Correlation of bone marrow cellularity and metabolic activity in healthy volunteers with simultaneous PET/MR imaging View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04

AUTHORS

Takeshi Fukuda, Mingqian Huang, Anuradha Janardhanan, Mark E. Schweitzer, Chuan Huang

ABSTRACT

OBJECTIVE: To evaluate the correlation between bone marrow cellularity (BMC) and metabolic activity in healthy subjects and to see whether yellow marrow is indeed metabolically quiescent. Because metabolic activity can be assumed to reflect vascularity, we assessed the relationship between regional metabolic activity and geographic frequency of metastases as noted in the literature. MATERIALS AND METHODS: Two hundred and twenty locations (ten in each side of the pelvis and proximal femur) were evaluated in 11 consecutive healthy volunteers with simultaneous PET/MR. BMC was calculated through precise water-fat fraction quantification with a 6-echo gradient echo. We analyzed correlations between cellularity and SUVr, age, and R2*. We also looked at the relation between our results and the reported prevalence of metastases. RESULTS: There was moderate but statistically significant correlation between BMC and metabolic activity (r = 0.636, p < 0.0001). Interestingly, the iliac and sacrum had higher metabolic activity relative to cellularity, whereas the femoral neck and lesser trochanter showed lower SUVr than other regions with the similar cellularity. The relatively lower metabolic status of the femoral neck conflicted with its reported high frequency of metastasis. Excluding regions with almost no remaining red marrow, cellularity showed inverse relationship with age (r = 0.476, p < 0.0001) and direct relationship with R2* (r = 0.532, p < 0.0010). CONCLUSIONS: Metabolic activity of bone marrow was largely dependent on BMC while yellow marrow seems metabolically quiescent. The discrepancy between the assumed vascularity as determined by metabolic activity and reported sites of metastasis suggested that the process of bone metastasis may not depend entirely on vascularity. More... »

PAGES

527-534

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00256-018-3058-6

DOI

http://dx.doi.org/10.1007/s00256-018-3058-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106835656

