Visualization of the lenticulostriate arteries at 3T using black-blood T1-weighted intracranial vessel wall imaging: comparison with 7T TOF-MRA View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-08-27

AUTHORS

Zihao Zhang, Zhaoyang Fan, Qingle Kong, Jiayu Xiao, Fang Wu, Jing An, Qi Yang, Debiao Li, Yan Zhuo

ABSTRACT

ObjectivesThe objective of this study was to explore the feasibility of using intracranial T1-weighted vessel wall imaging (VWI) to visualize the lenticulostriate arteries (LSAs) at 3T.Material and methodsThirteen healthy volunteers were examined with VWI at 3T and TOF-MRA at 7T during the same day. On the vascular skeletons obtained by manual tracing, the number of stems and branches of LSAs were counted. On the most prominent branch in every hemisphere, the contrast-to-noise ratio (CNR), the full length and the local length (5-15 mm above MCAs) were measured and compared between the two methods. Nine stroke patients with intracranial artery stenosis were also recruited into the study. The branches of LSAs were compared between the symptomatic and asymptomatic side.ResultsThe extracted vascular trees were in good agreement between 7T TOF-MRA and 3T VWI. The two acquisitions showed similar numbers of the LSA stems. The number of branches revealed by 3T VWI was slightly lower than 7T TOF. The full lengths were slightly lower by VWI at 3T (p = 0.011, ICC = 0.917). The measured local lengths (5-15 mm from MCAs) showed high coherence between VWI and TOF-MRA (p = 0.098, ICC = 0.970). In stroke patients, 12 plaques were identified on MCA segments, and nine plaques were located on the symptomatic side. The average numbers of LSA visualized by 3T VWI were 4.3±1.3 on the symptomatic side and 5.0±1.1 on the asymptomatic side.Conclusion3T VWI is capable of depicting LSAs, particularly the stems and the proximal segments, with comparable image quality to that of 7T TOF-MRA.Key Points• T1-weighted intracranial VWI at 3T allows for black-blood MR angiography of lenticulostriate artery.• 3T intracranial VWI depicts the stems and proximal segments of the lenticulostriate arteries comparable to 7T TOF-MRA.• It is feasible to assess both large vessel wall lesions and lenticulostriate vasculopathy in one scan. More... »

PAGES

1452-1459

References to SciGraph publications

  • 2015-07-09. Numerical investigation of fluid–particle interactions for embolic stroke in THEORETICAL AND COMPUTATIONAL FLUID DYNAMICS
  • 2011-11-27. Image-based modeling of hemodynamics in coronary artery aneurysms caused by Kawasaki disease in BIOMECHANICS AND MODELING IN MECHANOBIOLOGY
  • 2016-12-08. SimVascular: An Open Source Pipeline for Cardiovascular Simulation in ANNALS OF BIOMEDICAL ENGINEERING
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s00330-018-5701-y

