Feasibility of data-driven cardiac respiratory motion correction of myocardial perfusion CZT SPECT: A pilot study View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-10

AUTHORS

Doumit Daou, Rémy Sabbah, Carlos Coaguila, Hatem Boulahdour

ABSTRACT

BACKGROUND: We developed a data-driven respiratory motion (RM) correction method (REGAT program) for multiple-pinhole detector CZT SPECT. We verified its clinical feasibility with myocardial perfusion imaging (MPI) and studied its impact on image characteristics. METHODS: This retrospective study included 18 patients having stress/rest 99mTc-Tetrofosmin MPI SPECT. List mode was acquired on CZT SPECT and processed with REGAT. REGAT generates reconstructed RM-gated volumes that are summed either without realignment (NR-SPECT) or after realignment (R-SPECT). For both stress and rest, we calculated the maximal RM in the 3 axis, and image characteristics of both R-SPECT and NR-SPECT: minimum left ventricular (LV) cavity counts (LV-Min), maximum LV myocardial counts (LV-Max), LV contrast, and FWHM of both anterior (FWHM-ant) and inferior (FWHM-inf) LV myocardial walls. RESULTS: At both stress and rest, cranio-caudal motion was the dominant axial movement and REGAT had a positive impact on image characteristics as reflected by variations between R-SPECT and NR-SPECT in LV-Min, LV-Max, FWHM-ant, FWHM-inf, and contrast. These latter were well correlated to the amplitude of cranio-caudal motion at both stress and rest. CONCLUSIONS: Data-driven RM correction of MPI acquired with CZT SPECT is clinically feasible and easily applicable. It presents interesting impact on image characteristics. More... »

PAGES

1598-1607

References to SciGraph publications

  • 2014-05. Myocardial perfusion imaging with a cadmium zinc telluride-based gamma camera versus invasive fractional flow reserve in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2011-11. Nuclear myocardial perfusion imaging with a novel cadmium-zinc-telluride detector SPECT/CT device: first validation versus invasive coronary angiography in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2015-04. Data-driven respiratory motion tracking and compensation in CZT cameras: A comprehensive analysis of phantom and human images in JOURNAL OF NUCLEAR CARDIOLOGY
  • 2010-10. A fast cardiac gamma camera with dynamic SPECT capabilities: design, system validation and future potential in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2006-05. Respiratory gating of cardiac PET data in list-mode acquisition in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2010-04. Ultrafast nuclear myocardial perfusion imaging on a new gamma camera with semiconductor detector technique: first clinical validation in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2010-10. Real-time breath-hold triggering of myocardial perfusion imaging with a novel cadmium-zinc-telluride detector gamma camera in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2011-08. Comparison of high efficiency CZT SPECT MPI to coronary angiography in JOURNAL OF NUCLEAR CARDIOLOGY
  • 2008-11. Respiratory motion handling is mandatory to accomplish the high-resolution PET destiny in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 1999-01. Development of respiratory gated myocardial SPECT system in JOURNAL OF NUCLEAR CARDIOLOGY
  • 2007-09. Dual cardiac–respiratory gated PET: implementation and results from a feasibility study in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2012-01. High diagnostic accuracy of low-dose gated-SPECT with solid-state ultrafast detectors: preliminary clinical results in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2012-02. Reduced stress dose with rapid acquisition CZT SPECT MPI in a non-obese clinical population: Comparison to coronary angiography in JOURNAL OF NUCLEAR CARDIOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s12350-016-0493-4