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30194581


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/2008/1103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Clinical Sciences", 
        "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": "Bone Marrow Cells", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Femur", 
        "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": "Image Processing, Computer-Assisted", 
        "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": "Multimodal Imaging", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Pelvic Bones", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Positron-Emission Tomography", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Prospective Studies", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Stony Brook University", 
          "id": "https://www.grid.ac/institutes/grid.36425.36", 
          "name": [
            "Department of Radiology, Stony Brook University, Stony Brook, NY, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fukuda", 
        "givenName": "Takeshi", 
        "id": "sg:person.010461523562.08", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010461523562.08"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Stony Brook University", 
          "id": "https://www.grid.ac/institutes/grid.36425.36", 
          "name": [
            "Department of Radiology, Stony Brook University, Stony Brook, NY, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Huang", 
        "givenName": "Mingqian", 
        "id": "sg:person.012054464562.83", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012054464562.83"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Stony Brook University", 
          "id": "https://www.grid.ac/institutes/grid.36425.36", 
          "name": [
            "Department of Radiology, Stony Brook University, Stony Brook, NY, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Janardhanan", 
        "givenName": "Anuradha", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Stony Brook University", 
          "id": "https://www.grid.ac/institutes/grid.36425.36", 
          "name": [
            "Department of Radiology, Stony Brook University, Stony Brook, NY, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Schweitzer", 
        "givenName": "Mark E.", 
        "id": "sg:person.0602127174.94", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0602127174.94"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Stony Brook University", 
          "id": "https://www.grid.ac/institutes/grid.36425.36", 
          "name": [
            "Department of Radiology, Stony Brook University, Stony Brook, NY, USA", 
            "Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Huang", 
        "givenName": "Chuan", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1002/mrm.22177", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004206453"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.22177", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004206453"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.mri.2014.03.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010171173"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.110.078949", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011744620"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jmri.20831", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012819348"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jbmr.1833", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016778901"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/jama.1977.03270500056025", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016931501"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.115.159715", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017131339"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-319-01748-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017663970", 
          "https://doi.org/10.1007/978-3-319-01748-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-319-01748-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017663970", 
          "https://doi.org/10.1007/978-3-319-01748-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.21522", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020238393"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1242/dev.106575", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020599743"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/bonekey.2015.29", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021860148", 
          "https://doi.org/10.1038/bonekey.2015.29"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bone.2011.06.016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022175192"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s002560050423", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022964934", 
          "https://doi.org/10.1007/s002560050423"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrendo.2010.227", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025867490", 
          "https://doi.org/10.1038/nrendo.2010.227"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00259-012-2141-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026730750", 
          "https://doi.org/10.1007/s00259-012-2141-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jmri.22757", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028257995"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3389/fendo.2016.00085", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033926636"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00256-007-0309-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036535407", 
          "https://doi.org/10.1007/s00256-007-0309-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00256-007-0309-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036535407", 
          "https://doi.org/10.1007/s00256-007-0309-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jmri.24865", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037829108"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jmri.21492", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037832968"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrc1098", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042664529", 
          "https://doi.org/10.1038/nrc1098"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrc1098", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042664529", 
          "https://doi.org/10.1038/nrc1098"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00330-014-3340-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042693936", 
          "https://doi.org/10.1007/s00330-014-3340-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/8756-3282(91)90059-r", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044730925"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/md.0000000000003892", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049061345"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/md.0000000000003892", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049061345"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jmri.1880070222", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052824069"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11307-007-0112-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052890062", 
          "https://doi.org/10.1007/s11307-007-0112-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1055/s-0029-1220879", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057192259"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2214/ajr.15.14968", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069304392"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/107327481201900204", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1078545739"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/107327481201900204", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1078545739"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1148/radiology.175.1.2315484", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1078647500"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1079204684", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1148/radiology.153.1.6089263", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1081561244"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1148/radiology.196.3.7644622", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1082447352"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1082487078", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1148/rg.2017160133", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084778564"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.18632/oncotarget.25070", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103381087"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-04", 
    "datePublishedReg": "2019-04-01", 
    "description": "OBJECTIVE: To evaluate the correlation between bone marrow cellularity (BMC) and metabolic activity in healthy subjects and to see whether yellow marrow is indeed metabolically quiescent. Because metabolic activity can be assumed to reflect vascularity, we assessed the relationship between regional metabolic activity and geographic frequency of metastases as noted in the literature.\nMATERIALS AND METHODS: Two hundred and twenty locations (ten in each side of the pelvis and proximal femur) were evaluated in 11 consecutive healthy volunteers with simultaneous PET/MR. BMC was calculated through precise water-fat fraction quantification with a 6-echo gradient echo. We analyzed correlations between cellularity and SUVr, age, and R2*. We also looked at the relation between our results and the reported prevalence of metastases.\nRESULTS: There was moderate but statistically significant correlation between BMC and metabolic activity (r\u2009=\u20090.636, p\u2009<\u20090.0001). Interestingly, the iliac and sacrum had higher metabolic activity relative to cellularity, whereas the femoral neck and lesser trochanter showed lower SUVr than other regions with the similar cellularity. The relatively lower metabolic status of the femoral neck conflicted with its reported high frequency of metastasis. Excluding regions with almost no remaining red marrow, cellularity showed inverse relationship with age (r\u2009=\u20090.476, p\u2009<\u20090.0001) and direct relationship with R2* (r\u2009=\u20090.532, p\u2009<\u20090.0010).\nCONCLUSIONS: Metabolic activity of bone marrow was largely dependent on BMC while yellow marrow seems metabolically quiescent. The discrepancy between the assumed vascularity as determined by metabolic activity and reported sites of metastasis suggested that the process of bone metastasis may not depend entirely on vascularity.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s00256-018-3058-6", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1086201", 
        "issn": [
          "0364-2348", 
          "1432-2161"
        ], 
        "name": "Skeletal Radiology", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "4", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "48"
      }
    ], 
    "name": "Correlation of bone marrow cellularity and metabolic activity in healthy volunteers with simultaneous PET/MR imaging", 
    "pagination": "527-534", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "6886263069e160bcf36be094e423e8950e4f74691cd980a62dcf6e70a6e5e099"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30194581"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "7701953"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00256-018-3058-6"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1106835656"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00256-018-3058-6", 
      "https://app.dimensions.ai/details/publication/pub.1106835656"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T09:51", 
    "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/v90/0000000347_0000000347/records_89789_00000003.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs00256-018-3058-6"
  }
]
 

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/s00256-018-3058-6'

