Progressive iron accumulation across multiple sclerosis phenotypes revealed by sparse classification of deep gray matter
Purpose To create an automated framework for localized analysis of deep gray matter (DGM) iron accumulation and demyelination using sparse classification by combining quantitative susceptibility (QS) and transverse relaxation rate (R2*) maps, for evaluation of DGM in multiple sclerosis (MS) phenotyp...
Gespeichert in:
| Veröffentlicht in: | Journal of magnetic resonance imaging 2017-11, Vol.46 (5), p.1464-1473 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1473 |
|---|---|
| container_issue | 5 |
| container_start_page | 1464 |
| container_title | Journal of magnetic resonance imaging |
| container_volume | 46 |
| creator | Elkady, Ahmed M. Cobzas, Dana Sun, Hongfu Blevins, Gregg Wilman, Alan H. |
| description | Purpose
To create an automated framework for localized analysis of deep gray matter (DGM) iron accumulation and demyelination using sparse classification by combining quantitative susceptibility (QS) and transverse relaxation rate (R2*) maps, for evaluation of DGM in multiple sclerosis (MS) phenotypes relative to healthy controls.
Materials and Methods
R2*/QS maps were computed using a 4.7T 10‐echo gradient echo acquisition from 16 clinically isolated syndrome (CIS), 41 relapsing‐remitting (RR), 40 secondary‐progressive (SP), 13 primary‐progressive (PP) MS patients, and 75 controls. Sparse classification for R2*/QS maps of segmented caudate nucleus (CN), putamen (PU), thalamus (TH), and globus pallidus (GP) structures produced localized maps of iron/myelin in MS patients relative to controls. Paired t‐tests, with age as a covariate, were used to test for statistical significance (P ≤ 0.05).
Results
In addition to DGM structures found significantly different in patients compared to controls using whole region analysis, singular sparse analysis found significant results in RRMS PU R2* (P = 0.03), TH R2* (P = 0.04), CN QS (P = 0.04); in SPMS CN R2* (P = 0.04), GP R2* (P = 0.05); and in PPMS CN R2* (P = 0.04), TH QS (P = 0.04). All sparse regions were found to conform to an iron accumulation pattern of changes in R2*/QS, while none conformed to demyelination. Intersection of sparse R2*/QS regions also resulted in RRMS CN R2* becoming significant, while RRMS R2* TH and PPMS QS TH becoming insignificant. Common iron‐associated volumes in MS patients and their effect size progressively increased with advanced phenotypes.
Conclusion
A localized technique for identifying sparse regions indicative of iron or myelin in the DGM was developed. Progressive iron accumulation with advanced MS phenotypes was demonstrated, as indicated by iron‐associated sparsity and effect size.
Level of Evidence: 1
Technical Efficacy: Stage 1
J. Magn. Reson. Imaging 2017;46:1464–1473. |
| doi_str_mv | 10.1002/jmri.25682 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1878183314</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1878183314</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4592-c34b25dc9867eae090055db997f08fe6cdc71c8b4d68dad83ed390707d1152a53</originalsourceid><addsrcrecordid>eNp9kUtv1TAQRi1ERUthww9AltggpJSxHSf2ElU8iloVIVhbjj0pvnJugp0U8u_r3hQWLFjNQ0dHo_kIecHgjAHwt7shhTMuG8UfkRMmOa-4VM3j0oMUFVPQHpOnOe8AQOtaPiHHXAlg0LQn5PeXNN4kzDncIg1p3FPr3DIs0c7hMKQxZ1rmOUwRaXYRyyZkOv3A_TivE2aa8BZtRE-7lebJpozURVuUfXCbZuypR5zoTbIrHew8Y3pGjnobMz5_qKfk-4f3384_VZfXHy_O311WrpaaV07UHZfeadW0aBE0gJS-07rtQfXYOO9a5lRX-0Z565VALzS00HpWPmGlOCWvN--Uxp8L5tkMITuM0e5xXLJhqlVMCcHqgr76B92NS9qX6wzTEgTwmkOh3mzU4TUJezOlMNi0GgbmPg9zn4c55FHglw_KpRvQ_0X_BFAAtgG_QsT1Pyrz-errxSa9AwLamAQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1950302420</pqid></control><display><type>article</type><title>Progressive iron accumulation across multiple sclerosis phenotypes revealed by sparse classification of deep gray matter</title><source>Wiley Free Content</source><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><creator>Elkady, Ahmed M. ; Cobzas, Dana ; Sun, Hongfu ; Blevins, Gregg ; Wilman, Alan H.</creator><creatorcontrib>Elkady, Ahmed M. ; Cobzas, Dana ; Sun, Hongfu ; Blevins, Gregg ; Wilman, Alan H.</creatorcontrib><description>Purpose
To create an automated framework for localized analysis of deep gray matter (DGM) iron accumulation and demyelination using sparse classification by combining quantitative susceptibility (QS) and transverse relaxation rate (R2*) maps, for evaluation of DGM in multiple sclerosis (MS) phenotypes relative to healthy controls.
