Ontology type: schema:ScholarlyArticle
2019-08-01
AUTHORSAugustin Lecler, C. Bouzad, R. Deschamps, F. Maizeroi, J. C. Sadik, A. Gueguen, O. Gout, H. Picard, J. Savatovsky
ABSTRACTBackgroundTo assess the diagnostic value of three 3D FLAIR sequences with differing repetition-times (TR) at 3-Tesla when detecting multiple sclerosis (MS) lesions.MethodsIn this prospective study, approved by the institutional review board, 27 patients with confirmed MS were prospectively included. One radiologist performed manual segmentations of all high-signal intensity lesions using three 3D FLAIR data sets with different TR of 4800 ms (“FLAIR4800”), 8000 ms (“FLAIR8000”) and 10,000 ms (“FLAIR10,000”) and two radiologists double-checked it. The main judgment criterion was the overall number of lesions; secondary objectives were the assessment of lesion location, as well as measuring contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR). A non-parametric Wilcoxon’s test was used to compare the differing FLAIR.ResultsThe FLAIR8000 and FLAIR10,000 detected significantly more overall lesions per patient as compared with the FLAIR4800 [116.1 (± 61.7) (p = 0.02) and 115.8 (± 56.3) (p = 0.03) versus 99.2 (± 66.9), respectively]. The FLAIR8000 and FLAIR10,000 detected four and eight times more cortical or juxta-cortical lesions per patient as compared with FLAIR4800 [1.6 (± 2.2) (p = 0.001) and 4.1 (± 5.9) (p = 6 × 10–5) versus 0.4 (± 1.1), respectively]. CNR was significantly correlated to the TR value. It was significantly higher with FLAIR10,000 than it was with FLAIR8000 and FLAIR4800 [16.3 (± 3.5) versus 15 (± 2.4) (p = 0.01) and 12 (± 2.2) (p = 2 × 10–6), respectively]ConclusionAn optimized 3D FLAIR with a long TR significantly improved both overall lesion detection and CNR in MS patients as compared to a 3D FLAIR with factory settings. More... »
PAGES2786-2795
http://scigraph.springernature.com/pub.10.1007/s00415-019-09490-y
DOIhttp://dx.doi.org/10.1007/s00415-019-09490-y
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1120022070
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/31372735
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/2008/11",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Medical and Health Sciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1117",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Public Health and Health Services",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Adult",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Brain",
"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": "Image Interpretation, Computer-Assisted",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Imaging, Three-Dimensional",
"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": "Prospective Studies",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Department of Radiology, Fondation Ophtalmologique Adolphe de Rothschild, 25 rue Manin, 75019, Paris, France",
"id": "http://www.grid.ac/institutes/grid.417888.a",
"name": [
"Department of Radiology, Fondation Ophtalmologique Adolphe de Rothschild, 25 rue Manin, 75019, Paris, France"
],
"type": "Organization"
},
"familyName": "Lecler",
"givenName": "Augustin",
"id": "sg:person.013202254465.75",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013202254465.75"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Radiology, B\u00e9gin Military Teaching Hospital, Saint Mand\u00e9, France",
"id": "http://www.grid.ac/institutes/grid.414007.6",
"name": [
"Department of Radiology, Fondation Ophtalmologique Adolphe de Rothschild, 25 rue Manin, 75019, Paris, France",
"Department of Radiology, B\u00e9gin Military Teaching Hospital, Saint Mand\u00e9, France"
],
"type": "Organization"
},
"familyName": "Bouzad",
"givenName": "C.",
"id": "sg:person.0753664420.21",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0753664420.21"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Neurology, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France",
"id": "http://www.grid.ac/institutes/grid.417888.a",
"name": [
"Department of Neurology, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France"
],
"type": "Organization"
},
"familyName": "Deschamps",
"givenName": "R.",
"id": "sg:person.0744372225.82",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0744372225.82"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Radiology, Fondation Ophtalmologique Adolphe de Rothschild, 25 rue Manin, 75019, Paris, France",
"id": "http://www.grid.ac/institutes/grid.417888.a",
"name": [
"Department of Radiology, Fondation Ophtalmologique Adolphe de Rothschild, 25 rue Manin, 75019, Paris, France"
],
"type": "Organization"
},
"familyName": "Maizeroi",
"givenName": "F.",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Radiology, Fondation Ophtalmologique Adolphe de Rothschild, 25 rue Manin, 75019, Paris, France",
"id": "http://www.grid.ac/institutes/grid.417888.a",
"name": [
"Department of Radiology, Fondation Ophtalmologique Adolphe de Rothschild, 25 rue Manin, 75019, Paris, France"
],
"type": "Organization"
},
"familyName": "Sadik",
"givenName": "J. C.",
"id": "sg:person.0701117465.32",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0701117465.32"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Neurology, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France",
"id": "http://www.grid.ac/institutes/grid.417888.a",
"name": [
"Department of Neurology, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France"
],
"type": "Organization"
},
"familyName": "Gueguen",
"givenName": "A.",
"id": "sg:person.01102346504.85",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01102346504.85"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Neurology, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France",
"id": "http://www.grid.ac/institutes/grid.417888.a",
"name": [
"Department of Neurology, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France"
],
"type": "Organization"
},
"familyName": "Gout",
"givenName": "O.",
"id": "sg:person.01302231233.16",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01302231233.16"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Clinical Research Unit, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France",
