Quantitative susceptibility mapping (QSM) minimizes interference from cellular pathology in R2 estimation of liver iron concentration
Background A challenge for R2 and R2* methods in measuring liver iron concentration (LIC) is that fibrosis, fat, and other hepatic cellular pathology contribute to R2 and R2* and interfere with LIC estimation. Purpose To examine the interfering effects of fibrosis, fat, and other lesions on R2* LIC...
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| Veröffentlicht in: | Journal of magnetic resonance imaging 2018-10, Vol.48 (4), p.1069-1079 |
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| creator | Li, Jianqi Lin, Huimin Liu, Tian Zhang, Zhuwei Prince, Martin R. Gillen, Kelly Yan, Xu Song, Qi Hua, Ting Zhao, Xiance Zhang, Miao Zhao, Yu Li, Gaiying Tang, Guangyu Yang, Guang Brittenham, Gary M. Wang, Yi |
| description | Background
A challenge for R2 and R2* methods in measuring liver iron concentration (LIC) is that fibrosis, fat, and other hepatic cellular pathology contribute to R2 and R2* and interfere with LIC estimation.
Purpose
To examine the interfering effects of fibrosis, fat, and other lesions on R2* LIC estimation and to use quantitative susceptibility mapping (QSM) to reduce these distortions.
Study Type
Prospective.
Phantoms, Subjects
Water phantoms with various concentrations of gadolinium (Gd), collagen (Cl, modeling fibrosis), and fat; nine healthy controls with no known hepatic disease, nine patients with known or suspected hepatic iron overload, and nine patients with focal liver lesions.
Field Strength/Sequence
The phantoms and human subjects were imaged using a 3D multiecho gradient‐echo on clinical 1.5T and 3T MRI systems.
Assessment
QSM and R2* images were postprocessed from the same gradient‐echo data. Fat contributions to susceptibility and R2* were corrected in signal models for LIC estimation.
Statistical Tests
Polynomial regression analyses were performed to examine relations among susceptibility, R2* and true [Gd] and [Cl] in phantoms, and among susceptibility and R2* in patient livers.
Results
In phantoms, R2* had a strong nonlinear dependency on [Cl], [fat], and [Gd], while susceptibility was linearly dependent (R2 > 0.98). In patients, R2* was highly sensitive to liver pathological changes, including fat, fibrosis, and tumors, while QSM was relatively insensitive to these abnormalities (P = 0.015). With moderate iron overload, liver susceptibility and R2* were not linearly correlated over a common R2* range [0, 100] sec−1 (P = 0.35).
Data Conclusion
R2* estimation of LIC is prone to substantial nonlinear interference from fat, fibrosis, and other lesions. QSM processing of the same gradient echo MRI data can effectively minimize the effects of cellular pathology.
Level of Evidence: 1
Technical Efficacy: Stage 1
J. Magn. Reson. Imaging 2018;48:1069–1079. |
