRF sequence with nine readouts per TR, low flip angles (5‐15°), varying magnetisation preparation and golden angle radial trajectory is acquired at 1.5T to encode T1, T2, T2*, and FF simultaneously. The nine‐echo time‐series are reconstructed using a low‐rank tensor constrained reconstruction and used to fit T2*, B0 and to separate the water and fat signals. Water‐ and fat‐specific T1, T2, and M0 are obtained through dictionary matching, whereas FF estimation is extracted from the M0 maps. The framework was evaluated in a standardized T1/T2 phantom, a water‐fat phantom, and 12 subjects in comparison to reference methods. Preliminary clinical feasibility is shown in four patients. Results The proposed water T1, water T2, T2*, and FF maps in phantoms showed high coefficients of determination (r2 &gt; 0.97) relative to reference methods. Measured liver MRF values in vivo (mean ± SD) for T1, T2, T2*, and FF were 671 ± 60 ms, 43.2 ± 6.8 ms, 29 ± 6.6 ms, and 3.2 ± 2.6% with biases of 92 ms, −7.1 ms, −1.4 ms, and 0.63% when compared to conventional methods. Conclusion A nine‐echo liver MRF sequence allows for quantitative multi‐parametric liver tissue characterization in a single breath‐hold scan of ~14 s. 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Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-7397-9104 ; 0000-0003-4602-2523 ; 0000-0002-7854-4150 ; 0000-0002-2845-8617</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Jaubert, Olivier</creatorcontrib><creatorcontrib>Arrieta, Cristobal</creatorcontrib><creatorcontrib>Cruz, Gastão</creatorcontrib><creatorcontrib>Bustin, Aurélien</creatorcontrib><creatorcontrib>Schneider, Torben</creatorcontrib><creatorcontrib>Georgiopoulos, Georgios</creatorcontrib><creatorcontrib>Masci, Pier‐Giorgio</creatorcontrib><creatorcontrib>Sing‐Long, Carlos</creatorcontrib><creatorcontrib>Botnar, Rene M.</creatorcontrib><creatorcontrib>Prieto, Claudia</creatorcontrib><title>Multi‐parametric liver tissue characterization using MR fingerprinting: Simultaneous T1, T2, T2, and fat fraction mapping</title><title>Magnetic resonance in medicine</title><description>Purpose Quantitative T1, T2, T2*, and fat fraction (FF) maps are promising imaging biomarkers for the assessment of liver disease, however these are usually acquired in sequential scans. Here we propose an extended MR fingerprinting (MRF) framework enabling simultaneous liver T1, T2, T2*, and FF mapping from a single ~14 s breath‐hold scan. Methods A gradient echo (GRE) liver MRF sequence with nine readouts per TR, low flip angles (5‐15°), varying magnetisation preparation and golden angle radial trajectory is acquired at 1.5T to encode T1, T2, T2*, and FF simultaneously. The nine‐echo time‐series are reconstructed using a low‐rank tensor constrained reconstruction and used to fit T2*, B0 and to separate the water and fat signals. Water‐ and fat‐specific T1, T2, and M0 are obtained through dictionary matching, whereas FF estimation is extracted from the M0 maps. The framework was evaluated in a standardized T1/T2 phantom, a water‐fat phantom, and 12 subjects in comparison to reference methods. Preliminary clinical feasibility is shown in four patients. Results The proposed water T1, water T2, T2*, and FF maps in phantoms showed high coefficients of determination (r2 &gt; 0.97) relative to reference methods. Measured liver MRF values in vivo (mean ± SD) for T1, T2, T2*, and FF were 671 ± 60 ms, 43.2 ± 6.8 ms, 29 ± 6.6 ms, and 3.2 ± 2.6% with biases of 92 ms, −7.1 ms, −1.4 ms, and 0.63% when compared to conventional methods. Conclusion A nine‐echo liver MRF sequence allows for quantitative multi‐parametric liver tissue characterization in a single breath‐hold scan of ~14 s. 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Here we propose an extended MR fingerprinting (MRF) framework enabling simultaneous liver T1, T2, T2*, and FF mapping from a single ~14 s breath‐hold scan. Methods A gradient echo (GRE) liver MRF sequence with nine readouts per TR, low flip angles (5‐15°), varying magnetisation preparation and golden angle radial trajectory is acquired at 1.5T to encode T1, T2, T2*, and FF simultaneously. The nine‐echo time‐series are reconstructed using a low‐rank tensor constrained reconstruction and used to fit T2*, B0 and to separate the water and fat signals. Water‐ and fat‐specific T1, T2, and M0 are obtained through dictionary matching, whereas FF estimation is extracted from the M0 maps. The framework was evaluated in a standardized T1/T2 phantom, a water‐fat phantom, and 12 subjects in comparison to reference methods. Preliminary clinical feasibility is shown in four patients. Results The proposed water T1, water T2, T2*, and FF maps in phantoms showed high coefficients of determination (r2 &gt; 0.97) relative to reference methods. Measured liver MRF values in vivo (mean ± SD) for T1, T2, T2*, and FF were 671 ± 60 ms, 43.2 ± 6.8 ms, 29 ± 6.6 ms, and 3.2 ± 2.6% with biases of 92 ms, −7.1 ms, −1.4 ms, and 0.63% when compared to conventional methods. Conclusion A nine‐echo liver MRF sequence allows for quantitative multi‐parametric liver tissue characterization in a single breath‐hold scan of ~14 s. Future work will aim to validate the proposed approach in patients with liver disease.</abstract><cop>Hoboken</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/mrm.28311</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-7397-9104</orcidid><orcidid>https://orcid.org/0000-0003-4602-2523</orcidid><orcidid>https://orcid.org/0000-0002-7854-4150</orcidid><orcidid>https://orcid.org/0000-0002-2845-8617</orcidid><oa>free_for_read</oa></addata></record>
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source Wiley-Blackwell Read & Publish Collection
subjects Biomarkers
fat fraction
Fingerprinting
In vivo methods and tests
Liver
Liver diseases
liver MRI
Mapping
Measurement methods
MR fingerprinting
quantitative mapping
T1 mapping
T2 mapping
Tensors
title Multi‐parametric liver tissue characterization using MR fingerprinting: Simultaneous T1, T2, T2, and fat fraction mapping
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