    DOI

    http://dx.doi.org/10.1007/s12350-016-0493-4

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1050394616

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/27170338


    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/2008/0801", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Artificial Intelligence and Image Processing", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Information and Computing Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Aged", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Cardiac-Gated Single-Photon Emission Computer-Assisted Tomography", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Feasibility Studies", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Female", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Heart", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Heart Ventricles", 
            "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": "Linear Models", 
            "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": "Motion", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Myocardial Perfusion Imaging", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Organophosphorus Compounds", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Organotechnetium Compounds", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Pilot Projects", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Respiration", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Retrospective Studies", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Software", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Tomography, Emission-Computed, Single-Photon", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "H\u00f4pital Cochin", 
              "id": "https://www.grid.ac/institutes/grid.411784.f", 
              "name": [
                "EA 7334 REMES, Universit\u00e9 Paris-Diderot, Sorbonne Paris-Cit\u00e9, Paris, France", 
                "Nuclear Medicine Department, Cochin University Hospital, AP-HP, 27 rue du Faubourg Saint-Jacques, 75679, Paris Cedex 14, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Daou", 
            "givenName": "Doumit", 
            "id": "sg:person.01230404225.85", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01230404225.85"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Centre Hospitalier Universitaire de Besan\u00e7on", 
              "id": "https://www.grid.ac/institutes/grid.411158.8", 
              "name": [
                "Nuclear Medicine Department, CHU Jean Minjoz, Besan\u00e7on, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Sabbah", 
            "givenName": "R\u00e9my", 
            "id": "sg:person.011776740061.11", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011776740061.11"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Centre Hospitalier de Bigorre", 
              "id": "https://www.grid.ac/institutes/grid.492696.6", 
              "name": [
                "Nuclear Medicine Department, Centre Hospitalier de Bigorre, Tarbes, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Coaguila", 
            "givenName": "Carlos", 
            "id": "sg:person.01144457552.61", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01144457552.61"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Centre Hospitalier Universitaire de Besan\u00e7on", 
              "id": "https://www.grid.ac/institutes/grid.411158.8", 
              "name": [
                "Nuclear Medicine Department, CHU Jean Minjoz, Besan\u00e7on, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Boulahdour", 
            "givenName": "Hatem", 
            "id": "sg:person.01317223445.88", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01317223445.88"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/s00259-013-2630-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011852786", 
              "https://doi.org/10.1007/s00259-013-2630-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12350-011-9480-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014916254", 
              "https://doi.org/10.1007/s12350-011-9480-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-010-1488-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016336823", 
              "https://doi.org/10.1007/s00259-010-1488-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-010-1488-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016336823", 
              "https://doi.org/10.1007/s00259-010-1488-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-011-1877-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030056465", 
              "https://doi.org/10.1007/s00259-011-1877-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-010-1480-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033240025", 
              "https://doi.org/10.1007/s00259-010-1480-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-010-1480-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033240025", 
              "https://doi.org/10.1007/s00259-010-1480-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-007-0374-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034213847", 
              "https://doi.org/10.1007/s00259-007-0374-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-007-0374-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034213847", 
              "https://doi.org/10.1007/s00259-007-0374-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-011-1918-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034700602", 
              "https://doi.org/10.1007/s00259-011-1918-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2967/jnumed.106.037390", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036325805"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-005-0031-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038615370", 
              "https://doi.org/10.1007/s00259-005-0031-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-005-0031-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038615370", 
              "https://doi.org/10.1007/s00259-005-0031-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1253/circj.cj-14-0612", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043993499"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1016/s1071-3581(99)90061-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047288241", 
              "https://doi.org/10.1016/s1071-3581(99)90061-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12350-014-9963-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047518295", 
              "https://doi.org/10.1007/s12350-014-9963-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-008-0931-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048275554", 
              "https://doi.org/10.1007/s00259-008-0931-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-008-0931-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048275554", 
              "https://doi.org/10.1007/s00259-008-0931-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-009-1375-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051507500", 
              "https://doi.org/10.1007/s00259-009-1375-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-009-1375-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051507500", 
              "https://doi.org/10.1007/s00259-009-1375-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12350-011-9382-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053553556", 
              "https://doi.org/10.1007/s12350-011-9382-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/23.856568", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061132446"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tmi.2002.804427", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061694305"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2017-10", 
        "datePublishedReg": "2017-10-01", 
        "description": "BACKGROUND: We developed a data-driven respiratory motion (RM) correction method (REGAT program) for multiple-pinhole detector CZT SPECT. We verified its clinical feasibility with myocardial perfusion imaging (MPI) and studied its impact on image characteristics.\nMETHODS: This retrospective study included 18 patients having stress/rest 99mTc-Tetrofosmin MPI SPECT. List mode was acquired on CZT SPECT and processed with REGAT. REGAT generates reconstructed RM-gated volumes that are summed either without realignment (NR-SPECT) or after realignment (R-SPECT). For both stress and rest, we calculated the maximal RM in the 3 axis, and image characteristics of both R-SPECT and NR-SPECT: minimum left ventricular (LV) cavity counts (LV-Min), maximum LV myocardial counts (LV-Max), LV contrast, and FWHM of both anterior (FWHM-ant) and inferior (FWHM-inf) LV myocardial walls.\nRESULTS: At both stress and rest, cranio-caudal motion was the dominant axial movement and REGAT had a positive impact on image characteristics as reflected by variations between R-SPECT and NR-SPECT in LV-Min, LV-Max, FWHM-ant, FWHM-inf, and contrast. These latter were well correlated to the amplitude of cranio-caudal motion at both stress and rest.\nCONCLUSIONS: Data-driven RM correction of MPI acquired with CZT SPECT is clinically feasible and easily applicable. It presents interesting impact on image characteristics.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s12350-016-0493-4", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1106202", 
            "issn": [
              "1071-3581", 
              "1532-6551"
            ], 
            "name": "Journal of Nuclear Cardiology", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "5", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "24"
          }
        ], 
        "name": "Feasibility of data-driven cardiac respiratory motion correction of myocardial perfusion CZT SPECT: A pilot study", 
        "pagination": "1598-1607", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "f0104c62c538ee94cbb279ed9839fdf3d8cb01e1375806fbb9f96674d2043cab"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "27170338"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "9423534"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s12350-016-0493-4"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1050394616"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s12350-016-0493-4", 
          "https://app.dimensions.ai/details/publication/pub.1050394616"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T12:36", 
        "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/v90/0000000363_0000000363/records_70028_00000002.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1007%2Fs12350-016-0493-4"
      }
    ]
     

