Ontology type: schema:ScholarlyArticle Open Access: True
2017-10
AUTHORST. Campion, R. J. P. Smith, D. R. Altmann, G. C. Brito, B. P. Turner, J. Evanson, I. C. George, P. Sati, D. S. Reich, M. E. Miquel, K. Schmierer
ABSTRACTOBJECTIVE: To explore the potential of a post-processing technique combining FLAIR and T2* (FLAIR*) to distinguish between lesions caused by multiple sclerosis (MS) from cerebral small vessel disease (SVD) in a clinical setting. METHODS: FLAIR and T2* head datasets acquired at 3T of 25 people with relapsing MS (pwRMS) and ten with pwSVD were used. After post-processing, FLAIR* maps were used to determine the proportion of white matter lesions (WML) showing the 'vein in lesion' sign (VIL), a characteristic histopathological feature of MS plaques. Sensitivity and specificity of MS diagnosis were examined on the basis of >45% VIL+ and >60% VIL+ WML, and compared with current dissemination in space (DIS) MRI criteria. RESULTS: All pwRMS had >45% VIL+ WML (range 58-100%) whilst in pwSVD the proportion of VIL+ WML was significantly lower (0-64%; mean 32±20%). Sensitivity based on >45% VIL+ was 100% and specificity 80% whilst with >60% VIL+ as the criterion, sensitivity was 96% and specificity 90%. DIS criteria had 96% sensitivity and 40% specificity. CONCLUSION: FLAIR* enables VIL+ WML detection in a clinical setting, facilitating differentiation of MS from SVD based on brain MRI. KEY POINTS: • FLAIR* in a clinical setting allows visualization of veins in white matter lesions. • Significant proportions of MS lesions demonstrate a vein in lesion on MRI. • Microangiopathic lesions demonstrate a lower proportion of intralesional veins than MS lesions. • Intralesional vein-based criteria may complement current MRI criteria for MS diagnosis. More... »
PAGES4257-4263
http://scigraph.springernature.com/pub.10.1007/s00330-017-4822-z
DOIhttp://dx.doi.org/10.1007/s00330-017-4822-z
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1084819962
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/28409356
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1109",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Neurosciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Medical and Health Sciences",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Adult",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Aged",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Brain",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Brain Ischemia",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Cerebral Small Vessel Diseases",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Female",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Humans",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Magnetic Resonance Imaging",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Male",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Middle Aged",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Multiple Sclerosis",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Neuroimaging",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Sensitivity and Specificity",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Veins",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "White Matter",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Royal London Hospital",
"id": "https://www.grid.ac/institutes/grid.416041.6",
"name": [
"Blizard Institute (Neuroscience), Queen Mary University of London, London, UK",
"Barts Health NHS Trust, Emergency Care and Acute Medicine Clinical Academic Group Neuroscience, The Royal London Hospital, Whitechapel Road, London, UK"
],
"type": "Organization"
},
"familyName": "Campion",
"givenName": "T.",
"id": "sg:person.013457554135.52",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013457554135.52"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Gloucestershire Hospitals NHS Foundation Trust",
"id": "https://www.grid.ac/institutes/grid.434530.5",
"name": [
"Blizard Institute (Neuroscience), Queen Mary University of London, London, UK",
"Gloucestershire Hospitals NHS Trust, Cheltenham, UK"
],
"type": "Organization"
},
"familyName": "Smith",
"givenName": "R. J. P.",
"type": "Person"
},
{
"affiliation": {
"alternateName": "London School of Hygiene & Tropical Medicine",
"id": "https://www.grid.ac/institutes/grid.8991.9",
"name": [
"Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK"
],
"type": "Organization"
},
"familyName": "Altmann",
"givenName": "D. R.",
"id": "sg:person.010644625464.86",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010644625464.86"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Queen Mary University of London",
"id": "https://www.grid.ac/institutes/grid.4868.2",
"name": [
"Blizard Institute (Neuroscience), Queen Mary University of London, London, UK"
],
"type": "Organization"
},
"familyName": "Brito",
"givenName": "G. C.",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Royal London Hospital",
"id": "https://www.grid.ac/institutes/grid.416041.6",
"name": [
"Blizard Institute (Neuroscience), Queen Mary University of London, London, UK",
"Barts Health NHS Trust, Emergency Care and Acute Medicine Clinical Academic Group Neuroscience, The Royal London Hospital, Whitechapel Road, London, UK"
],
"type": "Organization"
},
"familyName": "Turner",
"givenName": "B. P.",
"id": "sg:person.0645041155.23",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0645041155.23"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Royal London Hospital",
"id": "https://www.grid.ac/institutes/grid.416041.6",
"name": [
"Barts Health NHS Trust, Emergency Care and Acute Medicine Clinical Academic Group Neuroscience, The Royal London Hospital, Whitechapel Road, London, UK"
],
"type": "Organization"
},
"familyName": "Evanson",