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/s00256-018-3058-6'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00256-018-3058-6'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00256-018-3058-6'


 

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

263 TRIPLES      21 PREDICATES      78 URIs      34 LITERALS      22 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00256-018-3058-6 schema:about N0c2b122fe32e4d04a3ce21e55a2571d7
2 N1af91899728c41c18ff60612ef399420
3 N1eb1f83d1b1342c7a67f141311750db6
4 N37f9ef79e0784e1ba49a2fd6568c48c4
5 N3c777585edf4448d9d43446cb693197e
6 N4da8a19111c14d82849eb06266175db8
7 N6b497c6c7a634af8bec904a7c9a91c67
8 N70eb0b60220d481c9f521f0574aeb0b7
9 N7ca30b5fc87544f696fb63fdcdb50495
10 N934b0e338f224b63baba5c9fa37ba708
11 N93faeafe59ae4a5a9c4118312b0262e7
12 Nc39d990222e24c9e9edff10f094a176f
13 Nff46a7e493974e87a7c1f209900642f6
14 anzsrc-for:11
15 anzsrc-for:1103
16 schema:author N8d4b9f1b37b8445c8522e2f7ad81d6cf
17 schema:citation sg:pub.10.1007/978-3-319-01748-8
18 sg:pub.10.1007/s00256-007-0309-3
19 sg:pub.10.1007/s002560050423
20 sg:pub.10.1007/s00259-012-2141-9
21 sg:pub.10.1007/s00330-014-3340-5
22 sg:pub.10.1007/s11307-007-0112-5
23 sg:pub.10.1038/bonekey.2015.29
24 sg:pub.10.1038/nrc1098
25 sg:pub.10.1038/nrendo.2010.227
26 https://app.dimensions.ai/details/publication/pub.1079204684
27 https://app.dimensions.ai/details/publication/pub.1082487078
28 https://doi.org/10.1001/jama.1977.03270500056025
29 https://doi.org/10.1002/jbmr.1833
30 https://doi.org/10.1002/jmri.1880070222
31 https://doi.org/10.1002/jmri.20831
32 https://doi.org/10.1002/jmri.21492
33 https://doi.org/10.1002/jmri.22757
34 https://doi.org/10.1002/jmri.24865
35 https://doi.org/10.1002/mrm.21522
36 https://doi.org/10.1002/mrm.22177
37 https://doi.org/10.1016/8756-3282(91)90059-r
38 https://doi.org/10.1016/j.bone.2011.06.016
39 https://doi.org/10.1016/j.mri.2014.03.005
40 https://doi.org/10.1055/s-0029-1220879
41 https://doi.org/10.1097/md.0000000000003892
42 https://doi.org/10.1148/radiology.153.1.6089263
43 https://doi.org/10.1148/radiology.175.1.2315484
44 https://doi.org/10.1148/radiology.196.3.7644622
45 https://doi.org/10.1148/rg.2017160133
46 https://doi.org/10.1177/107327481201900204
47 https://doi.org/10.1242/dev.106575
48 https://doi.org/10.18632/oncotarget.25070
49 https://doi.org/10.2214/ajr.15.14968
50 https://doi.org/10.2967/jnumed.110.078949
51 https://doi.org/10.2967/jnumed.115.159715
52 https://doi.org/10.3389/fendo.2016.00085
53 schema:datePublished 2019-04
54 schema:datePublishedReg 2019-04-01
55 schema:description OBJECTIVE: To evaluate the correlation between bone marrow cellularity (BMC) and metabolic activity in healthy subjects and to see whether yellow marrow is indeed metabolically quiescent. Because metabolic activity can be assumed to reflect vascularity, we assessed the relationship between regional metabolic activity and geographic frequency of metastases as noted in the literature. MATERIALS AND METHODS: Two hundred and twenty locations (ten in each side of the pelvis and proximal femur) were evaluated in 11 consecutive healthy volunteers with simultaneous PET/MR. BMC was calculated through precise water-fat fraction quantification with a 6-echo gradient echo. We analyzed correlations between cellularity and SUVr, age, and R2*. We also looked at the relation between our results and the reported prevalence of metastases. RESULTS: There was moderate but statistically significant correlation between BMC and metabolic activity (r = 0.636, p < 0.0001). Interestingly, the iliac and sacrum had higher metabolic activity relative to cellularity, whereas the femoral neck and lesser trochanter showed lower SUVr than other regions with the similar cellularity. The relatively lower metabolic status of the femoral neck conflicted with its reported high frequency of metastasis. Excluding regions with almost no remaining red marrow, cellularity showed inverse relationship with age (r = 0.476, p < 0.0001) and direct relationship with R2* (r = 0.532, p < 0.0010). CONCLUSIONS: Metabolic activity of bone marrow was largely dependent on BMC while yellow marrow seems metabolically quiescent. The discrepancy between the assumed vascularity as determined by metabolic activity and reported sites of metastasis suggested that the process of bone metastasis may not depend entirely on vascularity.
