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Normalizing data from GABA-edited MEGA-PRESS implementations at 3 Tesla
Standardization of results is an important milestone in the maturation of any truly quantitative methodology. For instance, a lack of measurement agreement across imaging platforms limits multisite studies, between-study comparisons based on the literature, and inferences based on and the generaliza...
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Published in: | Magnetic resonance imaging 2017-10, Vol.42, p.8-15 |
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description | Standardization of results is an important milestone in the maturation of any truly quantitative methodology. For instance, a lack of measurement agreement across imaging platforms limits multisite studies, between-study comparisons based on the literature, and inferences based on and the generalizability of results. In GABA-edited MEGA-PRESS, two key sources of differences between implementations are: differences in editing efficiency of GABA and the degree of co-editing of macromolecules (MM). In this work, GABA editing efficiency κ and MM-co-editing μ constants are determined for three widely used MEGA-PRESS implementations (on the most common MRI platforms; GE, Philips, and Siemens) by phantom experiments. Implementation-specific κ,μ-corrections were then applied to two in vivo datasets, one consisted of 8 subject scanned on the three platforms and the other one subject scanned eight times on each platform. Manufacturer-specific κ and μ values were determined as: κGE=0.436, κSiemens=0.366 and κPhilips=0.394 and μGE=0.83, μSiemens=0.625 and μPhilips=0.75. Applying the κ,μ-correction on the Cr-referenced data decreased the coefficient of variation (CV) of the data for both in vivo data sets (multisubjects: uncorrected CV=13%, κ,μ-corrected CV=5%, single subject: uncorrected CV=23%, κ,μ-corrected CV=13%) but had no significant effect on mean GABA levels. For the water-referenced results, CV increased in the multisubject data (uncorrected CV=6.7%, κ,μ-corrected CV=14%) while it decreased in the single subject data (uncorrected CV=24%, κ,μ-corrected CV=21%) and manufacturer was a significant source of variance in the κ,μ-corrected data. Applying a correction for editing efficiency and macromolecule contamination decreases the variance between different manufacturers for creatine-referenced data, but other sources of variance remain. |
doi_str_mv | 10.1016/j.mri.2017.04.013 |
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Andrea ; Rowland, Laura M. ; Mikkelsen, Mark ; Barker, Peter B. ; Evans, C. John ; Edden, Richard A.E.</creator><creatorcontrib>Harris, Ashley D. ; Puts, Nicolaas A.J. ; Wijtenburg, S. Andrea ; Rowland, Laura M. ; Mikkelsen, Mark ; Barker, Peter B. ; Evans, C. John ; Edden, Richard A.E.</creatorcontrib><description>Standardization of results is an important milestone in the maturation of any truly quantitative methodology. For instance, a lack of measurement agreement across imaging platforms limits multisite studies, between-study comparisons based on the literature, and inferences based on and the generalizability of results. In GABA-edited MEGA-PRESS, two key sources of differences between implementations are: differences in editing efficiency of GABA and the degree of co-editing of macromolecules (MM). In this work, GABA editing efficiency κ and MM-co-editing μ constants are determined for three widely used MEGA-PRESS implementations (on the most common MRI platforms; GE, Philips, and Siemens) by phantom experiments. Implementation-specific κ,μ-corrections were then applied to two in vivo datasets, one consisted of 8 subject scanned on the three platforms and the other one subject scanned eight times on each platform. Manufacturer-specific κ and μ values were determined as: κGE=0.436, κSiemens=0.366 and κPhilips=0.394 and μGE=0.83, μSiemens=0.625 and μPhilips=0.75. Applying the κ,μ-correction on the Cr-referenced data decreased the coefficient of variation (CV) of the data for both in vivo data sets (multisubjects: uncorrected CV=13%, κ,μ-corrected CV=5%, single subject: uncorrected CV=23%, κ,μ-corrected CV=13%) but had no significant effect on mean GABA levels. For the water-referenced results, CV increased in the multisubject data (uncorrected CV=6.7%, κ,μ-corrected CV=14%) while it decreased in the single subject data (uncorrected CV=24%, κ,μ-corrected CV=21%) and manufacturer was a significant source of variance in the κ,μ-corrected data. Applying a correction for editing efficiency and macromolecule contamination decreases the variance between different manufacturers for creatine-referenced data, but other sources of variance remain.