    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/s12350-016-0493-4'

    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/s12350-016-0493-4'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12350-016-0493-4'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12350-016-0493-4'


     

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

    241 TRIPLES      21 PREDICATES      66 URIs      41 LITERALS      29 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s12350-016-0493-4 schema:about N1c232796737c40ffa1270d16d2d8a1f1
    2 N21c8d3e034774fbd877cb851d65dd5e4
    3 N39e55296a6f442ecb6bc2bc36b108333
    4 N42e651028af4452b8d2287a30a8bb8dc
    5 N4f1ea33eb37a4b3287969543b9dd5cc8
    6 N52cacf9945f5428abf7152543802e97e
    7 N53d63e9d3ce14146be4f4efc2b7acefb
    8 N851ce1a221ab45969867d706e16f9558
    9 N8cb04df05dd446b7ab75c397807cf3a1
    10 N8eeeba45fcf44ca3be3fe8094cbe0b16
    11 Na311242a4f8f4255aec50b63b4643a96
    12 Nb43db7dde10b4a9595b064f15acdd512
    13 Nc591336c720c4326b7590dbfcaa1dba7
    14 Nc6187f8f62864d5ba1cf4e1db6d22464
    15 Nc6854b207b194b449b18a1c25e0a4840
    16 Ncfa1e5758a05469eb370c693a977a1a6
    17 Ne1b59041fc5f4ea0957e9023da97edca
    18 Ne3f48a63226e490d9fdb38cd4a47fb73
    19 Nece257d6f26b4f14bc93cb3e25eb9564
    20 Nf556aee377cb44efbf3358bb80c26e8a
    21 anzsrc-for:08
    22 anzsrc-for:0801
    23 schema:author N6f7afc3b33b4457f9878fa7af4565cc7
    24 schema:citation sg:pub.10.1007/s00259-005-0031-0
    25 sg:pub.10.1007/s00259-007-0374-9
    26 sg:pub.10.1007/s00259-008-0931-x
    27 sg:pub.10.1007/s00259-009-1375-7
    28 sg:pub.10.1007/s00259-010-1480-7
    29 sg:pub.10.1007/s00259-010-1488-z
    30 sg:pub.10.1007/s00259-011-1877-y
    31 sg:pub.10.1007/s00259-011-1918-6
    32 sg:pub.10.1007/s00259-013-2630-5
    33 sg:pub.10.1007/s12350-011-9382-z
    34 sg:pub.10.1007/s12350-011-9480-y
    35 sg:pub.10.1007/s12350-014-9963-8
    36 sg:pub.10.1016/s1071-3581(99)90061-2
    37 https://doi.org/10.1109/23.856568
    38 https://doi.org/10.1109/tmi.2002.804427
    39 https://doi.org/10.1253/circj.cj-14-0612
    40 https://doi.org/10.2967/jnumed.106.037390
    41 schema:datePublished 2017-10
    42 schema:datePublishedReg 2017-10-01
    43 schema:description BACKGROUND: We developed a data-driven respiratory motion (RM) correction method (REGAT program) for multiple-pinhole detector CZT SPECT. We verified its clinical feasibility with myocardial perfusion imaging (MPI) and studied its impact on image characteristics. METHODS: This retrospective study included 18 patients having stress/rest 99mTc-Tetrofosmin MPI SPECT. List mode was acquired on CZT SPECT and processed with REGAT. REGAT generates reconstructed RM-gated volumes that are summed either without realignment (NR-SPECT) or after realignment (R-SPECT). For both stress and rest, we calculated the maximal RM in the 3 axis, and image characteristics of both R-SPECT and NR-SPECT: minimum left ventricular (LV) cavity counts (LV-Min), maximum LV myocardial counts (LV-Max), LV contrast, and FWHM of both anterior (FWHM-ant) and inferior (FWHM-inf) LV myocardial walls. RESULTS: At both stress and rest, cranio-caudal motion was the dominant axial movement and REGAT had a positive impact on image characteristics as reflected by variations between R-SPECT and NR-SPECT in LV-Min, LV-Max, FWHM-ant, FWHM-inf, and contrast. These latter were well correlated to the amplitude of cranio-caudal motion at both stress and rest. CONCLUSIONS: Data-driven RM correction of MPI acquired with CZT SPECT is clinically feasible and easily applicable. It presents interesting impact on image characteristics.
    44 schema:genre research_article
    45 schema:inLanguage en
    46 schema:isAccessibleForFree false
    47 schema:isPartOf N8584a33c92834cd7b1f98dde96ae0ae5