| doi_str_mv | 10.1002/jmri.26019 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6151179</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2018018294</sourcerecordid><originalsourceid>FETCH-LOGICAL-c5149-56c98dee0136681201c4a4499ab1c9cf9e3a761dfea0228d8309917132d7f1a13</originalsourceid><addsrcrecordid>eNp9kU1rFTEYhYMo9kM3_gAJuKnC1LyZmcxkI0jxo9IirboOuZnMbS4zyZhkKrd7_7fv7dSiLoRAEt4nJ-dwCHkG7BgY4683Y3THXDCQD8g-1JwXvG7FQzyzuiygZc0eOUhpwxiTsqofkz0uayGqSu6Tnxez9tllnd21pWlOxk7Zrdzg8paOepqcX9Ojiy_nL-novBvdjU3U-Wxjb6P1xtI-hpEaOwzzoCOddL4KQ1hvEaKXnNqU3YjiwdPQ0wE_idRFvJmAj32Ot7Mn5FGvh2Sf3u2H5Nv7d19PPhZnnz-cnrw9K0wNlSxqYWTbWcugFKIFzsBUGmNIvQIjTS9tqRsBXW8147zt2hIDQwMl75oeNJSH5M2iO82r0XaLgUFNET3GrQraqb8n3l2pdbhWAmqARqLA0Z1ADN9nDKdGl3bhtbdhTgottbi4rBB98Q-6CXP0GE9xACEkL6sWqVcLZWJIKdr-3gwwtWtX7dpVt-0i_PxP-_fo7zoRgAX44Qa7_Y-U-nR-ebqI_gJ2Z7K5</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2116692348</pqid></control><display><type>article</type><title>Quantitative susceptibility mapping (QSM) minimizes interference from cellular pathology in R2 estimation of liver iron concentration</title><source>Wiley Free Content</source><source>Wiley Online Library Journals Frontfile Complete</source><creator>Li, Jianqi ; Lin, Huimin ; Liu, Tian ; Zhang, Zhuwei ; Prince, Martin R. ; Gillen, Kelly ; Yan, Xu ; Song, Qi ; Hua, Ting ; Zhao, Xiance ; Zhang, Miao ; Zhao, Yu ; Li, Gaiying ; Tang, Guangyu ; Yang, Guang ; Brittenham, Gary M. ; Wang, Yi</creator><creatorcontrib>Li, Jianqi ; Lin, Huimin ; Liu, Tian ; Zhang, Zhuwei ; Prince, Martin R. ; Gillen, Kelly ; Yan, Xu ; Song, Qi ; Hua, Ting ; Zhao, Xiance ; Zhang, Miao ; Zhao, Yu ; Li, Gaiying ; Tang, Guangyu ; Yang, Guang ; Brittenham, Gary M. ; Wang, Yi</creatorcontrib><description>Background
A challenge for R2 and R2* methods in measuring liver iron concentration (LIC) is that fibrosis, fat, and other hepatic cellular pathology contribute to R2 and R2* and interfere with LIC estimation.
Purpose
To examine the interfering effects of fibrosis, fat, and other lesions on R2* LIC estimation and to use quantitative susceptibility mapping (QSM) to reduce these distortions.
Study Type
Prospective.
Phantoms, Subjects
Water phantoms with various concentrations of gadolinium (Gd), collagen (Cl, modeling fibrosis), and fat; nine healthy controls with no known hepatic disease, nine patients with known or suspected hepatic iron overload, and nine patients with focal liver lesions.
Field Strength/Sequence
The phantoms and human subjects were imaged using a 3D multiecho gradient‐echo on clinical 1.5T and 3T MRI systems.
Assessment
QSM and R2* images were postprocessed from the same gradient‐echo data. Fat contributions to susceptibility and R2* were corrected in signal models for LIC estimation.
Statistical Tests
Polynomial regression analyses were performed to examine relations among susceptibility, R2* and true [Gd] and [Cl] in phantoms, and among susceptibility and R2* in patient livers.
Results
In phantoms, R2* had a strong nonlinear dependency on [Cl], [fat], and [Gd], while susceptibility was linearly dependent (R2 > 0.98). In patients, R2* was highly sensitive to liver pathological changes, including fat, fibrosis, and tumors, while QSM was relatively insensitive to these abnormalities (P = 0.015). With moderate iron overload, liver susceptibility and R2* were not linearly correlated over a common R2* range [0, 100] sec−1 (P = 0.35).
Data Conclusion
R2* estimation of LIC is prone to substantial nonlinear interference from fat, fibrosis, and other lesions. QSM processing of the same gradient echo MRI data can effectively minimize the effects of cellular pathology.