    DOI

    http://dx.doi.org/10.1007/s00330-018-5701-y

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1106365992

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30151642


    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/2008/1102", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Cardiorespiratory Medicine and Haematology", 
            "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": "Cerebral Arteries", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Female", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Healthy Volunteers", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Humans", 
            "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 Angiography", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Male", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Stroke", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Young Adult", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "The Innovation Center of Excellence on Brain Science, Chinese Academy of Sciences, Beijing, China", 
              "id": "http://www.grid.ac/institutes/grid.9227.e", 
              "name": [
                "State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China", 
                "The Innovation Center of Excellence on Brain Science, Chinese Academy of Sciences, Beijing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Zhang", 
            "givenName": "Zihao", 
            "id": "sg:person.0642646445.46", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0642646445.46"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Medicine, University of California, Los Angeles, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.19006.3e", 
              "name": [
                "Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 90048, Los Angeles, CA, USA", 
                "Department of Medicine, University of California, Los Angeles, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Fan", 
            "givenName": "Zhaoyang", 
            "id": "sg:person.01136172260.58", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01136172260.58"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Chinese Academy of Sciences, Beijing, China", 
              "id": "http://www.grid.ac/institutes/grid.410726.6", 
              "name": [
                "State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China", 
                "University of Chinese Academy of Sciences, Beijing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kong", 
            "givenName": "Qingle", 
            "id": "sg:person.015117501454.78", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015117501454.78"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Radiology, Chaoyang Hospital, Capital Medical University, Beijing, China", 
              "id": "http://www.grid.ac/institutes/grid.24696.3f", 
              "name": [
                "Department of Radiology, Chaoyang Hospital, Capital Medical University, Beijing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Xiao", 
            "givenName": "Jiayu", 
            "id": "sg:person.010005244404.21", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010005244404.21"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China", 
              "id": "http://www.grid.ac/institutes/grid.413259.8", 
              "name": [
                "Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wu", 
            "givenName": "Fang", 
            "id": "sg:person.07417576007.44", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07417576007.44"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China", 
              "id": "http://www.grid.ac/institutes/None", 
              "name": [
                "Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "An", 
            "givenName": "Jing", 
            "id": "sg:person.01066175422.29", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01066175422.29"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China", 
              "id": "http://www.grid.ac/institutes/grid.413259.8", 
              "name": [
                "Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 90048, Los Angeles, CA, USA", 
                "Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Yang", 
            "givenName": "Qi", 
            "id": "sg:person.01353064311.62", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01353064311.62"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Departments of Medicine and Bioengineering, University of California, Los Angeles, CA, United States", 
              "id": "http://www.grid.ac/institutes/grid.19006.3e", 
              "name": [
                "Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 90048, Los Angeles, CA, USA", 
                "Departments of Medicine and Bioengineering, University of California, Los Angeles, CA, United States"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Li", 
            "givenName": "Debiao", 
            "id": "sg:person.01152021525.33", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01152021525.33"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "The Innovation Center of Excellence on Brain Science, Chinese Academy of Sciences, Beijing, China", 
              "id": "http://www.grid.ac/institutes/grid.9227.e", 
              "name": [
                "State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China", 
                "The Innovation Center of Excellence on Brain Science, Chinese Academy of Sciences, Beijing, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Zhuo", 
            "givenName": "Yan", 
            "id": "sg:person.0703144631.96", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0703144631.96"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/s10439-016-1762-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045649343", 