"givenName": "J.",
"id": "sg:person.01065052145.15",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01065052145.15"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Yale University",
"id": "https://www.grid.ac/institutes/grid.47100.32",
"name": [
"Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA",
"Department of Neurology, Yale School of Medicine, New Haven, CT, USA"
],
"type": "Organization"
},
"familyName": "George",
"givenName": "I. C.",
"id": "sg:person.0606452723.48",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0606452723.48"
],
"type": "Person"
},
{
"affiliation": {
"name": [
"Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA"
],
"type": "Organization"
},
"familyName": "Sati",
"givenName": "P.",
"id": "sg:person.01301014523.26",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01301014523.26"
],
"type": "Person"
},
{
"affiliation": {
"name": [
"Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA"
],
"type": "Organization"
},
"familyName": "Reich",
"givenName": "D. S.",
"id": "sg:person.013120176052.10",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013120176052.10"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Queen Mary University of London",
"id": "https://www.grid.ac/institutes/grid.4868.2",
"name": [
"Barts Health NHS Trust, Emergency Care and Acute Medicine Clinical Academic Group Neuroscience, The Royal London Hospital, Whitechapel Road, London, UK",
"William Harvey Research Institute (Cardiovascular Biomedical Research Unit), Queen Mary University of London, London, UK"
],
"type": "Organization"
},
"familyName": "Miquel",
"givenName": "M. E.",
"id": "sg:person.01232511460.37",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01232511460.37"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Royal London Hospital",
"id": "https://www.grid.ac/institutes/grid.416041.6",
"name": [
"Blizard Institute (Neuroscience), Queen Mary University of London, London, UK",
"Barts Health NHS Trust, Emergency Care and Acute Medicine Clinical Academic Group Neuroscience, The Royal London Hospital, Whitechapel Road, London, UK"
],
"type": "Organization"
},
"familyName": "Schmierer",
"givenName": "K.",
"id": "sg:person.0670402210.06",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0670402210.06"
],
"type": "Person"
}
],
"citation": [
{
"id": "https://doi.org/10.1148/radiol.12120208",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1000475867"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s0140-6736(07)61194-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003292376"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1352458515616700",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003717997"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1352458515616700",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003717997"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1352458515616700",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003717997"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1352458514525868",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1004072090"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1352458514525868",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1004072090"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1352458514525868",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1004072090"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/bpa.12460",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1009827622"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/nrneurol.2016.166",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1010157948",
"https://doi.org/10.1038/nrneurol.2016.166"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s1474-4422(06)70572-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1015933976"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1750-3639.2005.tb00523.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1016334962"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s1474-4422(14)70005-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022385151"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00330-013-3080-y",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022589751",
"https://doi.org/10.1007/s00330-013-3080-y"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00234-010-0736-z",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1024022356",
"https://doi.org/10.1007/s00234-010-0736-z"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1097/rli.0b013e3181b4c144",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027012244"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1097/rli.0b013e3181b4c144",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027012244"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1097/rli.0b013e3181b4c144",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027012244"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/acn3.273",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028293911"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s1474-4422(07)70176-x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1034068056"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1212/wnl.0000000000000837",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036241915"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1212/wnl.0000000000000837",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036241915"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3174/ajnr.a1461",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1037163707"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1352458515624975",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1037959210"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1352458