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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 |
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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 |
format | article |
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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.</description><identifier>ISSN: 0740-3194</identifier><identifier>EISSN: 1522-2594</identifier><identifier>DOI: 10.1002/mrm.28311</identifier><language>eng</language><publisher>Hoboken: Wiley Subscription Services, Inc</publisher><subject>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</subject><ispartof>Magnetic resonance in medicine, 2020-11, Vol.84 (5), p.2625-2635</ispartof><rights>2020 The Authors. published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine</rights><rights>2020. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). 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 > 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.</description><subject>Biomarkers</subject><subject>fat fraction</subject><subject>Fingerprinting</subject><subject>In vivo methods and tests</subject><subject>Liver</subject><subject>Liver diseases</subject><subject>liver MRI</subject><subject>Mapping</subject><subject>Measurement methods</subject><subject>MR fingerprinting</subject><subject>quantitative mapping</subject><subject>T1 mapping</subject><subject>T2 mapping</subject><subject>Tensors</subject><issn>0740-3194</issn><issn>1522-2594</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><recordid>eNpdkctOwzAQRS0EEqWw4A8ssWFBWr8SJ-xQxUtqhFTK2nJjB1zlhe2AChs-gW_kS3AbVixGd-Q5czXyBeAUowlGiExrW09ISjHeAyMcExKROGP7YIQ4QxHFGTsER86tEUJZxtkIfOZ95c3P13cnray1t6aAlXnTFnrjXK9h8RIGhdfWfEhv2gb2zjTPMF_AMqi2nTWND90lfDR18JKNbnsHl_gCLslQslGwlB6WW6OtRS27Lqwcg4NSVk6f_OkYPN1cL2d30fzh9n52NY_WhHIcqSIhqzjJVjpWSklGFUsRJUqmNAgnCUYl4zwpJNLhdZUwxeIS4xjzMKWYjsH54NvZ9rXXzovauEJX1XCrIAwFp4SkSUDP_qHrtrdNuC5QJKOMkwwFajpQ76bSGxG-oJZ2IzAS2wxEyEDsMhD5It819Bd5W3wB</recordid><startdate>202011</startdate><enddate>202011</enddate><creator>Jaubert, Olivier</creator><creator>Arrieta, Cristobal</creator><creator>Cruz, Gastão</creator><creator>Bustin, Aurélien</creator><creator>Schneider, Torben</creator><creator>Georgiopoulos, Georgios</creator><creator>Masci, Pier‐Giorgio</creator><creator>Sing‐Long, Carlos</creator><creator>Botnar, Rene M.</creator><creator>Prieto, Claudia</creator><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>M7Z</scope><scope>P64</scope><scope>7X8</scope><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></search><sort><creationdate>202011</creationdate><title>Multi‐parametric liver tissue characterization using MR fingerprinting: Simultaneous T1, T2, T2, and fat fraction mapping</title><author>Jaubert, Olivier ; Arrieta, Cristobal ; Cruz, Gastão ; Bustin, Aurélien ; Schneider, Torben ; Georgiopoulos, Georgios ; Masci, Pier‐Giorgio ; Sing‐Long, Carlos ; Botnar, Rene M. ; Prieto, Claudia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-j2371-dc62b569be5ddda43d48032da8303272610f4776ca0e2dab64d45f11517272313</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Biomarkers</topic><topic>fat fraction</topic><topic>Fingerprinting</topic><topic>In vivo methods and tests</topic><topic>Liver</topic><topic>Liver diseases</topic><topic>liver MRI</topic><topic>Mapping</topic><topic>Measurement methods</topic><topic>MR fingerprinting</topic><topic>quantitative mapping</topic><topic>T1 mapping</topic><topic>T2 mapping</topic><topic>Tensors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><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><collection>Wiley Online Library website</collection><collection>Wiley Online Library website</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biochemistry Abstracts 1</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Magnetic resonance in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jaubert, Olivier</au><au>Arrieta, Cristobal</au><au>Cruz, Gastão</au><au>Bustin, Aurélien</au><au>Schneider, Torben</au><au>Georgiopoulos, Georgios</au><au>Masci, Pier‐Giorgio</au><au>Sing‐Long, Carlos</au><au>Botnar, Rene M.</au><au>Prieto, Claudia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multi‐parametric liver tissue characterization using MR fingerprinting: Simultaneous T1, T2, T2, and fat fraction mapping</atitle><jtitle>Magnetic resonance in medicine</jtitle><date>2020-11</date><risdate>2020</risdate><volume>84</volume><issue>5</issue><spage>2625</spage><epage>2635</epage><pages>2625-2635</pages><issn>0740-3194</issn><eissn>1522-2594</eissn><abstract>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.</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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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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