Materials and Methods
R2*/QS maps were computed using a 4.7T 10‐echo gradient echo acquisition from 16 clinically isolated syndrome (CIS), 41 relapsing‐remitting (RR), 40 secondary‐progressive (SP), 13 primary‐progressive (PP) MS patients, and 75 controls. Sparse classification for R2*/QS maps of segmented caudate nucleus (CN), putamen (PU), thalamus (TH), and globus pallidus (GP) structures produced localized maps of iron/myelin in MS patients relative to controls. Paired t‐tests, with age as a covariate, were used to test for statistical significance (P ≤ 0.05).
Results
In addition to DGM structures found significantly different in patients compared to controls using whole region analysis, singular sparse analysis found significant results in RRMS PU R2* (P = 0.03), TH R2* (P = 0.04), CN QS (P = 0.04); in SPMS CN R2* (P = 0.04), GP R2* (P = 0.05); and in PPMS CN R2* (P = 0.04), TH QS (P = 0.04). All sparse regions were found to conform to an iron accumulation pattern of changes in R2*/QS, while none conformed to demyelination. Intersection of sparse R2*/QS regions also resulted in RRMS CN R2* becoming significant, while RRMS R2* TH and PPMS QS TH becoming insignificant. Common iron‐associated volumes in MS patients and their effect size progressively increased with advanced phenotypes.
Conclusion
A localized technique for identifying sparse regions indicative of iron or myelin in the DGM was developed. Progressive iron accumulation with advanced MS phenotypes was demonstrated, as indicated by iron‐associated sparsity and effect size.
Level of Evidence: 1
Technical Efficacy: Stage 1
J. Magn. Reson. Imaging 2017;46:1464–1473.</description><identifier>ISSN: 1053-1807</identifier><identifier>EISSN: 1522-2586</identifier><identifier>DOI: 10.1002/jmri.25682</identifier><identifier>PMID: 28301067</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Accumulation ; Adult ; Automatic Data Processing ; Brain - diagnostic imaging ; brain iron ; Brain Mapping ; Case-Control Studies ; Caudate nucleus ; Classification ; deep gray matter ; Demyelination ; Female ; Globus pallidus ; Gray Matter - diagnostic imaging ; Gray Matter - physiopathology ; Humans ; Image Interpretation, Computer-Assisted ; Image Processing, Computer-Assisted ; Iron ; Iron - chemistry ; Magnetic Resonance Imaging ; Male ; Middle Aged ; Multiple sclerosis ; Multiple Sclerosis - diagnostic imaging ; Multiple Sclerosis - physiopathology ; Myelin ; Nuclei ; Patients ; Phenotype ; Putamen ; quantitative susceptibility mapping ; sparse classification ; Substantia grisea ; Thalamus</subject><ispartof>Journal of magnetic resonance imaging, 2017-11, Vol.46 (5), p.1464-1473</ispartof><rights>2017 International Society for Magnetic Resonance in Medicine</rights><rights>2017 International Society for Magnetic Resonance in Medicine.