3D PSIR MRI at 3 Tesla improves detection of spinal cord lesions in multiple sclerosis View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-10-26

AUTHORS

S. Mirafzal, A. Goujon, R. Deschamps, K. Zuber, J. C. Sadik, O. Gout, Augustin Lecler, J. Savatovsky

ABSTRACT

BackgroundSpinal imaging in multiple sclerosis remains challenging because of its small size and numerous artifacts.ObjectiveTo compare 3D Phase-Sensitive Inversion Recovery (PSIR) to a conventional dataset of 3D Short Tau Inversion Recovery (STIR) and T2-weighted imaging at 3 Tesla to detect multiple sclerosis spinal cord lesions.MethodsThis prospective single-center study was approved by a national research ethics board and included 54 patients (median age 44) enrolled from December 2016 to August 2018. Two neuroradiologists individually analyzed the two datasets separately and in random order. Discrepancies were resolved by consensus with a third neuroradiologist. The primary judgment criterion was the number of spinal cord lesions. Secondary judgment criteria included location of the lesions, reader-reported confidence and conspicuity assessed with the lesion-to-cord contrast ratio (LCCR).Results3D PSIR detected significantly more lesions than the conventional dataset (371 versus 173, respectively, p < 0.05). Seven patients had no detected lesion with the conventional dataset, whereas 3D PSIR detected at least one lesion. LCCR mean reader-reported confidence (p < 0.001) and inter-observer agreement were higher using 3D PSIR.Conclusions3D PSIR significantly improved overall spinal cord lesion detection in MS patients, with higher reader-reported confidence, higher lesion contrast, and higher inter-reader agreement. More... »

PAGES

406-414

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00415-019-09591-8

DOI

http://dx.doi.org/10.1007/s00415-019-09591-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1122118028

