Inter‐subject stability and regional concentration estimates of 3D‐FID‐MRSI in the human brain at 7 T
Purpose Recently, a 3D‐concentric ring trajectory (CRT)‐based free induction decay (FID)‐MRSI sequence was introduced for fast high‐resolution metabolic imaging at 7 T. This technique provides metabolic ratio maps of almost the entire brain within clinically feasible scan times, but its robustness h...
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creator | Hangel, Gilbert Spurny‐Dworak, Benjamin Lazen, Philipp Cadrien, Cornelius Sharma, Sukrit Hingerl, Lukas Hečková, Eva Strasser, Bernhard Motyka, Stanislav Lipka, Alexandra Gruber, Stephan Brandner, Christoph Lanzenberger, Rupert Rössler, Karl Trattnig, Siegfried Bogner, Wolfgang |
description | Purpose
Recently, a 3D‐concentric ring trajectory (CRT)‐based free induction decay (FID)‐MRSI sequence was introduced for fast high‐resolution metabolic imaging at 7 T. This technique provides metabolic ratio maps of almost the entire brain within clinically feasible scan times, but its robustness has not yet been thoroughly investigated. Therefore, we have assessed quantitative concentration estimates and their variability in healthy volunteers using this approach.
Methods
We acquired whole‐brain 3D‐CRT‐FID‐MRSI at 7 T in 15 min with 3.4 mm nominal isometric resolution in 24 volunteers (12 male, 12 female, mean age 27 ± 6 years). Concentration estimate maps were calculated for 15 metabolites using internal water referencing and evaluated in 55 different regions of interest (ROIs) in the brain. Data quality, mean metabolite concentrations, and their inter‐subject coefficients of variation (CVs) were compared for all ROIs.
Results
Of 24 datasets, one was excluded due to motion artifacts. The concentrations of total choline, total creatine, glutamate, myo‐inositol, and N‐acetylaspartate in 44 regions were estimated within quality thresholds. Inter‐subject CVs (mean over 44 ROIs/minimum/maximum) were 9%/5%/19% for total choline, 10%/6%/20% for total creatine, 11%/7%/24% for glutamate, 10%/6%/19% for myo‐inositol, and 9%/6%/19% for N‐acetylaspartate.
Discussion
We defined the performance of 3D‐CRT‐based FID‐MRSI for metabolite concentration estimate mapping, showing which metabolites could be robustly quantified in which ROIs with which inter‐subject CVs expected. However, the basal brain regions and lesser‐signal metabolites in particular remain as a challenge due susceptibility effects from the proximity to nasal and auditory cavities. Further improvement in quantification and the mitigation of B0/B1‐field inhomogeneities will be necessary to achieve reliable whole‐brain coverage.
We have assessed the typical amplitude and variability of quantitative concentration estimates of 3D‐CRT‐FID‐MRSI at 7 T in healthy volunteers. We successfully estimated, using an internal water reference, metabolite concentrations in 44 brain ROIs that agree with previous literature and determined inter‐subject coefficients of variation. Our results are a step towards future metabolic high‐resolution atlases of the human brain. |
doi_str_mv | 10.1002/nbm.4596 |
format | Article |
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Recently, a 3D‐concentric ring trajectory (CRT)‐based free induction decay (FID)‐MRSI sequence was introduced for fast high‐resolution metabolic imaging at 7 T. This technique provides metabolic ratio maps of almost the entire brain within clinically feasible scan times, but its robustness has not yet been thoroughly investigated. Therefore, we have assessed quantitative concentration estimates and their variability in healthy volunteers using this approach.
Methods
We acquired whole‐brain 3D‐CRT‐FID‐MRSI at 7 T in 15 min with 3.4 mm nominal isometric resolution in 24 volunteers (12 male, 12 female, mean age 27 ± 6 years). Concentration estimate maps were calculated for 15 metabolites using internal water referencing and evaluated in 55 different regions of interest (ROIs) in the brain. Data quality, mean metabolite concentrations, and their inter‐subject coefficients of variation (CVs) were compared for all ROIs.