Level of Evidence: 1
Technical Efficacy: Stage 1
J. Magn. Reson. Imaging 2018;48:1069–1079.</description><identifier>ISSN: 1053-1807</identifier><identifier>EISSN: 1522-2586</identifier><identifier>DOI: 10.1002/jmri.26019</identifier><identifier>PMID: 29566449</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Abnormalities ; cellularity ; Collagen ; Dependence ; Disease control ; Fibrosis ; Field strength ; Gadolinium ; Interference ; Iron ; Lesions ; Liver ; Liver diseases ; liver iron concentration ; Magnetic resonance imaging ; magnetic susceptibility ; Mapping ; Measurement methods ; Medical imaging ; Pathology ; Patients ; QSM ; quantitative susceptibility mapping ; Regression analysis ; Statistical analysis ; Statistical tests ; Tumors</subject><ispartof>Journal of magnetic resonance imaging, 2018-10, Vol.48 (4), p.1069-1079</ispartof><rights>2018 International Society for Magnetic Resonance in Medicine</rights><rights>2018 International Society for Magnetic Resonance in Medicine.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5149-56c98dee0136681201c4a4499ab1c9cf9e3a761dfea0228d8309917132d7f1a13</citedby><cites>FETCH-LOGICAL-c5149-56c98dee0136681201c4a4499ab1c9cf9e3a761dfea0228d8309917132d7f1a13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjmri.26019$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjmri.26019$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,776,780,881,1411,1427,27901,27902,45550,45551,46384,46808</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29566449$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Jianqi</creatorcontrib><creatorcontrib>Lin, Huimin</creatorcontrib><creatorcontrib>Liu, Tian</creatorcontrib><creatorcontrib>Zhang, Zhuwei</creatorcontrib><creatorcontrib>Prince, Martin R.</creatorcontrib><creatorcontrib>Gillen, Kelly</creatorcontrib><creatorcontrib>Yan, Xu</creatorcontrib><creatorcontrib>Song, Qi</creatorcontrib><creatorcontrib>Hua, Ting</creatorcontrib><creatorcontrib>Zhao, Xiance</creatorcontrib><creatorcontrib>Zhang, Miao</creatorcontrib><creatorcontrib>Zhao, Yu</creatorcontrib><creatorcontrib>Li, Gaiying</creatorcontrib><creatorcontrib>Tang, Guangyu</creatorcontrib><creatorcontrib>Yang, Guang</creatorcontrib><creatorcontrib>Brittenham, Gary M.</creatorcontrib><creatorcontrib>Wang, Yi</creatorcontrib><title>Quantitative susceptibility mapping (QSM) minimizes interference from cellular pathology in R2 estimation of liver iron concentration</title><title>Journal of magnetic resonance imaging</title><addtitle>J Magn Reson Imaging</addtitle><description>Background
A challenge for R2 and R2* methods in measuring liver iron concentration (LIC) is that fibrosis, fat, and other hepatic cellular pathology contribute to R2 and R2* and interfere with LIC estimation.
Purpose
To examine the interfering effects of fibrosis, fat, and other lesions on R2* LIC estimation and to use quantitative susceptibility mapping (QSM) to reduce these distortions.
Study Type
Prospective.
Phantoms, Subjects
Water phantoms with various concentrations of gadolinium (Gd), collagen (Cl, modeling fibrosis), and fat; nine healthy controls with no known hepatic disease, nine patients with known or suspected hepatic iron overload, and nine patients with focal liver lesions.
Field Strength/Sequence
The phantoms and human subjects were imaged using a 3D multiecho gradient‐echo on clinical 1.5T and 3T MRI systems.
Assessment
QSM and R2* images were postprocessed from the same gradient‐echo data. Fat contributions to susceptibility and R2* were corrected in signal models for LIC estimation.
Statistical Tests
Polynomial regression analyses were performed to examine relations among susceptibility, R2* and true [Gd] and [Cl] in phantoms, and among susceptibility and R2* in patient livers.
Results
In phantoms, R2* had a strong nonlinear dependency on [Cl], [fat], and [Gd], while susceptibility was linearly dependent (R2 > 0.98). In patients, R2* was highly sensitive to liver pathological changes, including fat, fibrosis, and tumors, while QSM was relatively insensitive to these abnormalities (P = 0.015). With moderate iron overload, liver susceptibility and R2* were not linearly correlated over a common R2* range [0, 100] sec−1 (P = 0.35).
Data Conclusion
R2* estimation of LIC is prone to substantial nonlinear interference from fat, fibrosis, and other lesions. QSM processing of the same gradient echo MRI data can effectively minimize the effects of cellular pathology.