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/31655891


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

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/2008/1109", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Neurosciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Adult", 
        "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": "Prospective Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Spinal Cord Diseases", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Neuroradiology, Foundation Adolphe de Rothschild Hospital, Paris, France", 
          "id": "http://www.grid.ac/institutes/grid.414318.b", 
          "name": [
            "Department of Neuroradiology, Foundation Adolphe de Rothschild Hospital, Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mirafzal", 
        "givenName": "S.", 
        "id": "sg:person.014556430673.15", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014556430673.15"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Neuroradiology, Foundation Adolphe de Rothschild Hospital, Paris, France", 
          "id": "http://www.grid.ac/institutes/grid.414318.b", 
          "name": [
            "Department of Neuroradiology, Foundation Adolphe de Rothschild Hospital, Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Goujon", 
        "givenName": "A.", 
        "id": "sg:person.014064577443.00", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014064577443.00"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Neurology, Foundation Adolphe de Rothschild Hospital, Paris, France", 
          "id": "http://www.grid.ac/institutes/grid.414318.b", 
          "name": [
            "Department of Neurology, Foundation Adolphe de Rothschild Hospital, 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 Biostatistics, Foundation Adolphe de Rothschild Hospital, Paris, France", 
          "id": "http://www.grid.ac/institutes/grid.414318.b", 
          "name": [
            "Department of Biostatistics, Foundation Adolphe de Rothschild Hospital, Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zuber", 
        "givenName": "K.", 
        "id": "sg:person.010262335434.89", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010262335434.89"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Neuroradiology, Foundation Adolphe de Rothschild Hospital, Paris, France", 
          "id": "http://www.grid.ac/institutes/grid.414318.b", 
          "name": [
            "Department of Neuroradiology, Foundation Adolphe de Rothschild Hospital, 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, Foundation Adolphe de Rothschild Hospital, Paris, France", 
          "id": "http://www.grid.ac/institutes/grid.414318.b", 
          "name": [
            "Department of Neurology, Foundation Adolphe de Rothschild Hospital, 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": "Department of Neuroradiology, Foundation Adolphe de Rothschild Hospital, Paris, France", 
          "id": "http://www.grid.ac/institutes/grid.414318.b", 
          "name": [
            "Department of Neuroradiology, Foundation Adolphe de Rothschild Hospital, 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 Neuroradiology, Foundation Adolphe de Rothschild Hospital, Paris, France", 
          "id": "http://www.grid.ac/institutes/grid.414318.b", 
          "name": [
            "Department of Neuroradiology, Foundation Adolphe de Rothschild Hospital, 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/s00234-012-1118-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033310166", 
          "https://doi.org/10.1007/s00234-012-1118-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00062-015-0430-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042954657", 
          "https://doi.org/10.1007/s00062-015-0430-y"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-10-26", 
    "datePublishedReg": "2019-10-26", 
    "description": "BackgroundSpinal imaging in multiple sclerosis remains challenging because of its small size and numerous artifacts.ObjectiveTo compare 3D Phase-Sensitive Inversion Recovery (PSIR) to a conventional dataset of 3D Short Tau Inversion Recovery (STIR) and T2-weighted imaging at 3\u00a0Tesla to detect multiple sclerosis spinal cord lesions.MethodsThis prospective single-center study was approved by a national research ethics board and included 54 patients (median age 44) enrolled from December 2016 to August 2018. Two neuroradiologists individually analyzed the two datasets separately and in random order. Discrepancies were resolved by consensus with a third neuroradiologist. The primary judgment criterion was the number of spinal cord lesions. Secondary judgment criteria included location of the lesions, reader-reported confidence and conspicuity assessed with the lesion-to-cord contrast ratio (LCCR).Results3D PSIR detected significantly more lesions than the conventional dataset (371 versus 173, respectively, p\u2009<\u20090.05). Seven patients had no detected lesion with the conventional dataset, whereas 3D PSIR detected at least one lesion. LCCR mean reader-reported confidence (p\u2009<\u20090.001) and inter-observer agreement were higher using 3D PSIR.Conclusions3D PSIR significantly improved overall spinal cord lesion detection in MS patients, with higher reader-reported confidence, higher lesion contrast, and higher inter-reader agreement.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s00415-019-09591-8", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1014525", 
        "issn": [
          "0340-5354", 
          "1432-1459"
        ], 
        "name": "Journal of Neurology", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "267"
      }
    ], 
    "keywords": [
      "spinal cord lesions", 
      "cord lesions", 
      "short tau inversion recovery", 
      "phase-sensitive inversion recovery", 
      "multiple sclerosis", 
      "MethodsThis prospective single-center study", 
      "prospective single-center study", 
      "single-center study", 
      "multiple sclerosis spinal cord lesions", 
      "primary judgment criterion", 
      "high inter-reader agreement", 
      "inversion recovery", 
      "Secondary judgment criteria", 
      "T2-weighted imaging", 
      "inter-reader agreement", 
      "inter-observer agreement", 
      "MS patients", 
      "Research Ethics Board", 
      "more lesions", 
      "detected lesions", 
      "lesions", 
      "patients", 
      "third neuroradiologist", 
      "random order", 
      "Ethics Board", 
      "higher lesion contrast", 
      "sclerosis", 
      "lesion detection", 
      "neuroradiologists", 
      "lesion contrast", 
      "ObjectiveTo", 
      "MRI", 
      "criteria", 
      "recovery", 
      "judgment criteria", 
      "conspicuity", 
      "imaging", 
      "Conclusions3D", 
      "confidence", 
      "consensus", 
      "Tesla", 
      "study", 
      "detection", 
      "contrast", 
      "LCCR", 
      "number", 
      "ratio", 
      "discrepancy", 
      "small size", 
      "location", 
      "numerous artifacts", 
      "size", 
      "board", 
      "contrast ratio", 
      "conventional datasets", 
      "dataset", 
      "agreement", 
      "order", 
      "artifacts"
    ], 
    "name": "3D PSIR MRI at 3 Tesla improves detection of spinal cord lesions in multiple sclerosis", 
    "pagination": "406-414", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1122118028"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00415-019-09591-8"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "31655891"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00415-019-09591-8", 
      "https://app.dimensions.ai/details/publication/pub.1122118028"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-06-01T22:21", 
    "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_823.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s00415-019-09591-8"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

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/s00415-019-09591-8'

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/s00415-019-09591-8'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00415-019-09591-8'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00415-019-09591-8'


 

This table displays all metadata directly associated to this object as RDF triples.