Results
Of 24 datasets, one was excluded due to motion artifacts. The concentrations of total choline, total creatine, glutamate, myo‐inositol, and N‐acetylaspartate in 44 regions were estimated within quality thresholds. Inter‐subject CVs (mean over 44 ROIs/minimum/maximum) were 9%/5%/19% for total choline, 10%/6%/20% for total creatine, 11%/7%/24% for glutamate, 10%/6%/19% for myo‐inositol, and 9%/6%/19% for N‐acetylaspartate.
Discussion
We defined the performance of 3D‐CRT‐based FID‐MRSI for metabolite concentration estimate mapping, showing which metabolites could be robustly quantified in which ROIs with which inter‐subject CVs expected. However, the basal brain regions and lesser‐signal metabolites in particular remain as a challenge due susceptibility effects from the proximity to nasal and auditory cavities. Further improvement in quantification and the mitigation of B0/B1‐field inhomogeneities will be necessary to achieve reliable whole‐brain coverage.
We have assessed the typical amplitude and variability of quantitative concentration estimates of 3D‐CRT‐FID‐MRSI at 7 T in healthy volunteers. We successfully estimated, using an internal water reference, metabolite concentrations in 44 brain ROIs that agree with previous literature and determined inter‐subject coefficients of variation. Our results are a step towards future metabolic high‐resolution atlases of the human brain.</description><identifier>ISSN: 0952-3480</identifier><identifier>ISSN: 1099-1492</identifier><identifier>EISSN: 1099-1492</identifier><identifier>DOI: 10.1002/nbm.4596</identifier><identifier>PMID: 34382280</identifier><language>eng</language><publisher>England: Wiley Subscription Services, Inc</publisher><subject>7 T ; Adult ; Biological products ; Brain ; Brain - diagnostic imaging ; Brain - metabolism ; Brain mapping ; Choline ; Coefficient of variation ; Creatine ; Estimates ; Female ; healthy brain ; high resolution ; Humans ; Imaging, Three-Dimensional - methods ; Inositol ; Internal water ; inter‐subject reproducibility ; Isometric ; Magnetic Resonance Imaging - methods ; Magnetic Resonance Spectroscopy - methods ; Male ; Mathematical analysis ; Metabolism ; Metabolites ; Mitigation ; MRS ; MRSI ; Neuroimaging ; Reproducibility ; Young Adult</subject><ispartof>NMR in biomedicine, 2021-12, Vol.34 (12), p.e4596-n/a</ispartof><rights>2021 The Authors. published by John Wiley & Sons Ltd.</rights><rights>2021 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.</rights><rights>2021. 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><citedby>FETCH-LOGICAL-c4396-1bbab7c3b976a43dbd6f3652b113f0d2720035d67ad90ef0ab9d502c453509f63</citedby><cites>FETCH-LOGICAL-c4396-1bbab7c3b976a43dbd6f3652b113f0d2720035d67ad90ef0ab9d502c453509f63</cites><orcidid>0000-0002-3986-3159 ; 0000-0002-0130-3463</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fnbm.4596$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fnbm.4596$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,777,781,882,1412,27905,27906,45555,45556</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34382280$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hangel, Gilbert</creatorcontrib><creatorcontrib>Spurny‐Dworak, Benjamin</creatorcontrib><creatorcontrib>Lazen, Philipp</creatorcontrib><creatorcontrib>Cadrien, Cornelius</creatorcontrib><creatorcontrib>Sharma, Sukrit</creatorcontrib><creatorcontrib>Hingerl, Lukas</creatorcontrib><creatorcontrib>Hečková, Eva</creatorcontrib><creatorcontrib>Strasser, Bernhard</creatorcontrib><creatorcontrib>Motyka, Stanislav</creatorcontrib><creatorcontrib>Lipka, Alexandra</creatorcontrib><creatorcontrib>Gruber, Stephan</creatorcontrib><creatorcontrib>Brandner, Christoph</creatorcontrib><creatorcontrib>Lanzenberger, Rupert</creatorcontrib><creatorcontrib>Rössler, Karl</creatorcontrib><creatorcontrib>Trattnig, Siegfried</creatorcontrib><creatorcontrib>Bogner, Wolfgang</creatorcontrib><title>Inter‐subject stability and regional concentration estimates of 3D‐FID‐MRSI in the human brain at 7 T</title><title>NMR in biomedicine</title><addtitle>NMR Biomed</addtitle><description>Purpose
Recently, a 3D‐concentric ring trajectory (CRT)‐based free induction decay (FID)‐MRSI sequence was introduced for fast high‐resolution metabolic imaging at 7 T. This technique provides metabolic ratio maps of almost the entire brain within clinically feasible scan times, but its robustness has not yet been thoroughly investigated. Therefore, we have assessed quantitative concentration estimates and their variability in healthy volunteers using this approach.