              "https://doi.org/10.1007/s10439-016-1762-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00162-015-0359-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016236144", 
              "https://doi.org/10.1007/s00162-015-0359-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10237-011-0361-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041098439", 
              "https://doi.org/10.1007/s10237-011-0361-8"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2018-08-27", 
        "datePublishedReg": "2018-08-27", 
        "description": "ObjectivesThe objective of this study was to explore the feasibility of using intracranial T1-weighted vessel wall imaging (VWI) to visualize the lenticulostriate arteries (LSAs) at 3T.Material and methodsThirteen healthy volunteers were examined with VWI at 3T and TOF-MRA at 7T during the same day. On the vascular skeletons obtained by manual tracing, the number of stems and branches of LSAs were counted. On the most prominent branch in every hemisphere, the contrast-to-noise ratio (CNR), the full length and the local length (5-15 mm above MCAs) were measured and compared between the two methods. Nine stroke patients with intracranial artery stenosis were also recruited into the study. The branches of LSAs were compared between the symptomatic and asymptomatic side.ResultsThe extracted vascular trees were in good agreement between 7T TOF-MRA and 3T VWI. The two acquisitions showed similar numbers of the LSA stems. The number of\u00a0branches revealed by 3T VWI was slightly lower than 7T TOF. The full lengths were slightly lower by VWI at 3T (p = 0.011, ICC = 0.917). The measured local lengths (5-15 mm from MCAs) showed high coherence between VWI and TOF-MRA (p = 0.098, ICC = 0.970). In stroke patients, 12 plaques were identified on MCA segments, and nine plaques were located on the symptomatic side. The average numbers of LSA visualized by 3T VWI were 4.3\u00b11.3 on the symptomatic side and 5.0\u00b11.1 on the asymptomatic side.Conclusion3T VWI is capable of depicting LSAs, particularly the stems and the proximal segments, with comparable image quality to that of 7T TOF-MRA.Key Points\u2022 T1-weighted intracranial VWI at 3T allows for black-blood MR angiography of lenticulostriate artery.\u2022 3T intracranial VWI depicts the stems and proximal segments of the lenticulostriate arteries comparable to 7T TOF-MRA.\u2022 It is feasible to assess both large vessel wall lesions and lenticulostriate vasculopathy in one scan.", 
        "genre": "article", 
        "id": "sg:pub.10.1007/s00330-018-5701-y", 
        "isAccessibleForFree": false, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.2542522", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.100067747", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.8374654", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1289120", 
            "issn": [
              "0938-7994", 
              "1432-1084"
            ], 
            "name": "European Radiology", 
            "publisher": "Springer Nature", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "3", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "29"
          }
        ], 
        "keywords": [
          "vessel wall imaging", 
          "T TOF-MRA", 
          "lenticulostriate arteries", 
          "symptomatic side", 
          "stroke patients", 
          "asymptomatic side", 
          "TOF-MRA", 
          "proximal segment", 
          "intracranial artery stenosis", 
          "intracranial vessel wall imaging", 
          "MethodsThirteen healthy volunteers", 
          "vessel wall lesions", 
          "MCA segments", 
          "lenticulostriate vasculopathy", 
          "artery stenosis", 
          "healthy volunteers", 
          "wall lesions", 
          "artery", 
          "ObjectivesThe objective", 
          "MR angiography", 
          "same day", 
          "wall imaging", 
          "patients", 
          "vascular tree", 
          "plaques", 
          "similar number", 
          "full length", 
          "manual tracing", 
          "imaging", 
          "vasculopathy", 
          "stenosis", 
          "angiography", 
          "lesions", 
          "average number", 
          "comparable image quality", 
          "volunteers", 
          "ResultsThe", 
          "scans", 
          "study", 
          "days", 
          "vascular skeleton", 
          "segments", 
          "prominent branch", 
          "number", 
          "side", 
          "tracing", 
          "image quality", 
          "length", 
          "hemisphere", 
          "branches", 
          "contrast", 
          "stem", 
          "objective", 
          "quality", 
          "black\u2010blood MR angiography", 
          "feasibility", 
          "TOF", 
          "ratio", 
          "comparison", 
          "visualization", 
          "high coherence", 
          "acquisition", 
          "skeleton", 
          "method", 
          "coherence", 
          "noise ratio", 
          "agreement", 
          "trees", 
          "local length", 
          "good agreement", 
          "number of stems"
        ], 
        "name": "Visualization of the lenticulostriate arteries at 3T using black-blood T1-weighted intracranial vessel wall imaging: comparison with 7T TOF-MRA", 
        "pagination": "1452-1459", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1106365992"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s00330-018-5701-y"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "30151642"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s00330-018-5701-y", 
          "https://app.dimensions.ai/details/publication/pub.1106365992"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2022-11-24T21:03", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-springernature-scigraph/baseset/20221124/entities/gbq_results/article/article_762.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://doi.org/10.1007/s00330-018-5701-y"
      }
    ]
     