515624975",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1037959210"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1352458515624975",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1037959210"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1352458510362441",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1041590891"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1352458510362441",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1041590891"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1352458510362441",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1041590891"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.msard.2015.04.006",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1043695250"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1097/rct.0000000000000233",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1045442226"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1097/rct.0000000000000233",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1045442226"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1001/jamaneurol.2013.1405",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1048697268"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/ana.22366",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1052372006"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00415-005-0934-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1053438904",
"https://doi.org/10.1007/s00415-005-0934-5"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00415-005-0934-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1053438904",
"https://doi.org/10.1007/s00415-005-0934-5"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.11613/bm.2012.031",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1063347969"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1212/wnl.0b013e31820b7630",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1064355922"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1212/wnl.0b013e31820b7630",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1064355922"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1212/wnl.0b013e31820b7630",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1064355922"
],
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1074659651",
"type": "CreativeWork"
}
],
"datePublished": "2017-10",
"datePublishedReg": "2017-10-01",
"description": "OBJECTIVE: To explore the potential of a post-processing technique combining FLAIR and T2* (FLAIR*) to distinguish between lesions caused by multiple sclerosis (MS) from cerebral small vessel disease (SVD) in a clinical setting.\nMETHODS: FLAIR and T2* head datasets acquired at 3T of 25 people with relapsing MS (pwRMS) and ten with pwSVD were used. After post-processing, FLAIR* maps were used to determine the proportion of white matter lesions (WML) showing the 'vein in lesion' sign (VIL), a characteristic histopathological feature of MS plaques. Sensitivity and specificity of MS diagnosis were examined on the basis of >45% VIL+ and >60% VIL+ WML, and compared with current dissemination in space (DIS) MRI criteria.\nRESULTS: All pwRMS had >45% VIL+ WML (range 58-100%) whilst in pwSVD the proportion of VIL+ WML was significantly lower (0-64%; mean 32\u00b120%). Sensitivity based on >45% VIL+ was 100% and specificity 80% whilst with >60% VIL+ as the criterion, sensitivity was 96% and specificity 90%. DIS criteria had 96% sensitivity and 40% specificity.\nCONCLUSION: FLAIR* enables VIL+ WML detection in a clinical setting, facilitating differentiation of MS from SVD based on brain MRI.\nKEY POINTS: \u2022 FLAIR* in a clinical setting allows visualization of veins in white matter lesions. \u2022 Significant proportions of MS lesions demonstrate a vein in lesion on MRI. \u2022 Microangiopathic lesions demonstrate a lower proportion of intralesional veins than MS lesions. \u2022 Intralesional vein-based criteria may complement current MRI criteria\u00a0for MS diagnosis.",
"genre": "research_article",
"id": "sg:pub.10.1007/s00330-017-4822-z",
"inLanguage": [
"en"
],
"isAccessibleForFree": true,
"isFundedItemOf": [
{
"id": "sg:grant.2726329",
"type": "MonetaryGrant"
}
],
"isPartOf": [
{
"id": "sg:journal.1289120",
"issn": [
"0938-7994",
"1432-1084"
],
"name": "European Radiology",
"type": "Periodical"
},
{
"issueNumber": "10",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "27"
}
],
"name": "FLAIR* to visualize veins in white matter lesions: A new tool for the diagnosis of multiple sclerosis?",
"pagination": "4257-4263",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"e516e258cf9a1c06dfd128288cbde7bd08bdafda580adad1b086d6c18dfc30d2"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"28409356"
]
},
{
"name": "nlm_unique_id",
"type": "PropertyValue",
"value": [
"9114774"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s00330-017-4822-z"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1084819962"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s00330-017-4822-z",
"https://app.dimensions.ai/details/publication/pub.1084819962"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T10:21",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000348_0000000348/records_54338_00000001.jsonl",
"type": "ScholarlyArticle",
"url": "https://link.springer.com/10.1007%2Fs00330-017-4822-z"
}
]Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00330-017-4822-z'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00330-017-4822-z'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00330-017-4822-z'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00330-017-4822-z'
This table displays all metadata directly associated to this object as RDF triples.
301 TRIPLES
21 PREDICATES
70 URIs
36 LITERALS
24 BLANK NODES