Methods
We acquired whole‐brain 3D‐CRT‐FID‐MRSI at 7 T in 15 min with 3.4 mm nominal isometric resolution in 24 volunteers (12 male, 12 female, mean age 27 ± 6 years). Concentration estimate maps were calculated for 15 metabolites using internal water referencing and evaluated in 55 different regions of interest (ROIs) in the brain. Data quality, mean metabolite concentrations, and their inter‐subject coefficients of variation (CVs) were compared for all ROIs.
Results
Of 24 datasets, one was excluded due to motion artifacts. The concentrations of total choline, total creatine, glutamate, myo‐inositol, and N‐acetylaspartate in 44 regions were estimated within quality thresholds. Inter‐subject CVs (mean over 44 ROIs/minimum/maximum) were 9%/5%/19% for total choline, 10%/6%/20% for total creatine, 11%/7%/24% for glutamate, 10%/6%/19% for myo‐inositol, and 9%/6%/19% for N‐acetylaspartate.
Discussion
We defined the performance of 3D‐CRT‐based FID‐MRSI for metabolite concentration estimate mapping, showing which metabolites could be robustly quantified in which ROIs with which inter‐subject CVs expected. However, the basal brain regions and lesser‐signal metabolites in particular remain as a challenge due susceptibility effects from the proximity to nasal and auditory cavities. Further improvement in quantification and the mitigation of B0/B1‐field inhomogeneities will be necessary to achieve reliable whole‐brain coverage.
We have assessed the typical amplitude and variability of quantitative concentration estimates of 3D‐CRT‐FID‐MRSI at 7 T in healthy volunteers. We successfully estimated, using an internal water reference, metabolite concentrations in 44 brain ROIs that agree with previous literature and determined inter‐subject coefficients of variation. Our results are a step towards future metabolic high‐resolution atlases of the human brain.</description><subject>7 T</subject><subject>Adult</subject><subject>Biological products</subject><subject>Brain</subject><subject>Brain - diagnostic imaging</subject><subject>Brain - metabolism</subject><subject>Brain mapping</subject><subject>Choline</subject><subject>Coefficient of variation</subject><subject>Creatine</subject><subject>Estimates</subject><subject>Female</subject><subject>healthy brain</subject><subject>high resolution</subject><subject>Humans</subject><subject>Imaging, Three-Dimensional - methods</subject><subject>Inositol</subject><subject>Internal water</subject><subject>inter‐subject reproducibility</subject><subject>Isometric</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Magnetic Resonance Spectroscopy - methods</subject><subject>Male</subject><subject>Mathematical analysis</subject><subject>Metabolism</subject><subject>Metabolites</subject><subject>Mitigation</subject><subject>MRS</subject><subject>MRSI</subject><subject>Neuroimaging</subject><subject>Reproducibility</subject><subject>Young Adult</subject><issn>0952-3480</issn><issn>1099-1492</issn><issn>1099-1492</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>EIF</sourceid><recordid>eNp1kd1uFCEYhomxsdtq4hUYEk88mfbjb2Y4MlqtbtJqovWYwAzTZZ2BFhjNnvUSvEavRNat9SfxBPKFhycvvAg9JnBEAOixN9MRF7K-hxYEpKwIl_Q-WoAUtGK8hX10kNIaAFrO6AO0zzhrKW1hgT4vfbbx-823NJu17TJOWRs3urzB2vc42ksXvB5xF3xnfY46lxnblN2ks004DJi9KtdPl9v1_MPHJXYe55XFq3nSHpuoy6wzbvDFQ7Q36DHZR7f7Ifp0-vri5G119v7N8uTFWdVxJuuKGKNN0zEjm1pz1pu-HlgtqCGEDdDThgIw0deN7iXYAbSRvQDaccEEyKFmh-j5zns1m8n2u9yjuoolc9yooJ36-8S7lboMXxQhvBGUtcXw7NYQw_VcXqsmlzo7jtrbMCdFRQ0tYxRkQZ_-g67DHMuXbSnZSCZkC7-FXQwpRTvcpSGgthWqUqHaVljQJ3-mvwN_dVaAagd8daPd_Fek3r08_yn8AaVgp4I</recordid><startdate>202112</startdate><enddate>202112</enddate><creator>Hangel, Gilbert</creator><creator>Spurny‐Dworak, Benjamin</creator><creator>Lazen, Philipp</creator><creator>Cadrien, Cornelius</creator><creator>Sharma, Sukrit</creator><creator>Hingerl, Lukas</creator><creator>Hečková, Eva</creator><creator>Strasser, Bernhard</creator><creator>Motyka, Stanislav</creator><creator>Lipka, Alexandra</creator><creator>Gruber, Stephan</creator><creator>Brandner, Christoph</creator><creator>Lanzenberger, Rupert</creator><creator>Rössler, Karl</creator><creator>Trattnig, Siegfried</creator><creator>Bogner, Wolfgang</creator><general>Wiley