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4592-c34b25dc9867eae090055db997f08fe6cdc71c8b4d68dad83ed390707d1152a53</citedby><cites>FETCH-LOGICAL-c4592-c34b25dc9867eae090055db997f08fe6cdc71c8b4d68dad83ed390707d1152a53</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.25682$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjmri.25682$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,1427,27901,27902,45550,45551,46384,46808</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28301067$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Elkady, Ahmed M.</creatorcontrib><creatorcontrib>Cobzas, Dana</creatorcontrib><creatorcontrib>Sun, Hongfu</creatorcontrib><creatorcontrib>Blevins, Gregg</creatorcontrib><creatorcontrib>Wilman, Alan H.</creatorcontrib><title>Progressive iron accumulation across multiple sclerosis phenotypes revealed by sparse classification of deep gray matter</title><title>Journal of magnetic resonance imaging</title><addtitle>J Magn Reson Imaging</addtitle><description>Purpose
To create an automated framework for localized analysis of deep gray matter (DGM) iron accumulation and demyelination using sparse classification by combining quantitative susceptibility (QS) and transverse relaxation rate (R2*) maps, for evaluation of DGM in multiple sclerosis (MS) phenotypes relative to healthy controls.
Materials and Methods
R2*/QS maps were computed using a 4.7T 10‐echo gradient echo acquisition from 16 clinically isolated syndrome (CIS), 41 relapsing‐remitting (RR), 40 secondary‐progressive (SP), 13 primary‐progressive (PP) MS patients, and 75 controls. Sparse classification for R2*/QS maps of segmented caudate nucleus (CN), putamen (PU), thalamus (TH), and globus pallidus (GP) structures produced localized maps of iron/myelin in MS patients relative to controls. Paired t‐tests, with age as a covariate, were used to test for statistical significance (P ≤ 0.05).
Results
In addition to DGM structures found significantly different in patients compared to controls using whole region analysis, singular sparse analysis found significant results in RRMS PU R2* (P = 0.03), TH R2* (P = 0.04), CN QS (P = 0.04); in SPMS CN R2* (P = 0.04), GP R2* (P = 0.05); and in PPMS CN R2* (P = 0.04), TH QS (P = 0.04). All sparse regions were found to conform to an iron accumulation pattern of changes in R2*/QS, while none conformed to demyelination. Intersection of sparse R2*/QS regions also resulted in RRMS CN R2* becoming significant, while RRMS R2* TH and PPMS QS TH becoming insignificant. Common iron‐associated volumes in MS patients and their effect size progressively increased with advanced phenotypes.
Conclusion
A localized technique for identifying sparse regions indicative of iron or myelin in the DGM was developed. Progressive iron accumulation with advanced MS phenotypes was demonstrated, as indicated by iron‐associated sparsity and effect size.