Level of Evidence: 1
Technical Efficacy: Stage 1
J. Magn. Reson. Imaging 2018;48:1069–1079.</description><subject>Abnormalities</subject><subject>cellularity</subject><subject>Collagen</subject><subject>Dependence</subject><subject>Disease control</subject><subject>Fibrosis</subject><subject>Field strength</subject><subject>Gadolinium</subject><subject>Interference</subject><subject>Iron</subject><subject>Lesions</subject><subject>Liver</subject><subject>Liver diseases</subject><subject>liver iron concentration</subject><subject>Magnetic resonance imaging</subject><subject>magnetic susceptibility</subject><subject>Mapping</subject><subject>Measurement methods</subject><subject>Medical imaging</subject><subject>Pathology</subject><subject>Patients</subject><subject>QSM</subject><subject>quantitative susceptibility mapping</subject><subject>Regression analysis</subject><subject>Statistical analysis</subject><subject>Statistical tests</subject><subject>Tumors</subject><issn>1053-1807</issn><issn>1522-2586</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp9kU1rFTEYhYMo9kM3_gAJuKnC1LyZmcxkI0jxo9IirboOuZnMbS4zyZhkKrd7_7fv7dSiLoRAEt4nJ-dwCHkG7BgY4683Y3THXDCQD8g-1JwXvG7FQzyzuiygZc0eOUhpwxiTsqofkz0uayGqSu6Tnxez9tllnd21pWlOxk7Zrdzg8paOepqcX9Ojiy_nL-novBvdjU3U-Wxjb6P1xtI-hpEaOwzzoCOddL4KQ1hvEaKXnNqU3YjiwdPQ0wE_idRFvJmAj32Ot7Mn5FGvh2Sf3u2H5Nv7d19PPhZnnz-cnrw9K0wNlSxqYWTbWcugFKIFzsBUGmNIvQIjTS9tqRsBXW8147zt2hIDQwMl75oeNJSH5M2iO82r0XaLgUFNET3GrQraqb8n3l2pdbhWAmqARqLA0Z1ADN9nDKdGl3bhtbdhTgottbi4rBB98Q-6CXP0GE9xACEkL6sWqVcLZWJIKdr-3gwwtWtX7dpVt-0i_PxP-_fo7zoRgAX44Qa7_Y-U-nR-ebqI_gJ2Z7K5</recordid><startdate>201810</startdate><enddate>201810</enddate><creator>Li, Jianqi</creator><creator>Lin, Huimin</creator><creator>Liu, Tian</creator><creator>Zhang, Zhuwei</creator><creator>Prince, Martin R.</creator><creator>Gillen, Kelly</creator><creator>Yan, Xu</creator><creator>Song, Qi</creator><creator>Hua, Ting</creator><creator>Zhao, Xiance</creator><creator>Zhang, Miao</creator><creator>Zhao, Yu</creator><creator>Li, Gaiying</creator><creator>Tang, Guangyu</creator><creator>Yang, Guang</creator><creator>Brittenham, Gary M.</creator><creator>Wang, Yi</creator><general>Wiley Subscription Services, Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>201810</creationdate><title>Quantitative susceptibility mapping (QSM) minimizes interference from cellular pathology in R2 estimation of liver iron concentration</title><author>Li, Jianqi ; Lin, Huimin ; Liu, Tian ; Zhang, Zhuwei ; Prince, Martin R. ; Gillen, Kelly ; Yan, Xu ; Song, Qi ; Hua, Ting ; Zhao, Xiance ; Zhang, Miao ; Zhao, Yu ; Li, Gaiying ; Tang, Guangyu ; Yang, Guang ; Brittenham, Gary M. ; Wang, Yi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5149-56c98dee0136681201c4a4499ab1c9cf9e3a761dfea0228d8309917132d7f1a13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Abnormalities</topic><topic>cellularity</topic><topic>Collagen</topic><topic>Dependence</topic><topic>Disease control</topic><topic>Fibrosis</topic><topic>Field strength</topic><topic>Gadolinium</topic><topic>Interference</topic><topic>Iron</topic><topic>Lesions</topic><topic>Liver</topic><topic>Liver diseases</topic><topic>liver iron concentration</topic><topic>Magnetic resonance imaging</topic><topic>magnetic susceptibility</topic><topic>Mapping</topic><topic>Measurement methods</topic><topic>Medical imaging</topic><topic>Pathology</topic><topic>Patients</topic><topic>QSM</topic><topic>quantitative susceptibility mapping</topic><topic>Regression analysis</topic><topic>Statistical analysis</topic><topic>Statistical tests</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Jianqi</creatorcontrib><creatorcontrib>Lin, Huimin</creatorcontrib><creatorcontrib>Liu, Tian</creatorcontrib><creatorcontrib>Zhang, Zhuwei</creatorcontrib><creatorcontrib>Prince, Martin R.</creatorcontrib><creatorcontrib>Gillen, Kelly</creatorcontrib><creatorcontrib>Yan, Xu</creatorcontrib><creatorcontrib>Song, Qi</creatorcontrib><creatorcontrib>Hua, Ting</creatorcontrib><creatorcontrib>Zhao, Xiance</creatorcontrib><creatorcontrib>Zhang, Miao</creatorcontrib><creatorcontrib>Zhao, Yu</creatorcontrib><creatorcontrib>Li, Gaiying</creatorcontrib><creatorcontrib>Tang, Guangyu</creatorcontrib><creatorcontrib>Yang, Guang</creatorcontrib><creatorcontrib>Brittenham, Gary M.