    48 Na082cf70fe2e4cab80111740971c5817
    49 sg:journal.1106202
    50 schema:name Feasibility of data-driven cardiac respiratory motion correction of myocardial perfusion CZT SPECT: A pilot study
    51 schema:pagination 1598-1607
    52 schema:productId N2cb7c8e3397146c3820be80b610f9cbb
    53 N53a93678e63546c1b98bdf2fdea681a7
    54 N76d543ffa0744903a5ccb528c80ae3b8
    55 Nbfa1eb62d4e8451683572c3453d28695
    56 Nf0308a427f164fca8cbf6685cc6aa289
    57 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050394616
    58 https://doi.org/10.1007/s12350-016-0493-4
    59 schema:sdDatePublished 2019-04-11T12:36
    60 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    61 schema:sdPublisher N8790e51e64a74fa3967427a6bbd726cc
    62 schema:url https://link.springer.com/10.1007%2Fs12350-016-0493-4
    63 sgo:license sg:explorer/license/
    64 sgo:sdDataset articles
    65 rdf:type schema:ScholarlyArticle
    66 N1c232796737c40ffa1270d16d2d8a1f1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    67 schema:name Female
    68 rdf:type schema:DefinedTerm
    69 N21c8d3e034774fbd877cb851d65dd5e4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    70 schema:name Linear Models
    71 rdf:type schema:DefinedTerm
    72 N2cb7c8e3397146c3820be80b610f9cbb schema:name nlm_unique_id
    73 schema:value 9423534
    74 rdf:type schema:PropertyValue
    75 N39e55296a6f442ecb6bc2bc36b108333 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    76 schema:name Pilot Projects
    77 rdf:type schema:DefinedTerm
    78 N42e651028af4452b8d2287a30a8bb8dc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    79 schema:name Myocardial Perfusion Imaging
    80 rdf:type schema:DefinedTerm
    81 N4f1ea33eb37a4b3287969543b9dd5cc8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    82 schema:name Respiration
    83 rdf:type schema:DefinedTerm
    84 N52cacf9945f5428abf7152543802e97e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    85 schema:name Organotechnetium Compounds
    86 rdf:type schema:DefinedTerm
    87 N53a93678e63546c1b98bdf2fdea681a7 schema:name pubmed_id
    88 schema:value 27170338
    89 rdf:type schema:PropertyValue
    90 N53d63e9d3ce14146be4f4efc2b7acefb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    91 schema:name Middle Aged
    92 rdf:type schema:DefinedTerm
    93 N6c531e5ef1334db884b9e9bc3ed32e6b rdf:first sg:person.01144457552.61
    94 rdf:rest N722a9ecfe73747a6b63a278ce7b557b2
    95 N6f7afc3b33b4457f9878fa7af4565cc7 rdf:first sg:person.01230404225.85
    96 rdf:rest N7af2bf761a2040dcadf34e16f44304af
    97 N722a9ecfe73747a6b63a278ce7b557b2 rdf:first sg:person.01317223445.88
    98 rdf:rest rdf:nil
    99 N76d543ffa0744903a5ccb528c80ae3b8 schema:name dimensions_id
    100 schema:value pub.1050394616
    101 rdf:type schema:PropertyValue
    102 N7af2bf761a2040dcadf34e16f44304af rdf:first sg:person.011776740061.11
    103 rdf:rest N6c531e5ef1334db884b9e9bc3ed32e6b
    104 N851ce1a221ab45969867d706e16f9558 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    105 schema:name Software
    106 rdf:type schema:DefinedTerm
    107 N8584a33c92834cd7b1f98dde96ae0ae5 schema:issueNumber 5
    108 rdf:type schema:PublicationIssue
    109 N8790e51e64a74fa3967427a6bbd726cc schema:name Springer Nature - SN SciGraph project
    110 rdf:type schema:Organization
    111 N8cb04df05dd446b7ab75c397807cf3a1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    112 schema:name Organophosphorus Compounds
    113 rdf:type schema:DefinedTerm
    114 N8eeeba45fcf44ca3be3fe8094cbe0b16 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    115 schema:name Humans
    116 rdf:type schema:DefinedTerm
    117 Na082cf70fe2e4cab80111740971c5817 schema:volumeNumber 24
    118 rdf:type schema:PublicationVolume