</description><identifier>ISSN: 0730-725X</identifier><identifier>EISSN: 1873-5894</identifier><identifier>DOI: 10.1016/j.mri.2017.04.013</identifier><identifier>PMID: 28479342</identifier><language>eng</language><publisher>Netherlands: Elsevier Inc</publisher><subject>Adult ; Cross-platform ; Editing efficiency ; Female ; GABA ; gamma-Aminobutyric Acid - metabolism ; Humans ; Macromolecular co-editing ; Macromolecular Substances - metabolism ; Magnetic Resonance Spectroscopy - methods ; Male ; MEGA-PRESS ; Multi-site ; Phantoms, Imaging</subject><ispartof>Magnetic resonance imaging, 2017-10, Vol.42, p.8-15</ispartof><rights>2017 Elsevier Inc.</rights><rights>Copyright © 2017 Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c504t-c29bc3a8eae51ef5de0af81be805d32d7dd6630f8bdf3993bd05eab25ac4eed33</citedby><cites>FETCH-LOGICAL-c504t-c29bc3a8eae51ef5de0af81be805d32d7dd6630f8bdf3993bd05eab25ac4eed33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28479342$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Harris, Ashley D.</creatorcontrib><creatorcontrib>Puts, Nicolaas A.J.</creatorcontrib><creatorcontrib>Wijtenburg, S. Andrea</creatorcontrib><creatorcontrib>Rowland, Laura M.</creatorcontrib><creatorcontrib>Mikkelsen, Mark</creatorcontrib><creatorcontrib>Barker, Peter B.</creatorcontrib><creatorcontrib>Evans, C. John</creatorcontrib><creatorcontrib>Edden, Richard A.E.</creatorcontrib><title>Normalizing data from GABA-edited MEGA-PRESS implementations at 3 Tesla</title><title>Magnetic resonance imaging</title><addtitle>Magn Reson Imaging</addtitle><description>Standardization of results is an important milestone in the maturation of any truly quantitative methodology. For instance, a lack of measurement agreement across imaging platforms limits multisite studies, between-study comparisons based on the literature, and inferences based on and the generalizability of results. In GABA-edited MEGA-PRESS, two key sources of differences between implementations are: differences in editing efficiency of GABA and the degree of co-editing of macromolecules (MM). In this work, GABA editing efficiency κ and MM-co-editing μ constants are determined for three widely used MEGA-PRESS implementations (on the most common MRI platforms; GE, Philips, and Siemens) by phantom experiments. Implementation-specific κ,μ-corrections were then applied to two in vivo datasets, one consisted of 8 subject scanned on the three platforms and the other one subject scanned eight times on each platform. Manufacturer-specific κ and μ values were determined as: κGE=0.436, κSiemens=0.366 and κPhilips=0.394 and μGE=0.83, μSiemens=0.625 and μPhilips=0.75. Applying the κ,μ-correction on the Cr-referenced data decreased the coefficient of variation (CV) of the data for both in vivo data sets (multisubjects: uncorrected CV=13%, κ,μ-corrected CV=5%, single subject: uncorrected CV=23%, κ,μ-corrected CV=13%) but had no significant effect on mean GABA levels. For the water-referenced results, CV increased in the multisubject data (uncorrected CV=6.7%, κ,μ-corrected CV=14%) while it decreased in the single subject data (uncorrected CV=24%, κ,μ-corrected CV=21%) and manufacturer was a significant source of variance in the κ,μ-corrected data. Applying a correction for editing efficiency and macromolecule contamination decreases the variance between different manufacturers for creatine-referenced data, but other sources of variance remain.</description><subject>Adult</subject><subject>Cross-platform</subject><subject>Editing efficiency</subject><subject>Female</subject><subject>GABA</subject><subject>gamma-Aminobutyric Acid - metabolism</subject><subject>Humans</subject><subject>Macromolecular co-editing</subject><subject>Macromolecular Substances - metabolism</subject><subject>Magnetic Resonance Spectroscopy - methods</subject><subject>Male</subject><subject>MEGA-PRESS</subject><subject>Multi-site</subject><subject>Phantoms, Imaging</subject><issn>0730-725X</issn><issn>1873-5894</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp9kUFP3DAQha2qqGwpP6AXlGMvCePYThwhVVrQdosEtCog9WY59gS8SuLFziLBr6_RAqIXTnOY996M3kfIVwoFBVodroohuKIEWhfAC6DsA5lRWbNcyIZ_JDOoGeR1Kf7uks8xrgBAlEx8Irul5HXDeDkjywsfBt27RzfeZFZPOuuCH7Ll_Hieo3UT2ux8sZznv_8sLi8zN6x7HHCc9OT8GDM9ZSy7wtjrL2Sn033E_ee5R65_LK5OfuZnv5anJ_Oz3AjgU27KpjVMS9QoKHbCIuhO0hYlCMtKW1tbVQw62dqONQ1rLQjUbSm04YiWsT3yfZu73rQDWpN-CbpX6-AGHR6U1079vxndrbrx90oISauqTgHfngOCv9tgnNTgosG-1yP6TVRUNhWnlANPUrqVmuBjDNi9nqGgngColUoA1BMABVwlAMlz8Pa_V8dL40lwtBVgauneYVDROBxNKjugmZT17p34f1B7l1Y</recordid><startdate>20171001</startdate><enddate>20171001</enddate><creator>Harris, Ashley D.