</creatorcontrib><creatorcontrib>Wang, Yi</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of magnetic resonance imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Jianqi</au><au>Lin, Huimin</au><au>Liu, Tian</au><au>Zhang, Zhuwei</au><au>Prince, Martin R.</au><au>Gillen, Kelly</au><au>Yan, Xu</au><au>Song, Qi</au><au>Hua, Ting</au><au>Zhao, Xiance</au><au>Zhang, Miao</au><au>Zhao, Yu</au><au>Li, Gaiying</au><au>Tang, Guangyu</au><au>Yang, Guang</au><au>Brittenham, Gary M.</au><au>Wang, Yi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantitative susceptibility mapping (QSM) minimizes interference from cellular pathology in R2 estimation of liver iron concentration</atitle><jtitle>Journal of magnetic resonance imaging</jtitle><addtitle>J Magn Reson Imaging</addtitle><date>2018-10</date><risdate>2018</risdate><volume>48</volume><issue>4</issue><spage>1069</spage><epage>1079</epage><pages>1069-1079</pages><issn>1053-1807</issn><eissn>1522-2586</eissn><abstract>Background
A challenge for R2 and R2* methods in measuring liver iron concentration (LIC) is that fibrosis, fat, and other hepatic cellular pathology contribute to R2 and R2* and interfere with LIC estimation.
Purpose
To examine the interfering effects of fibrosis, fat, and other lesions on R2* LIC estimation and to use quantitative susceptibility mapping (QSM) to reduce these distortions.
Study Type
Prospective.
Phantoms, Subjects
Water phantoms with various concentrations of gadolinium (Gd), collagen (Cl, modeling fibrosis), and fat; nine healthy controls with no known hepatic disease, nine patients with known or suspected hepatic iron overload, and nine patients with focal liver lesions.
Field Strength/Sequence
The phantoms and human subjects were imaged using a 3D multiecho gradient‐echo on clinical 1.5T and 3T MRI systems.
Assessment
QSM and R2* images were postprocessed from the same gradient‐echo data. Fat contributions to susceptibility and R2* were corrected in signal models for LIC estimation.
Statistical Tests
Polynomial regression analyses were performed to examine relations among susceptibility, R2* and true [Gd] and [Cl] in phantoms, and among susceptibility and R2* in patient livers.
Results
In phantoms, R2* had a strong nonlinear dependency on [Cl], [fat], and [Gd], while susceptibility was linearly dependent (R2 > 0.98). In patients, R2* was highly sensitive to liver pathological changes, including fat, fibrosis, and tumors, while QSM was relatively insensitive to these abnormalities (P = 0.015). With moderate iron overload, liver susceptibility and R2* were not linearly correlated over a common R2* range [0, 100] sec−1 (P = 0.35).
Data Conclusion
R2* estimation of LIC is prone to substantial nonlinear interference from fat, fibrosis, and other lesions. QSM processing of the same gradient echo MRI data can effectively minimize the effects of cellular pathology.
Level of Evidence: 1
Technical Efficacy: Stage 1
J. Magn. Reson. Imaging 2018;48:1069–1079.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>29566449</pmid><doi>10.1002/jmri.26019</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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| source | Wiley Free Content; Wiley Online Library Journals Frontfile Complete |
| subjects | Abnormalities cellularity Collagen Dependence Disease control Fibrosis Field strength Gadolinium Interference Iron Lesions Liver Liver diseases liver iron concentration Magnetic resonance imaging magnetic susceptibility Mapping Measurement methods Medical imaging Pathology Patients QSM quantitative susceptibility mapping Regression analysis Statistical analysis Statistical tests Tumors |
| title | Quantitative susceptibility mapping (QSM) minimizes interference from cellular pathology in R2 estimation of liver iron concentration |
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