226 TRIPLES      22 PREDICATES      98 URIs      87 LITERALS      17 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00415-019-09591-8 schema:about N0669ec756e464072a4282eb8313623dc
2 N1a3a56a7fb194b1891a3a0fdd1e63d39
3 N3f9ee786ec1b488e8456989b5448a4cb
4 N5e96ff04d10242518a5d4da3422e40e2
5 N76314f3dcd6241d1a4630a4a950e1f47
6 N9b3406c70143405b9a57dc1289a2d313
7 N9d3d5b7eef544f4aa6c009e83afeaa47
8 Nbe774892ef8b4d31bd0edf3b1a878d03
9 Ne931a26d4c964bce97e9585fcd476661
10 Nf814b7aae92b43048334438c047ad50f
11 anzsrc-for:11
12 anzsrc-for:1109
13 schema:author N676ec6f421fe4ec6bd2c82dcdce14faf
14 schema:citation sg:pub.10.1007/s00062-015-0430-y
15 sg:pub.10.1007/s00234-012-1118-5
16 sg:pub.10.1038/nrneurol.2015.106
17 schema:datePublished 2019-10-26
18 schema:datePublishedReg 2019-10-26
19 schema:description BackgroundSpinal imaging in multiple sclerosis remains challenging because of its small size and numerous artifacts.ObjectiveTo compare 3D Phase-Sensitive Inversion Recovery (PSIR) to a conventional dataset of 3D Short Tau Inversion Recovery (STIR) and T2-weighted imaging at 3 Tesla to detect multiple sclerosis spinal cord lesions.MethodsThis prospective single-center study was approved by a national research ethics board and included 54 patients (median age 44) enrolled from December 2016 to August 2018. Two neuroradiologists individually analyzed the two datasets separately and in random order. Discrepancies were resolved by consensus with a third neuroradiologist. The primary judgment criterion was the number of spinal cord lesions. Secondary judgment criteria included location of the lesions, reader-reported confidence and conspicuity assessed with the lesion-to-cord contrast ratio (LCCR).Results3D PSIR detected significantly more lesions than the conventional dataset (371 versus 173, respectively, p < 0.05). Seven patients had no detected lesion with the conventional dataset, whereas 3D PSIR detected at least one lesion. LCCR mean reader-reported confidence (p < 0.001) and inter-observer agreement were higher using 3D PSIR.Conclusions3D PSIR significantly improved overall spinal cord lesion detection in MS patients, with higher reader-reported confidence, higher lesion contrast, and higher inter-reader agreement.
20 schema:genre article
21 schema:inLanguage en
22 schema:isAccessibleForFree false
23 schema:isPartOf Nc24bf26bacbf4452891d9ce5bfb8bc77
24 Ne321e373a7d040b9a45fdf4263e50f8b
25 sg:journal.1014525
26 schema:keywords Conclusions3D
27 Ethics Board
28 LCCR
29 MRI
30 MS patients
31 MethodsThis prospective single-center study
32 ObjectiveTo
33 Research Ethics Board
34 Secondary judgment criteria
35 T2-weighted imaging
36 Tesla
37 agreement
38 artifacts
39 board
40 confidence
41 consensus
42 conspicuity
43 contrast
44 contrast ratio
45 conventional datasets
46 cord lesions
47 criteria
48 dataset
49 detected lesions
50 detection
51 discrepancy
52 high inter-reader agreement
53 higher lesion contrast
54 imaging
55 inter-observer agreement
56 inter-reader agreement
57 inversion recovery
58 judgment criteria
59 lesion contrast
60 lesion detection
61 lesions
62 location
63 more lesions
64 multiple sclerosis
65 multiple sclerosis spinal cord lesions
66 neuroradiologists
67 number
68 numerous artifacts
69 order
70 patients
71 phase-sensitive inversion recovery
72 primary judgment criterion
73 prospective single-center study
74 random order
75 ratio
76 recovery
77 sclerosis
78 short tau inversion recovery
79 single-center study
80 size
81 small size
82 spinal cord lesions
83 study
84 third neuroradiologist
85 schema:name 3D PSIR MRI at 3 Tesla improves detection of spinal cord lesions in multiple sclerosis