"id": "http://www.grid.ac/institutes/grid.417888.a",
"name": [
"Clinical Research Unit, Fondation Ophtalmologique Adolphe de Rothschild, Paris, France"
],
"type": "Organization"
},
"familyName": "Picard",
"givenName": "H.",
"id": "sg:person.014513766571.96",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014513766571.96"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Radiology, Fondation Ophtalmologique Adolphe de Rothschild, 25 rue Manin, 75019, Paris, France",
"id": "http://www.grid.ac/institutes/grid.417888.a",
"name": [
"Department of Radiology, Fondation Ophtalmologique Adolphe de Rothschild, 25 rue Manin, 75019, Paris, France"
],
"type": "Organization"
},
"familyName": "Savatovsky",
"givenName": "J.",
"id": "sg:person.01346477626.47",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01346477626.47"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1038/nrneurol.2015.106",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1012623025",
"https://doi.org/10.1038/nrneurol.2015.106"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00415-015-7724-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1009394731",
"https://doi.org/10.1007/s00415-015-7724-5"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00330-005-0107-z",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1049539714",
"https://doi.org/10.1007/s00330-005-0107-z"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00330-008-1009-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1000475540",
"https://doi.org/10.1007/s00330-008-1009-7"
],
"type": "CreativeWork"
}
],
"datePublished": "2019-08-01",
"datePublishedReg": "2019-08-01",
"description": "BackgroundTo assess the diagnostic value of three 3D FLAIR sequences with differing repetition-times (TR) at 3-Tesla when detecting multiple sclerosis (MS) lesions.MethodsIn this prospective study, approved by the institutional review board, 27 patients with confirmed MS were prospectively included. One radiologist performed manual segmentations of all high-signal intensity lesions using three 3D FLAIR data sets with different TR of 4800\u00a0ms (\u201cFLAIR4800\u201d), 8000\u00a0ms (\u201cFLAIR8000\u201d) and 10,000\u00a0ms (\u201cFLAIR10,000\u201d) and two radiologists double-checked it. The main judgment criterion was the overall number of lesions; secondary objectives were the assessment of lesion location, as well as measuring contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR). A non-parametric Wilcoxon\u2019s test was used to compare the differing FLAIR.ResultsThe FLAIR8000 and FLAIR10,000 detected significantly more overall lesions per patient as compared with the FLAIR4800 [116.1 (\u00b1\u200961.7) (p\u2009=\u20090.02) and 115.8 (\u00b1\u200956.3) (p\u2009=\u20090.03) versus 99.2 (\u00b1\u200966.9), respectively]. The FLAIR8000 and FLAIR10,000 detected four and eight times more cortical or juxta-cortical lesions per patient as compared with FLAIR4800 [1.6 (\u00b1\u20092.2) (p\u2009=\u20090.001) and 4.1 (\u00b1\u20095.9) (p\u2009=\u20096\u00a0\u00d7\u00a010\u20135) versus 0.4 (\u00b1\u20091.1), respectively]. CNR was significantly correlated to the TR value. It was significantly higher with FLAIR10,000 than it was with FLAIR8000 and FLAIR4800 [16.3 (\u00b1\u20093.5) versus 15 (\u00b1\u20092.4) (p\u2009=\u20090.01) and 12 (\u00b1\u20092.2) (p\u2009=\u20092\u00a0\u00d7\u00a010\u20136), respectively]ConclusionAn optimized 3D FLAIR with a long TR significantly improved both overall lesion detection and CNR in MS patients as compared to a 3D FLAIR with factory settings.",
"genre": "article",
"id": "sg:pub.10.1007/s00415-019-09490-y",
"inLanguage": "en",
"isAccessibleForFree": false,
"isPartOf": [
{
"id": "sg:journal.1014525",
"issn": [
"0340-5354",
"1432-1459"
],
"name": "Journal of Neurology",
"publisher": "Springer Nature",
"type": "Periodical"
},
{
"issueNumber": "11",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "266"
}
],
"keywords": [
"high signal intensity lesions",
"juxta-cortical lesions",
"main judgment criterion",
"multiple sclerosis lesions",
"institutional review board",
"non-parametric Wilcoxon test",
"MS patients",
"prospective study",
"intensity lesions",
"lesion location",
"overall lesions",
"MS lesions",
"sclerosis lesions",
"patients",
"diagnostic value",
"lesions",
"secondary objective",
"overall lesion detection",
"FLAIR sequences",
"review board",
"Wilcoxon test",
"lesion detection",
"long TR",
"radiologists",
"FLAIR",
"overall number",
"BackgroundTo",
"MethodsIn",
"setting",
"ms",
"different TRs",
"CNR",
"test",
"manual segmentation",
"assessment",
"TR values",
"criteria",
"TR",
"study",
"judgment criteria",
"ratio",
"contrast",
"objective",
"MS",
"values",
"detection",
"number",
"factory settings",
"time",
"results",
"location",
"board",
"sequence",
"signals",
"noise ratio",
"data sets",
"precise results",
"set",
"segmentation"
],
"name": "Optimizing 3D FLAIR to detect MS lesions: pushing past factory settings for precise results",
"pagination": "2786-2795",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1120022070"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s00415-019-09490-y"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"31372735"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s00415-019-09490-y",
"https://app.dimensions.ai/details/publication/pub.1120022070"
],
"sdDataset": "articles",
"sdDatePublished": "2022-06-01T22:20",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-springernature-scigraph/baseset/20220601/entities/gbq_results/article/article_800.jsonl",
"type": "ScholarlyArticle",
"url": "https://doi.org/10.1007/s00415-019-09490-y"
}
]
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/s00415-019-09490-y'
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/s00415-019-09490-y'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00415-019-09490-y'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00415-019-09490-y'
This table displays all metadata directly associated to this object as RDF triples.
248 TRIPLES
22 PREDICATES
101 URIs
89 LITERALS
19 BLANK NODES