Level of Evidence: 1
Technical Efficacy: Stage 1
J. Magn. Reson. Imaging 2017;46:1464–1473.</description><subject>Accumulation</subject><subject>Adult</subject><subject>Automatic Data Processing</subject><subject>Brain - diagnostic imaging</subject><subject>brain iron</subject><subject>Brain Mapping</subject><subject>Case-Control Studies</subject><subject>Caudate nucleus</subject><subject>Classification</subject><subject>deep gray matter</subject><subject>Demyelination</subject><subject>Female</subject><subject>Globus pallidus</subject><subject>Gray Matter - diagnostic imaging</subject><subject>Gray Matter - physiopathology</subject><subject>Humans</subject><subject>Image Interpretation, Computer-Assisted</subject><subject>Image Processing, Computer-Assisted</subject><subject>Iron</subject><subject>Iron - chemistry</subject><subject>Magnetic Resonance Imaging</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Multiple sclerosis</subject><subject>Multiple Sclerosis - diagnostic imaging</subject><subject>Multiple Sclerosis - physiopathology</subject><subject>Myelin</subject><subject>Nuclei</subject><subject>Patients</subject><subject>Phenotype</subject><subject>Putamen</subject><subject>quantitative susceptibility mapping</subject><subject>sparse classification</subject><subject>Substantia grisea</subject><subject>Thalamus</subject><issn>1053-1807</issn><issn>1522-2586</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kUtv1TAQRi1ERUthww9AltggpJSxHSf2ElU8iloVIVhbjj0pvnJugp0U8u_r3hQWLFjNQ0dHo_kIecHgjAHwt7shhTMuG8UfkRMmOa-4VM3j0oMUFVPQHpOnOe8AQOtaPiHHXAlg0LQn5PeXNN4kzDncIg1p3FPr3DIs0c7hMKQxZ1rmOUwRaXYRyyZkOv3A_TivE2aa8BZtRE-7lebJpozURVuUfXCbZuypR5zoTbIrHew8Y3pGjnobMz5_qKfk-4f3384_VZfXHy_O311WrpaaV07UHZfeadW0aBE0gJS-07rtQfXYOO9a5lRX-0Z565VALzS00HpWPmGlOCWvN--Uxp8L5tkMITuM0e5xXLJhqlVMCcHqgr76B92NS9qX6wzTEgTwmkOh3mzU4TUJezOlMNi0GgbmPg9zn4c55FHglw_KpRvQ_0X_BFAAtgG_QsT1Pyrz-errxSa9AwLamAQ</recordid><startdate>201711</startdate><enddate>201711</enddate><creator>Elkady, Ahmed M.</creator><creator>Cobzas, Dana</creator><creator>Sun, Hongfu</creator><creator>Blevins, Gregg</creator><creator>Wilman, Alan H.</creator><general>Wiley Subscription Services, 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>7QO</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>201711</creationdate><title>Progressive iron accumulation across multiple sclerosis phenotypes revealed by sparse classification of deep gray matter</title><author>Elkady, Ahmed M. ; Cobzas, Dana ; Sun, Hongfu ; Blevins, Gregg ; Wilman, Alan H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4592-c34b25dc9867eae090055db997f08fe6cdc71c8b4d68dad83ed390707d1152a53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Accumulation</topic><topic>Adult</topic><topic>Automatic Data Processing</topic><topic>Brain - diagnostic imaging</topic><topic>brain iron</topic><topic>Brain Mapping</topic><topic>Case-Control Studies</topic><topic>Caudate nucleus</topic><topic>Classification</topic><topic>deep gray matter</topic><topic>Demyelination</topic><topic>Female</topic><topic>Globus pallidus</topic><topic>Gray Matter - diagnostic imaging</topic><topic>Gray Matter - physiopathology</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted</topic><topic>Image Processing, Computer-Assisted</topic><topic>Iron</topic><topic>Iron - chemistry</topic><topic>Magnetic Resonance Imaging</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Multiple sclerosis</topic><topic>Multiple Sclerosis - diagnostic imaging</topic><topic>Multiple Sclerosis - physiopathology</topic><topic>Myelin</topic><topic>Nuclei</topic><topic>Patients</topic><topic>Phenotype</topic><topic>Putamen</topic><topic>quantitative susceptibility mapping</topic><topic>sparse classification</topic><topic>Substantia grisea</topic><topic>Thalamus</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Elkady, Ahmed M.</creatorcontrib><creatorcontrib>Cobzas, Dana</creatorcontrib><creatorcontrib>Sun, Hongfu</creatorcontrib><creatorcontrib>Blevins, Gregg</creatorcontrib><creatorcontrib>Wilman, Alan H.</creatorcontrib><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>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><jtitle>Journal of magnetic resonance imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Elkady, Ahmed M.</au><au>Cobzas, Dana</au><au>Sun, Hongfu</au><au>Blevins, Gregg</au><au>Wilman, Alan H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Progressive iron accumulation across multiple sclerosis phenotypes revealed by sparse classification of deep gray matter</atitle><jtitle>Journal of magnetic resonance imaging</jtitle><addtitle>J Magn Reson Imaging</addtitle><date>2017-11</date><risdate>2017</risdate><volume>46</volume><issue>5</issue><spage>1464</spage><epage>1473</epage><pages>1464-1473</pages><issn>1053-1807</issn><eissn>1522-2586</eissn><abstract>Purpose
To create an automated framework for localized analysis of deep gray matter (DGM) iron accumulation and demyelination using sparse classification by combining quantitative susceptibility (QS) and transverse relaxation rate (R2*) maps, for evaluation of DGM in multiple sclerosis (MS) phenotypes relative to healthy controls.