    119 Na311242a4f8f4255aec50b63b4643a96 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    120 schema:name Retrospective Studies
    121 rdf:type schema:DefinedTerm
    122 Nb43db7dde10b4a9595b064f15acdd512 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    123 schema:name Cardiac-Gated Single-Photon Emission Computer-Assisted Tomography
    124 rdf:type schema:DefinedTerm
    125 Nbfa1eb62d4e8451683572c3453d28695 schema:name readcube_id
    126 schema:value f0104c62c538ee94cbb279ed9839fdf3d8cb01e1375806fbb9f96674d2043cab
    127 rdf:type schema:PropertyValue
    128 Nc591336c720c4326b7590dbfcaa1dba7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    129 schema:name Feasibility Studies
    130 rdf:type schema:DefinedTerm
    131 Nc6187f8f62864d5ba1cf4e1db6d22464 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    132 schema:name Tomography, Emission-Computed, Single-Photon
    133 rdf:type schema:DefinedTerm
    134 Nc6854b207b194b449b18a1c25e0a4840 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    135 schema:name Heart Ventricles
    136 rdf:type schema:DefinedTerm
    137 Ncfa1e5758a05469eb370c693a977a1a6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    138 schema:name Heart
    139 rdf:type schema:DefinedTerm
    140 Ne1b59041fc5f4ea0957e9023da97edca schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    141 schema:name Image Processing, Computer-Assisted
    142 rdf:type schema:DefinedTerm
    143 Ne3f48a63226e490d9fdb38cd4a47fb73 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    144 schema:name Male
    145 rdf:type schema:DefinedTerm
    146 Nece257d6f26b4f14bc93cb3e25eb9564 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    147 schema:name Motion
    148 rdf:type schema:DefinedTerm
    149 Nf0308a427f164fca8cbf6685cc6aa289 schema:name doi
    150 schema:value 10.1007/s12350-016-0493-4
    151 rdf:type schema:PropertyValue
    152 Nf556aee377cb44efbf3358bb80c26e8a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    153 schema:name Aged
    154 rdf:type schema:DefinedTerm
    155 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    156 schema:name Information and Computing Sciences
    157 rdf:type schema:DefinedTerm
    158 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
    159 schema:name Artificial Intelligence and Image Processing
    160 rdf:type schema:DefinedTerm
    161 sg:journal.1106202 schema:issn 1071-3581
    162 1532-6551
    163 schema:name Journal of Nuclear Cardiology
    164 rdf:type schema:Periodical
    165 sg:person.01144457552.61 schema:affiliation https://www.grid.ac/institutes/grid.492696.6
    166 schema:familyName Coaguila
    167 schema:givenName Carlos
    168 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01144457552.61
    169 rdf:type schema:Person
    170 sg:person.011776740061.11 schema:affiliation https://www.grid.ac/institutes/grid.411158.8
    171 schema:familyName Sabbah
    172 schema:givenName Rémy
    173 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011776740061.11
    174 rdf:type schema:Person
    175 sg:person.01230404225.85 schema:affiliation https://www.grid.ac/institutes/grid.411784.f
    176 schema:familyName Daou
    177 schema:givenName Doumit
    178 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01230404225.85
    179 rdf:type schema:Person
    180 sg:person.01317223445.88 schema:affiliation https://www.grid.ac/institutes/grid.411158.8
    181 schema:familyName Boulahdour
    182 schema:givenName Hatem
    183 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01317223445.88
    184 rdf:type schema:Person
    185 sg:pub.10.1007/s00259-005-0031-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038615370
    186 https://doi.org/10.1007/s00259-005-0031-0