56 schema:genre research_article
57 schema:inLanguage en
58 schema:isAccessibleForFree false
59 schema:isPartOf Na77b68f105ae453d97f2bb073d4d6f25
60 Nadb77d50bed5446480a91bd055f04f0f
61 sg:journal.1086201
62 schema:name Correlation of bone marrow cellularity and metabolic activity in healthy volunteers with simultaneous PET/MR imaging
63 schema:pagination 527-534
64 schema:productId N4d79d77afdac4bf2ab1ed367bfb3610a
65 N62b00c9511684f77a02496753b186ce3
66 N84c13373ed904b1ab28726752137c4d3
67 N9432d56597294e48992c8c7a5f2cc4e1
68 Nd7fbcbe18b244e62a9b254a3d4428a88
69 schema:sameAs https://app.dimensions.ai/details/publication/pub.1106835656
70 https://doi.org/10.1007/s00256-018-3058-6
71 schema:sdDatePublished 2019-04-11T09:51
72 schema:sdLicense https://scigraph.springernature.com/explorer/license/
73 schema:sdPublisher Nba44f5bfbd1a4f1da631780c57760dd1
74 schema:url https://link.springer.com/10.1007%2Fs00256-018-3058-6
75 sgo:license sg:explorer/license/
76 sgo:sdDataset articles
77 rdf:type schema:ScholarlyArticle
78 N0c2b122fe32e4d04a3ce21e55a2571d7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
79 schema:name Pelvic Bones
80 rdf:type schema:DefinedTerm
81 N1af91899728c41c18ff60612ef399420 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
82 schema:name Femur
83 rdf:type schema:DefinedTerm
84 N1eb1f83d1b1342c7a67f141311750db6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
85 schema:name Male
86 rdf:type schema:DefinedTerm
87 N37f9ef79e0784e1ba49a2fd6568c48c4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
88 schema:name Prospective Studies
89 rdf:type schema:DefinedTerm
90 N3c777585edf4448d9d43446cb693197e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
91 schema:name Multimodal Imaging
92 rdf:type schema:DefinedTerm
93 N4d79d77afdac4bf2ab1ed367bfb3610a schema:name dimensions_id
94 schema:value pub.1106835656
95 rdf:type schema:PropertyValue
96 N4da8a19111c14d82849eb06266175db8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
97 schema:name Magnetic Resonance Imaging
98 rdf:type schema:DefinedTerm
99 N62b00c9511684f77a02496753b186ce3 schema:name pubmed_id
100 schema:value 30194581
101 rdf:type schema:PropertyValue
102 N6b497c6c7a634af8bec904a7c9a91c67 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
103 schema:name Healthy Volunteers
104 rdf:type schema:DefinedTerm
105 N70eb0b60220d481c9f521f0574aeb0b7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
106 schema:name Female
107 rdf:type schema:DefinedTerm
108 N7ca30b5fc87544f696fb63fdcdb50495 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
109 schema:name Positron-Emission Tomography
110 rdf:type schema:DefinedTerm
111 N84ad9b5e4e4d49b7a597bdb64830052e rdf:first sg:person.012054464562.83
112 rdf:rest N97de195031fb4e268042e90a82d406f4
113 N84c13373ed904b1ab28726752137c4d3 schema:name readcube_id
114 schema:value 6886263069e160bcf36be094e423e8950e4f74691cd980a62dcf6e70a6e5e099
115 rdf:type schema:PropertyValue
116 N8d4b9f1b37b8445c8522e2f7ad81d6cf rdf:first sg:person.010461523562.08
117 rdf:rest N84ad9b5e4e4d49b7a597bdb64830052e
118 N934b0e338f224b63baba5c9fa37ba708 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
119 schema:name Adult
120 rdf:type schema:DefinedTerm
121 N93faeafe59ae4a5a9c4118312b0262e7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
122 schema:name Humans
123 rdf:type schema:DefinedTerm
124 N9432d56597294e48992c8c7a5f2cc4e1 schema:name doi
125 schema:value 10.1007/s00256-018-3058-6
126 rdf:type schema:PropertyValue
127 N97de195031fb4e268042e90a82d406f4 rdf:first Ndc3e8ec3539144d0b9b587dfea5d0f29
128 rdf:rest N9c3ea4d0958a434195ecf9a46d66558f
129 N9c3ea4d0958a434195ecf9a46d66558f rdf:first sg:person.0602127174.94