Subscription Services, Inc</general><general>John Wiley and Sons Inc</general><scope>24P</scope><scope>WIN</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-3986-3159</orcidid><orcidid>https://orcid.org/0000-0002-0130-3463</orcidid></search><sort><creationdate>202112</creationdate><title>Inter‐subject stability and regional concentration estimates of 3D‐FID‐MRSI in the human brain at 7 T</title><author>Hangel, Gilbert ; Spurny‐Dworak, Benjamin ; Lazen, Philipp ; Cadrien, Cornelius ; Sharma, Sukrit ; Hingerl, Lukas ; Hečková, Eva ; Strasser, Bernhard ; Motyka, Stanislav ; Lipka, Alexandra ; Gruber, Stephan ; Brandner, Christoph ; Lanzenberger, Rupert ; Rössler, Karl ; Trattnig, Siegfried ; Bogner, Wolfgang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4396-1bbab7c3b976a43dbd6f3652b113f0d2720035d67ad90ef0ab9d502c453509f63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>7 T</topic><topic>Adult</topic><topic>Biological products</topic><topic>Brain</topic><topic>Brain - diagnostic imaging</topic><topic>Brain - metabolism</topic><topic>Brain mapping</topic><topic>Choline</topic><topic>Coefficient of variation</topic><topic>Creatine</topic><topic>Estimates</topic><topic>Female</topic><topic>healthy brain</topic><topic>high resolution</topic><topic>Humans</topic><topic>Imaging, Three-Dimensional - methods</topic><topic>Inositol</topic><topic>Internal water</topic><topic>inter‐subject reproducibility</topic><topic>Isometric</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Magnetic Resonance Spectroscopy - methods</topic><topic>Male</topic><topic>Mathematical analysis</topic><topic>Metabolism</topic><topic>Metabolites</topic><topic>Mitigation</topic><topic>MRS</topic><topic>MRSI</topic><topic>Neuroimaging</topic><topic>Reproducibility</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hangel, Gilbert</creatorcontrib><creatorcontrib>Spurny‐Dworak, Benjamin</creatorcontrib><creatorcontrib>Lazen, Philipp</creatorcontrib><creatorcontrib>Cadrien, Cornelius</creatorcontrib><creatorcontrib>Sharma, Sukrit</creatorcontrib><creatorcontrib>Hingerl, Lukas</creatorcontrib><creatorcontrib>Hečková, Eva</creatorcontrib><creatorcontrib>Strasser, Bernhard</creatorcontrib><creatorcontrib>Motyka, Stanislav</creatorcontrib><creatorcontrib>Lipka, Alexandra</creatorcontrib><creatorcontrib>Gruber, Stephan</creatorcontrib><creatorcontrib>Brandner, Christoph</creatorcontrib><creatorcontrib>Lanzenberger, Rupert</creatorcontrib><creatorcontrib>Rössler, Karl</creatorcontrib><creatorcontrib>Trattnig, Siegfried</creatorcontrib><creatorcontrib>Bogner, Wolfgang</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Free Content</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>NMR in biomedicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hangel, Gilbert</au><au>Spurny‐Dworak, Benjamin</au><au>Lazen, Philipp</au><au>Cadrien, Cornelius</au><au>Sharma, Sukrit</au><au>Hingerl, Lukas</au><au>Hečková, Eva</au><au>Strasser, Bernhard</au><au>Motyka, Stanislav</au><au>Lipka, Alexandra</au><au>Gruber, Stephan</au><au>Brandner, Christoph</au><au>Lanzenberger, Rupert</au><au>Rössler, Karl</au><au>Trattnig, Siegfried</au><au>Bogner, Wolfgang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Inter‐subject stability and regional concentration estimates of 3D‐FID‐MRSI in the human brain at 7 T</atitle><jtitle>NMR in biomedicine</jtitle><addtitle>NMR Biomed</addtitle><date>2021-12</date><risdate>2021</risdate><volume>34</volume><issue>12</issue><spage>e4596</spage><epage>n/a</epage><pages>e4596-n/a</pages><issn>0952-3480</issn><issn>1099-1492</issn><eissn>1099-1492</eissn><abstract>Purpose