Materials and Methods
R2*/QS maps were computed using a 4.7T 10‐echo gradient echo acquisition from 16 clinically isolated syndrome (CIS), 41 relapsing‐remitting (RR), 40 secondary‐progressive (SP), 13 primary‐progressive (PP) MS patients, and 75 controls. Sparse classification for R2*/QS maps of segmented caudate nucleus (CN), putamen (PU), thalamus (TH), and globus pallidus (GP) structures produced localized maps of iron/myelin in MS patients relative to controls. Paired t‐tests, with age as a covariate, were used to test for statistical significance (P ≤ 0.05).
Results
In addition to DGM structures found significantly different in patients compared to controls using whole region analysis, singular sparse analysis found significant results in RRMS PU R2* (P = 0.03), TH R2* (P = 0.04), CN QS (P = 0.04); in SPMS CN R2* (P = 0.04), GP R2* (P = 0.05); and in PPMS CN R2* (P = 0.04), TH QS (P = 0.04). All sparse regions were found to conform to an iron accumulation pattern of changes in R2*/QS, while none conformed to demyelination. Intersection of sparse R2*/QS regions also resulted in RRMS CN R2* becoming significant, while RRMS R2* TH and PPMS QS TH becoming insignificant. Common iron‐associated volumes in MS patients and their effect size progressively increased with advanced phenotypes.
Conclusion
A localized technique for identifying sparse regions indicative of iron or myelin in the DGM was developed. Progressive iron accumulation with advanced MS phenotypes was demonstrated, as indicated by iron‐associated sparsity and effect size.
Level of Evidence: 1
Technical Efficacy: Stage 1
J. Magn. Reson. Imaging 2017;46:1464–1473.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>28301067</pmid><doi>10.1002/jmri.25682</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1053-1807 |
| ispartof | Journal of magnetic resonance imaging, 2017-11, Vol.46 (5), p.1464-1473 |
| issn | 1053-1807 1522-2586 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1878183314 |
| source | Wiley Free Content; MEDLINE; Wiley Online Library Journals Frontfile Complete |
| subjects | Accumulation Adult Automatic Data Processing Brain - diagnostic imaging brain iron Brain Mapping Case-Control Studies Caudate nucleus Classification deep gray matter Demyelination Female Globus pallidus Gray Matter - diagnostic imaging Gray Matter - physiopathology Humans Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Iron Iron - chemistry Magnetic Resonance Imaging Male Middle Aged Multiple sclerosis Multiple Sclerosis - diagnostic imaging Multiple Sclerosis - physiopathology Myelin Nuclei Patients Phenotype Putamen quantitative susceptibility mapping sparse classification Substantia grisea Thalamus |
| title | Progressive iron accumulation across multiple sclerosis phenotypes revealed by sparse classification of deep gray matter |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-06T16%3A14%3A58IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Progressive%20iron%20accumulation%20across%20multiple%20sclerosis%20phenotypes%20revealed%20by%20sparse%20classification%20of%20deep%20gray%20matter&rft.jtitle=Journal%20of%20magnetic%20resonance%20imaging&rft.au=Elkady,%20Ahmed%20M.&rft.date=2017-11&rft.volume=46&rft.issue=5&rft.spage=1464&rft.epage=1473&rft.pages=1464-1473&rft.issn=1053-1807&rft.eissn=1522-2586&rft_id=info:doi/10.1002/jmri.25682&rft_dat=%3Cproquest_cross%3E1878183314%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1950302420&rft_id=info:pmid/28301067&rfr_iscdi=true |