130 rdf:rest Ne067bf3ef49b45a082037700c45dc17a
131 Na77b68f105ae453d97f2bb073d4d6f25 schema:issueNumber 4
132 rdf:type schema:PublicationIssue
133 Nadb77d50bed5446480a91bd055f04f0f schema:volumeNumber 48
134 rdf:type schema:PublicationVolume
135 Nba44f5bfbd1a4f1da631780c57760dd1 schema:name Springer Nature - SN SciGraph project
136 rdf:type schema:Organization
137 Nc39d990222e24c9e9edff10f094a176f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
138 schema:name Bone Marrow Cells
139 rdf:type schema:DefinedTerm
140 Ncbff3764d6eb40c691b713eb5552652e schema:affiliation https://www.grid.ac/institutes/grid.36425.36
141 schema:familyName Huang
142 schema:givenName Chuan
143 rdf:type schema:Person
144 Nd7fbcbe18b244e62a9b254a3d4428a88 schema:name nlm_unique_id
145 schema:value 7701953
146 rdf:type schema:PropertyValue
147 Ndc3e8ec3539144d0b9b587dfea5d0f29 schema:affiliation https://www.grid.ac/institutes/grid.36425.36
148 schema:familyName Janardhanan
149 schema:givenName Anuradha
150 rdf:type schema:Person
151 Ne067bf3ef49b45a082037700c45dc17a rdf:first Ncbff3764d6eb40c691b713eb5552652e
152 rdf:rest rdf:nil
153 Nff46a7e493974e87a7c1f209900642f6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
154 schema:name Image Processing, Computer-Assisted
155 rdf:type schema:DefinedTerm
156 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
157 schema:name Medical and Health Sciences
158 rdf:type schema:DefinedTerm
159 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
160 schema:name Clinical Sciences
161 rdf:type schema:DefinedTerm
162 sg:journal.1086201 schema:issn 0364-2348
163 1432-2161
164 schema:name Skeletal Radiology
165 rdf:type schema:Periodical
166 sg:person.010461523562.08 schema:affiliation https://www.grid.ac/institutes/grid.36425.36
167 schema:familyName Fukuda
168 schema:givenName Takeshi
169 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010461523562.08
170 rdf:type schema:Person
171 sg:person.012054464562.83 schema:affiliation https://www.grid.ac/institutes/grid.36425.36
172 schema:familyName Huang
173 schema:givenName Mingqian
174 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012054464562.83
175 rdf:type schema:Person
176 sg:person.0602127174.94 schema:affiliation https://www.grid.ac/institutes/grid.36425.36
177 schema:familyName Schweitzer
178 schema:givenName Mark E.
179 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0602127174.94
180 rdf:type schema:Person
181 sg:pub.10.1007/978-3-319-01748-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017663970
182 https://doi.org/10.1007/978-3-319-01748-8
183 rdf:type schema:CreativeWork
184 sg:pub.10.1007/s00256-007-0309-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036535407
185 https://doi.org/10.1007/s00256-007-0309-3
186 rdf:type schema:CreativeWork
187 sg:pub.10.1007/s002560050423 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022964934
188 https://doi.org/10.1007/s002560050423
189 rdf:type schema:CreativeWork
190 sg:pub.10.1007/s00259-012-2141-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026730750
191 https://doi.org/10.1007/s00259-012-2141-9
192 rdf:type schema:CreativeWork
193 sg:pub.10.1007/s00330-014-3340-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042693936
194 https://doi.org/10.1007/s00330-014-3340-5
195 rdf:type schema:CreativeWork
196 sg:pub.10.1007/s11307-007-0112-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052890062
197 https://doi.org/10.1007/s11307-007-0112-5
198 rdf:type schema:CreativeWork
199 sg:pub.10.1038/bonekey.2015.29 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021860148
200 https://doi.org/10.1038/bonekey.2015.29
201 rdf:type schema:CreativeWork
202 sg:pub.10.1038/nrc1098 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042664529
203 https://doi.org/10.1038/nrc1098
204 rdf:type schema:CreativeWork
205 sg:pub.10.1038/nrendo.2010.227 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025867490
206 https://doi.org/10.1038/nrendo.2010.227
207 rdf:type schema:CreativeWork