    187 rdf:type schema:CreativeWork
    188 sg:pub.10.1007/s00259-007-0374-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034213847
    189 https://doi.org/10.1007/s00259-007-0374-9
    190 rdf:type schema:CreativeWork
    191 sg:pub.10.1007/s00259-008-0931-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1048275554
    192 https://doi.org/10.1007/s00259-008-0931-x
    193 rdf:type schema:CreativeWork
    194 sg:pub.10.1007/s00259-009-1375-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051507500
    195 https://doi.org/10.1007/s00259-009-1375-7
    196 rdf:type schema:CreativeWork
    197 sg:pub.10.1007/s00259-010-1480-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033240025
    198 https://doi.org/10.1007/s00259-010-1480-7
    199 rdf:type schema:CreativeWork
    200 sg:pub.10.1007/s00259-010-1488-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1016336823
    201 https://doi.org/10.1007/s00259-010-1488-z
    202 rdf:type schema:CreativeWork
    203 sg:pub.10.1007/s00259-011-1877-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1030056465
    204 https://doi.org/10.1007/s00259-011-1877-y
    205 rdf:type schema:CreativeWork
    206 sg:pub.10.1007/s00259-011-1918-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034700602
    207 https://doi.org/10.1007/s00259-011-1918-6
    208 rdf:type schema:CreativeWork
    209 sg:pub.10.1007/s00259-013-2630-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011852786
    210 https://doi.org/10.1007/s00259-013-2630-5
    211 rdf:type schema:CreativeWork
    212 sg:pub.10.1007/s12350-011-9382-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1053553556
    213 https://doi.org/10.1007/s12350-011-9382-z
    214 rdf:type schema:CreativeWork
    215 sg:pub.10.1007/s12350-011-9480-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1014916254
    216 https://doi.org/10.1007/s12350-011-9480-y
    217 rdf:type schema:CreativeWork
    218 sg:pub.10.1007/s12350-014-9963-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047518295
    219 https://doi.org/10.1007/s12350-014-9963-8
    220 rdf:type schema:CreativeWork
    221 sg:pub.10.1016/s1071-3581(99)90061-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047288241
    222 https://doi.org/10.1016/s1071-3581(99)90061-2
    223 rdf:type schema:CreativeWork
    224 https://doi.org/10.1109/23.856568 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061132446
    225 rdf:type schema:CreativeWork
    226 https://doi.org/10.1109/tmi.2002.804427 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061694305
    227 rdf:type schema:CreativeWork
    228 https://doi.org/10.1253/circj.cj-14-0612 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043993499
    229 rdf:type schema:CreativeWork
    230 https://doi.org/10.2967/jnumed.106.037390 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036325805
    231 rdf:type schema:CreativeWork
    232 https://www.grid.ac/institutes/grid.411158.8 schema:alternateName Centre Hospitalier Universitaire de Besançon
    233 schema:name Nuclear Medicine Department, CHU Jean Minjoz, Besançon, France
    234 rdf:type schema:Organization
    235 https://www.grid.ac/institutes/grid.411784.f schema:alternateName Hôpital Cochin
    236 schema:name EA 7334 REMES, Université Paris-Diderot, Sorbonne Paris-Cité, Paris, France
    237 Nuclear Medicine Department, Cochin University Hospital, AP-HP, 27 rue du Faubourg Saint-Jacques, 75679, Paris Cedex 14, France
    238 rdf:type schema:Organization
    239 https://www.grid.ac/institutes/grid.492696.6 schema:alternateName Centre Hospitalier de Bigorre
    240 schema:name Nuclear Medicine Department, Centre Hospitalier de Bigorre, Tarbes, France
    241 rdf:type schema:Organization
     




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


    ...