86 schema:pagination 406-414
87 schema:productId N1a1d1f98b416449baa407c76bca03918
88 N865e85299bdc4cc5be2f03b069f6b0a0
89 Nf6dd2b8ff14d4c32800569cb3abf024e
90 schema:sameAs https://app.dimensions.ai/details/publication/pub.1122118028
91 https://doi.org/10.1007/s00415-019-09591-8
92 schema:sdDatePublished 2022-06-01T22:21
93 schema:sdLicense https://scigraph.springernature.com/explorer/license/
94 schema:sdPublisher N515e658ea4074b3d8027ec6f4c54cc76
95 schema:url https://doi.org/10.1007/s00415-019-09591-8
96 sgo:license sg:explorer/license/
97 sgo:sdDataset articles
98 rdf:type schema:ScholarlyArticle
99 N0669ec756e464072a4282eb8313623dc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
100 schema:name Middle Aged
101 rdf:type schema:DefinedTerm
102 N1a1d1f98b416449baa407c76bca03918 schema:name dimensions_id
103 schema:value pub.1122118028
104 rdf:type schema:PropertyValue
105 N1a3a56a7fb194b1891a3a0fdd1e63d39 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
106 schema:name Female
107 rdf:type schema:DefinedTerm
108 N3f9ee786ec1b488e8456989b5448a4cb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
109 schema:name Magnetic Resonance Imaging
110 rdf:type schema:DefinedTerm
111 N515e658ea4074b3d8027ec6f4c54cc76 schema:name Springer Nature - SN SciGraph project
112 rdf:type schema:Organization
113 N5e96ff04d10242518a5d4da3422e40e2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
114 schema:name Humans
115 rdf:type schema:DefinedTerm
116 N676ec6f421fe4ec6bd2c82dcdce14faf rdf:first sg:person.014556430673.15
117 rdf:rest Nb9d4fa5e2b124a96ac5a518d367dbe46
118 N6a292612ba1f465b84f52260157b3111 rdf:first sg:person.010262335434.89
119 rdf:rest N91593af9e3fd4661aa597cf4708890f3
120 N76314f3dcd6241d1a4630a4a950e1f47 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
121 schema:name Male
122 rdf:type schema:DefinedTerm
123 N865e85299bdc4cc5be2f03b069f6b0a0 schema:name doi
124 schema:value 10.1007/s00415-019-09591-8
125 rdf:type schema:PropertyValue
126 N87b372e0a2c1463fbbc4aadb16a990c7 rdf:first sg:person.013202254465.75
127 rdf:rest Nffa556d888244c26b24eca6ca014f885
128 N8da106ac3e6f465e86051ecb849f9e92 rdf:first sg:person.01302231233.16
129 rdf:rest N87b372e0a2c1463fbbc4aadb16a990c7
130 N91593af9e3fd4661aa597cf4708890f3 rdf:first sg:person.0701117465.32
131 rdf:rest N8da106ac3e6f465e86051ecb849f9e92
132 N9b3406c70143405b9a57dc1289a2d313 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
133 schema:name Multiple Sclerosis
134 rdf:type schema:DefinedTerm
135 N9d3d5b7eef544f4aa6c009e83afeaa47 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
136 schema:name Neuroimaging
137 rdf:type schema:DefinedTerm
138 Nb1c96b9ba5a944bc949c71f3966ec12d rdf:first sg:person.0744372225.82
139 rdf:rest N6a292612ba1f465b84f52260157b3111
140 Nb9d4fa5e2b124a96ac5a518d367dbe46 rdf:first sg:person.014064577443.00
141 rdf:rest Nb1c96b9ba5a944bc949c71f3966ec12d
142 Nbe774892ef8b4d31bd0edf3b1a878d03 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
143 schema:name Spinal Cord Diseases
144 rdf:type schema:DefinedTerm
145 Nc24bf26bacbf4452891d9ce5bfb8bc77 schema:volumeNumber 267
146 rdf:type schema:PublicationVolume
147 Ne321e373a7d040b9a45fdf4263e50f8b schema:issueNumber 2
148 rdf:type schema:PublicationIssue
149 Ne931a26d4c964bce97e9585fcd476661 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
150 schema:name Adult
151 rdf:type schema:DefinedTerm
152 Nf6dd2b8ff14d4c32800569cb3abf024e schema:name pubmed_id
153 schema:value 31655891
154 rdf:type schema:PropertyValue
155 Nf814b7aae92b43048334438c047ad50f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