208 https://app.dimensions.ai/details/publication/pub.1079204684 schema:CreativeWork
209 https://app.dimensions.ai/details/publication/pub.1082487078 schema:CreativeWork
210 https://doi.org/10.1001/jama.1977.03270500056025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016931501
211 rdf:type schema:CreativeWork
212 https://doi.org/10.1002/jbmr.1833 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016778901
213 rdf:type schema:CreativeWork
214 https://doi.org/10.1002/jmri.1880070222 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052824069
215 rdf:type schema:CreativeWork
216 https://doi.org/10.1002/jmri.20831 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012819348
217 rdf:type schema:CreativeWork
218 https://doi.org/10.1002/jmri.21492 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037832968
219 rdf:type schema:CreativeWork
220 https://doi.org/10.1002/jmri.22757 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028257995
221 rdf:type schema:CreativeWork
222 https://doi.org/10.1002/jmri.24865 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037829108
223 rdf:type schema:CreativeWork
224 https://doi.org/10.1002/mrm.21522 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020238393
225 rdf:type schema:CreativeWork
226 https://doi.org/10.1002/mrm.22177 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004206453
227 rdf:type schema:CreativeWork
228 https://doi.org/10.1016/8756-3282(91)90059-r schema:sameAs https://app.dimensions.ai/details/publication/pub.1044730925
229 rdf:type schema:CreativeWork
230 https://doi.org/10.1016/j.bone.2011.06.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022175192
231 rdf:type schema:CreativeWork
232 https://doi.org/10.1016/j.mri.2014.03.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010171173
233 rdf:type schema:CreativeWork
234 https://doi.org/10.1055/s-0029-1220879 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057192259
235 rdf:type schema:CreativeWork
236 https://doi.org/10.1097/md.0000000000003892 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049061345
237 rdf:type schema:CreativeWork
238 https://doi.org/10.1148/radiology.153.1.6089263 schema:sameAs https://app.dimensions.ai/details/publication/pub.1081561244
239 rdf:type schema:CreativeWork
240 https://doi.org/10.1148/radiology.175.1.2315484 schema:sameAs https://app.dimensions.ai/details/publication/pub.1078647500
241 rdf:type schema:CreativeWork
242 https://doi.org/10.1148/radiology.196.3.7644622 schema:sameAs https://app.dimensions.ai/details/publication/pub.1082447352
243 rdf:type schema:CreativeWork
244 https://doi.org/10.1148/rg.2017160133 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084778564
245 rdf:type schema:CreativeWork
246 https://doi.org/10.1177/107327481201900204 schema:sameAs https://app.dimensions.ai/details/publication/pub.1078545739
247 rdf:type schema:CreativeWork
248 https://doi.org/10.1242/dev.106575 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020599743
249 rdf:type schema:CreativeWork
250 https://doi.org/10.18632/oncotarget.25070 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103381087
251 rdf:type schema:CreativeWork
252 https://doi.org/10.2214/ajr.15.14968 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069304392
253 rdf:type schema:CreativeWork
254 https://doi.org/10.2967/jnumed.110.078949 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011744620
255 rdf:type schema:CreativeWork
256 https://doi.org/10.2967/jnumed.115.159715 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017131339
257 rdf:type schema:CreativeWork
258 https://doi.org/10.3389/fendo.2016.00085 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033926636
259 rdf:type schema:CreativeWork
260 https://www.grid.ac/institutes/grid.36425.36 schema:alternateName Stony Brook University
261 schema:name Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
262 Department of Radiology, Stony Brook University, Stony Brook, NY, USA
263 rdf:type schema:Organization
 




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


...