    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/s00330-018-5701-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/s00330-018-5701-y'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00330-018-5701-y'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00330-018-5701-y'


     

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

    271 TRIPLES      21 PREDICATES      110 URIs      99 LITERALS      18 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s00330-018-5701-y schema:about N055031ceb4544143a13a954344ede093
    2 N236a2403c1c34c9795a560fa19a1d10e
    3 N317e4248f1fb4ce0af6f688be122328b
    4 N3a4b199c163b4f2e891fccd9d50ffd01
    5 N4669194c802d452d80ef3291ce920539
    6 N63832bc3d0084b0ea6fcbd679fe0627d
    7 N87573ee68ff24080a7e6840d095a7e1a
    8 N98d4564c43964b90a8972ba96a83bcba
    9 N9e9b04357c3248c682610dbdeccefd00
    10 Nb8f88be5f3da48f38edf5fe5d33bdfcb
    11 Nec93b7afa28c48239ec55ec45881fbd7
    12 anzsrc-for:11
    13 anzsrc-for:1102
    14 schema:author Ncedcb88e9c574d4a8eab9bfb127f1fab
    15 schema:citation sg:pub.10.1007/s00162-015-0359-4
    16 sg:pub.10.1007/s10237-011-0361-8
    17 sg:pub.10.1007/s10439-016-1762-8
    18 schema:datePublished 2018-08-27
    19 schema:datePublishedReg 2018-08-27
    20 schema:description ObjectivesThe objective of this study was to explore the feasibility of using intracranial T1-weighted vessel wall imaging (VWI) to visualize the lenticulostriate arteries (LSAs) at 3T.Material and methodsThirteen healthy volunteers were examined with VWI at 3T and TOF-MRA at 7T during the same day. On the vascular skeletons obtained by manual tracing, the number of stems and branches of LSAs were counted. On the most prominent branch in every hemisphere, the contrast-to-noise ratio (CNR), the full length and the local length (5-15 mm above MCAs) were measured and compared between the two methods. Nine stroke patients with intracranial artery stenosis were also recruited into the study. The branches of LSAs were compared between the symptomatic and asymptomatic side.ResultsThe extracted vascular trees were in good agreement between 7T TOF-MRA and 3T VWI. The two acquisitions showed similar numbers of the LSA stems. The number of branches revealed by 3T VWI was slightly lower than 7T TOF. The full lengths were slightly lower by VWI at 3T (p = 0.011, ICC = 0.917). The measured local lengths (5-15 mm from MCAs) showed high coherence between VWI and TOF-MRA (p = 0.098, ICC = 0.970). In stroke patients, 12 plaques were identified on MCA segments, and nine plaques were located on the symptomatic side. The average numbers of LSA visualized by 3T VWI were 4.3±1.3 on the symptomatic side and 5.0±1.1 on the asymptomatic side.Conclusion3T VWI is capable of depicting LSAs, particularly the stems and the proximal segments, with comparable image quality to that of 7T TOF-MRA.Key Points• T1-weighted intracranial VWI at 3T allows for black-blood MR angiography of lenticulostriate artery.• 3T intracranial VWI depicts the stems and proximal segments of the lenticulostriate arteries comparable to 7T TOF-MRA.• It is feasible to assess both large vessel wall lesions and lenticulostriate vasculopathy in one scan.
    21 schema:genre article
    22 schema:isAccessibleForFree false
    23 schema:isPartOf Nb9a708c629d74b40aeab3c0c577bb38e
    24 Ne207012e4ad348b9bbafbe96d29823a6
    25 sg:journal.1289120
    26 schema:keywords MCA segments
    27 MR angiography
    28 MethodsThirteen healthy volunteers
    29 ObjectivesThe objective
    30 ResultsThe
    31 T TOF-MRA
    32 TOF
    33 TOF-MRA
    34 acquisition
    35 agreement
    36 angiography
    37 artery
    38 artery stenosis
    39 asymptomatic side
    40 average number
    41 black‐blood MR angiography
    42 branches
    43 coherence
    44 comparable image quality
    45 comparison
    46 contrast
    47 days
    48 feasibility
    49 full length
    50 good agreement
    51 healthy volunteers
    52 hemisphere
    53 high coherence
    54 image quality
    55 imaging
    56 intracranial artery stenosis
    57 intracranial vessel wall imaging
    58 length
    59 lenticulostriate arteries
    60 lenticulostriate vasculopathy
    61 lesions
    62 local length
    63 manual tracing
    64 method
    65 noise ratio
    66 number
    67 number of stems
    68 objective
    69 patients
    70 plaques
    71 prominent branch
    72 proximal segment
    73 quality
    74 ratio
    75 same day
    76 scans
    77 segments
    78 side
    79 similar number
    80 skeleton
    81 stem
    82 stenosis
    83 stroke patients
    84 study
    85 symptomatic side
    86 tracing
    87 trees
    88 vascular skeleton
    89 vascular tree
    90 vasculopathy
    91 vessel wall imaging
    92 vessel wall lesions
    93 visualization
    94 volunteers
    95 wall imaging
    96 wall lesions
    97 schema:name Visualization of the lenticulostriate arteries at 3T using black-blood T1-weighted intracranial vessel wall imaging: comparison with 7T TOF-MRA
    98 schema:pagination 1452-1459