Recently, a 3D‐concentric ring trajectory (CRT)‐based free induction decay (FID)‐MRSI sequence was introduced for fast high‐resolution metabolic imaging at 7 T. This technique provides metabolic ratio maps of almost the entire brain within clinically feasible scan times, but its robustness has not yet been thoroughly investigated. Therefore, we have assessed quantitative concentration estimates and their variability in healthy volunteers using this approach.
Methods
We acquired whole‐brain 3D‐CRT‐FID‐MRSI at 7 T in 15 min with 3.4 mm nominal isometric resolution in 24 volunteers (12 male, 12 female, mean age 27 ± 6 years). Concentration estimate maps were calculated for 15 metabolites using internal water referencing and evaluated in 55 different regions of interest (ROIs) in the brain. Data quality, mean metabolite concentrations, and their inter‐subject coefficients of variation (CVs) were compared for all ROIs.
Results
Of 24 datasets, one was excluded due to motion artifacts. The concentrations of total choline, total creatine, glutamate, myo‐inositol, and N‐acetylaspartate in 44 regions were estimated within quality thresholds. Inter‐subject CVs (mean over 44 ROIs/minimum/maximum) were 9%/5%/19% for total choline, 10%/6%/20% for total creatine, 11%/7%/24% for glutamate, 10%/6%/19% for myo‐inositol, and 9%/6%/19% for N‐acetylaspartate.
Discussion
We defined the performance of 3D‐CRT‐based FID‐MRSI for metabolite concentration estimate mapping, showing which metabolites could be robustly quantified in which ROIs with which inter‐subject CVs expected. However, the basal brain regions and lesser‐signal metabolites in particular remain as a challenge due susceptibility effects from the proximity to nasal and auditory cavities. Further improvement in quantification and the mitigation of B0/B1‐field inhomogeneities will be necessary to achieve reliable whole‐brain coverage.
We have assessed the typical amplitude and variability of quantitative concentration estimates of 3D‐CRT‐FID‐MRSI at 7 T in healthy volunteers. We successfully estimated, using an internal water reference, metabolite concentrations in 44 brain ROIs that agree with previous literature and determined inter‐subject coefficients of variation. Our results are a step towards future metabolic high‐resolution atlases of the human brain.</abstract><cop>England</cop><pub>Wiley Subscription Services, Inc</pub><pmid>34382280</pmid><doi>10.1002/nbm.4596</doi><tpages>20</tpages><orcidid>https://orcid.org/0000-0002-3986-3159</orcidid><orcidid>https://orcid.org/0000-0002-0130-3463</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | 7 T Adult Biological products Brain Brain - diagnostic imaging Brain - metabolism Brain mapping Choline Coefficient of variation Creatine Estimates Female healthy brain high resolution Humans Imaging, Three-Dimensional - methods Inositol Internal water inter‐subject reproducibility Isometric Magnetic Resonance Imaging - methods Magnetic Resonance Spectroscopy - methods Male Mathematical analysis Metabolism Metabolites Mitigation MRS MRSI Neuroimaging Reproducibility Young Adult |
title | Inter‐subject stability and regional concentration estimates of 3D‐FID‐MRSI in the human brain at 7 T |
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