156 schema:name Prospective Studies
157 rdf:type schema:DefinedTerm
158 Nffa556d888244c26b24eca6ca014f885 rdf:first sg:person.01346477626.47
159 rdf:rest rdf:nil
160 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
161 schema:name Medical and Health Sciences
162 rdf:type schema:DefinedTerm
163 anzsrc-for:1109 schema:inDefinedTermSet anzsrc-for:
164 schema:name Neurosciences
165 rdf:type schema:DefinedTerm
166 sg:journal.1014525 schema:issn 0340-5354
167 1432-1459
168 schema:name Journal of Neurology
169 schema:publisher Springer Nature
170 rdf:type schema:Periodical
171 sg:person.010262335434.89 schema:affiliation grid-institutes:grid.414318.b
172 schema:familyName Zuber
173 schema:givenName K.
174 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010262335434.89
175 rdf:type schema:Person
176 sg:person.01302231233.16 schema:affiliation grid-institutes:grid.414318.b
177 schema:familyName Gout
178 schema:givenName O.
179 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01302231233.16
180 rdf:type schema:Person
181 sg:person.013202254465.75 schema:affiliation grid-institutes:grid.414318.b
182 schema:familyName Lecler
183 schema:givenName Augustin
184 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013202254465.75
185 rdf:type schema:Person
186 sg:person.01346477626.47 schema:affiliation grid-institutes:grid.414318.b
187 schema:familyName Savatovsky
188 schema:givenName J.
189 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01346477626.47
190 rdf:type schema:Person
191 sg:person.014064577443.00 schema:affiliation grid-institutes:grid.414318.b
192 schema:familyName Goujon
193 schema:givenName A.
194 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014064577443.00
195 rdf:type schema:Person
196 sg:person.014556430673.15 schema:affiliation grid-institutes:grid.414318.b
197 schema:familyName Mirafzal
198 schema:givenName S.
199 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014556430673.15
200 rdf:type schema:Person
201 sg:person.0701117465.32 schema:affiliation grid-institutes:grid.414318.b
202 schema:familyName Sadik
203 schema:givenName J. C.
204 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0701117465.32
205 rdf:type schema:Person
206 sg:person.0744372225.82 schema:affiliation grid-institutes:grid.414318.b
207 schema:familyName Deschamps
208 schema:givenName R.
209 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0744372225.82
210 rdf:type schema:Person
211 sg:pub.10.1007/s00062-015-0430-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1042954657
212 https://doi.org/10.1007/s00062-015-0430-y
213 rdf:type schema:CreativeWork
214 sg:pub.10.1007/s00234-012-1118-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033310166
215 https://doi.org/10.1007/s00234-012-1118-5
216 rdf:type schema:CreativeWork
217 sg:pub.10.1038/nrneurol.2015.106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012623025
218 https://doi.org/10.1038/nrneurol.2015.106
219 rdf:type schema:CreativeWork
220 grid-institutes:grid.414318.b schema:alternateName Department of Biostatistics, Foundation Adolphe de Rothschild Hospital, Paris, France
221 Department of Neurology, Foundation Adolphe de Rothschild Hospital, Paris, France
222 Department of Neuroradiology, Foundation Adolphe de Rothschild Hospital, Paris, France
223 schema:name Department of Biostatistics, Foundation Adolphe de Rothschild Hospital, Paris, France
224 Department of Neurology, Foundation Adolphe de Rothschild Hospital, Paris, France
225 Department of Neuroradiology, Foundation Adolphe de Rothschild Hospital, Paris, France
226 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...