    99 schema:productId N6a679b1e575f45128221f7bc8e82fb1b
    100 Nb2dc2357d6704e4792cfb982c0e73570
    101 Nb698cd21903543ff8e5623ecb8604385
    102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1106365992
    103 https://doi.org/10.1007/s00330-018-5701-y
    104 schema:sdDatePublished 2022-11-24T21:03
    105 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    106 schema:sdPublisher N867c3c18ef254355ad87fd33657d684d
    107 schema:url https://doi.org/10.1007/s00330-018-5701-y
    108 sgo:license sg:explorer/license/
    109 sgo:sdDataset articles
    110 rdf:type schema:ScholarlyArticle
    111 N055031ceb4544143a13a954344ede093 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    112 schema:name Healthy Volunteers
    113 rdf:type schema:DefinedTerm
    114 N236a2403c1c34c9795a560fa19a1d10e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    115 schema:name Adult
    116 rdf:type schema:DefinedTerm
    117 N317e4248f1fb4ce0af6f688be122328b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    118 schema:name Humans
    119 rdf:type schema:DefinedTerm
    120 N3a4b199c163b4f2e891fccd9d50ffd01 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    121 schema:name Stroke
    122 rdf:type schema:DefinedTerm
    123 N4669194c802d452d80ef3291ce920539 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    124 schema:name Male
    125 rdf:type schema:DefinedTerm
    126 N5c178ae83a754407b09bfc63040f7c51 rdf:first sg:person.010005244404.21
    127 rdf:rest Nf0f9200f1bba413688cb03afab09f5d1
    128 N63832bc3d0084b0ea6fcbd679fe0627d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    129 schema:name Imaging, Three-Dimensional
    130 rdf:type schema:DefinedTerm
    131 N6a679b1e575f45128221f7bc8e82fb1b schema:name dimensions_id
    132 schema:value pub.1106365992
    133 rdf:type schema:PropertyValue
    134 N867c3c18ef254355ad87fd33657d684d schema:name Springer Nature - SN SciGraph project
    135 rdf:type schema:Organization
    136 N87573ee68ff24080a7e6840d095a7e1a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    137 schema:name Young Adult
    138 rdf:type schema:DefinedTerm
    139 N98d4564c43964b90a8972ba96a83bcba schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    140 schema:name Cerebral Arteries
    141 rdf:type schema:DefinedTerm
    142 N9970d9b15cda4b4d9e2caa29bf2f44ee rdf:first sg:person.01136172260.58
    143 rdf:rest Nda7e4193eb5b408884edac2914742a4f
    144 N998ef89d7a8d4bd0a48df4781d68a35f rdf:first sg:person.0703144631.96
    145 rdf:rest rdf:nil
    146 N9e9b04357c3248c682610dbdeccefd00 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    147 schema:name Brain
    148 rdf:type schema:DefinedTerm
    149 Nb2dc2357d6704e4792cfb982c0e73570 schema:name doi
    150 schema:value 10.1007/s00330-018-5701-y
    151 rdf:type schema:PropertyValue
    152 Nb698cd21903543ff8e5623ecb8604385 schema:name pubmed_id
    153 schema:value 30151642
    154 rdf:type schema:PropertyValue
    155 Nb8f88be5f3da48f38edf5fe5d33bdfcb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    156 schema:name Female
    157 rdf:type schema:DefinedTerm
    158 Nb9a708c629d74b40aeab3c0c577bb38e schema:volumeNumber 29
    159 rdf:type schema:PublicationVolume
    160 Ncedcb88e9c574d4a8eab9bfb127f1fab rdf:first sg:person.0642646445.46
    161 rdf:rest N9970d9b15cda4b4d9e2caa29bf2f44ee
    162 Nda7e4193eb5b408884edac2914742a4f rdf:first sg:person.015117501454.78
    163 rdf:rest N5c178ae83a754407b09bfc63040f7c51
    164 Ne207012e4ad348b9bbafbe96d29823a6 schema:issueNumber 3
    165 rdf:type schema:PublicationIssue
    166 Ne6c87ed102124fb7adf60f4a6b503331 rdf:first sg:person.01353064311.62
    167 rdf:rest Nf65675535ba94513bed06b0a007a740b
    168 Nec93b7afa28c48239ec55ec45881fbd7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    169 schema:name Magnetic Resonance Angiography
    170 rdf:type schema:DefinedTerm
    171 Nf0f9200f1bba413688cb03afab09f5d1 rdf:first sg:person.07417576007.44
    172 rdf:rest Nf3a8a21189ec4ca3afb3020891250d5e
    173 Nf3a8a21189ec4ca3afb3020891250d5e rdf:first sg:person.01066175422.29
    174 rdf:rest Ne6c87ed102124fb7adf60f4a6b503331
    175 Nf65675535ba94513bed06b0a007a740b rdf:first sg:person.01152021525.33
    176 rdf:rest N998ef89d7a8d4bd0a48df4781d68a35f
    177 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
    178 schema:name Medical and Health Sciences
    179 rdf:type schema:DefinedTerm
    180 anzsrc-for:1102 schema:inDefinedTermSet anzsrc-for:
    181 schema:name Cardiorespiratory Medicine and Haematology
    182 rdf:type schema:DefinedTerm
    183 sg:grant.100067747 http://pending.schema.org/fundedItem sg:pub.10.1007/s00330-018-5701-y
    184 rdf:type schema:MonetaryGrant
    185 sg:grant.2542522 http://pending.schema.org/fundedItem sg:pub.10.1007/s00330-018-5701-y
    186 rdf:type schema:MonetaryGrant
    187 sg:grant.8374654 http://pending.schema.org/fundedItem sg:pub.10.1007/s00330-018-5701-y
    188 rdf:type schema:MonetaryGrant
    189 sg:journal.1289120 schema:issn 0938-7994