</creator><creator>Puts, Nicolaas A.J.</creator><creator>Wijtenburg, S. Andrea</creator><creator>Rowland, Laura M.</creator><creator>Mikkelsen, Mark</creator><creator>Barker, Peter B.</creator><creator>Evans, C. John</creator><creator>Edden, Richard A.E.</creator><general>Elsevier Inc</general><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>7X8</scope><scope>5PM</scope></search><sort><creationdate>20171001</creationdate><title>Normalizing data from GABA-edited MEGA-PRESS implementations at 3 Tesla</title><author>Harris, Ashley D. ; Puts, Nicolaas A.J. ; Wijtenburg, S. Andrea ; Rowland, Laura M. ; Mikkelsen, Mark ; Barker, Peter B. ; Evans, C. 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Andrea</creatorcontrib><creatorcontrib>Rowland, Laura M.</creatorcontrib><creatorcontrib>Mikkelsen, Mark</creatorcontrib><creatorcontrib>Barker, Peter B.</creatorcontrib><creatorcontrib>Evans, C. John</creatorcontrib><creatorcontrib>Edden, Richard A.E.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Magnetic resonance imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Harris, Ashley D.</au><au>Puts, Nicolaas A.J.</au><au>Wijtenburg, S. Andrea</au><au>Rowland, Laura M.</au><au>Mikkelsen, Mark</au><au>Barker, Peter B.</au><au>Evans, C. John</au><au>Edden, Richard A.E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Normalizing data from GABA-edited MEGA-PRESS implementations at 3 Tesla</atitle><jtitle>Magnetic resonance imaging</jtitle><addtitle>Magn Reson Imaging</addtitle><date>2017-10-01</date><risdate>2017</risdate><volume>42</volume><spage>8</spage><epage>15</epage><pages>8-15</pages><issn>0730-725X</issn><eissn>1873-5894</eissn><abstract>Standardization of results is an important milestone in the maturation of any truly quantitative methodology. For instance, a lack of measurement agreement across imaging platforms limits multisite studies, between-study comparisons based on the literature, and inferences based on and the generalizability of results. In GABA-edited MEGA-PRESS, two key sources of differences between implementations are: differences in editing efficiency of GABA and the degree of co-editing of macromolecules (MM). In this work, GABA editing efficiency κ and MM-co-editing μ constants are determined for three widely used MEGA-PRESS implementations (on the most common MRI platforms; GE, Philips, and Siemens) by phantom experiments. Implementation-specific κ,μ-corrections were then applied to two in vivo datasets, one consisted of 8 subject scanned on the three platforms and the other one subject scanned eight times on each platform. Manufacturer-specific κ and μ values were determined as: κGE=0.436, κSiemens=0.366 and κPhilips=0.394 and μGE=0.83, μSiemens=0.625 and μPhilips=0.75. Applying the κ,μ-correction on the Cr-referenced data decreased the coefficient of variation (CV) of the data for both in vivo data sets (multisubjects: uncorrected CV=13%, κ,μ-corrected CV=5%, single subject: uncorrected CV=23%, κ,μ-corrected CV=13%) but had no significant effect on mean GABA levels. For the water-referenced results, CV increased in the multisubject data (uncorrected CV=6.7%, κ,μ-corrected CV=14%) while it decreased in the single subject data (uncorrected CV=24%, κ,μ-corrected CV=21%) and manufacturer was a significant source of variance in the κ,μ-corrected data. Applying a correction for editing efficiency and macromolecule contamination decreases the variance between different manufacturers for creatine-referenced data, but other sources of variance remain.</abstract><cop>Netherlands</cop><pub>Elsevier Inc</pub><pmid>28479342</pmid><doi>10.1016/j.mri.2017.04.013</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adult Cross-platform Editing efficiency Female GABA gamma-Aminobutyric Acid - metabolism Humans Macromolecular co-editing Macromolecular Substances - metabolism Magnetic Resonance Spectroscopy - methods Male MEGA-PRESS Multi-site Phantoms, Imaging |
title | Normalizing data from GABA-edited MEGA-PRESS implementations at 3 Tesla |
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