    190 1432-1084
    191 schema:name European Radiology
    192 schema:publisher Springer Nature
    193 rdf:type schema:Periodical
    194 sg:person.010005244404.21 schema:affiliation grid-institutes:grid.24696.3f
    195 schema:familyName Xiao
    196 schema:givenName Jiayu
    197 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010005244404.21
    198 rdf:type schema:Person
    199 sg:person.01066175422.29 schema:affiliation grid-institutes:None
    200 schema:familyName An
    201 schema:givenName Jing
    202 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01066175422.29
    203 rdf:type schema:Person
    204 sg:person.01136172260.58 schema:affiliation grid-institutes:grid.19006.3e
    205 schema:familyName Fan
    206 schema:givenName Zhaoyang
    207 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01136172260.58
    208 rdf:type schema:Person
    209 sg:person.01152021525.33 schema:affiliation grid-institutes:grid.19006.3e
    210 schema:familyName Li
    211 schema:givenName Debiao
    212 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01152021525.33
    213 rdf:type schema:Person
    214 sg:person.01353064311.62 schema:affiliation grid-institutes:grid.413259.8
    215 schema:familyName Yang
    216 schema:givenName Qi
    217 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01353064311.62
    218 rdf:type schema:Person
    219 sg:person.015117501454.78 schema:affiliation grid-institutes:grid.410726.6
    220 schema:familyName Kong
    221 schema:givenName Qingle
    222 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015117501454.78
    223 rdf:type schema:Person
    224 sg:person.0642646445.46 schema:affiliation grid-institutes:grid.9227.e
    225 schema:familyName Zhang
    226 schema:givenName Zihao
    227 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0642646445.46
    228 rdf:type schema:Person
    229 sg:person.0703144631.96 schema:affiliation grid-institutes:grid.9227.e
    230 schema:familyName Zhuo
    231 schema:givenName Yan
    232 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0703144631.96
    233 rdf:type schema:Person
    234 sg:person.07417576007.44 schema:affiliation grid-institutes:grid.413259.8
    235 schema:familyName Wu
    236 schema:givenName Fang
    237 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07417576007.44
    238 rdf:type schema:Person
    239 sg:pub.10.1007/s00162-015-0359-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016236144
    240 https://doi.org/10.1007/s00162-015-0359-4
    241 rdf:type schema:CreativeWork
    242 sg:pub.10.1007/s10237-011-0361-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041098439
    243 https://doi.org/10.1007/s10237-011-0361-8
    244 rdf:type schema:CreativeWork
    245 sg:pub.10.1007/s10439-016-1762-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045649343
    246 https://doi.org/10.1007/s10439-016-1762-8
    247 rdf:type schema:CreativeWork
    248 grid-institutes:None schema:alternateName Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
    249 schema:name Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
    250 rdf:type schema:Organization
    251 grid-institutes:grid.19006.3e schema:alternateName Department of Medicine, University of California, Los Angeles, CA, USA
    252 Departments of Medicine and Bioengineering, University of California, Los Angeles, CA, United States
    253 schema:name Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 90048, Los Angeles, CA, USA
    254 Department of Medicine, University of California, Los Angeles, CA, USA
    255 Departments of Medicine and Bioengineering, University of California, Los Angeles, CA, United States
    256 rdf:type schema:Organization
    257 grid-institutes:grid.24696.3f schema:alternateName Department of Radiology, Chaoyang Hospital, Capital Medical University, Beijing, China
    258 schema:name Department of Radiology, Chaoyang Hospital, Capital Medical University, Beijing, China
    259 rdf:type schema:Organization
    260 grid-institutes:grid.410726.6 schema:alternateName University of Chinese Academy of Sciences, Beijing, China
    261 schema:name State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
    262 University of Chinese Academy of Sciences, Beijing, China
    263 rdf:type schema:Organization
    264 grid-institutes:grid.413259.8 schema:alternateName Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
    265 schema:name Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 90048, Los Angeles, CA, USA
    266 Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
    267 rdf:type schema:Organization
    268 grid-institutes:grid.9227.e schema:alternateName The Innovation Center of Excellence on Brain Science, Chinese Academy of Sciences, Beijing, China
    269 schema:name State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
    270 The Innovation Center of Excellence on Brain Science, Chinese Academy of Sciences, Beijing, China
    271 rdf:type schema:Organization
     




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


    ...