Ontology type: schema:ScholarlyArticle Open Access: True
2015-07-30
AUTHORSElske Quak, Pierre-Yves Le Roux, Michael S. Hofman, Philippe Robin, David Bourhis, Jason Callahan, David Binns, Cédric Desmonts, Pierre-Yves Salaun, Rodney J. Hicks, Nicolas Aide
ABSTRACTPurposePoint-spread function (PSF) or PSF + time-of-flight (TOF) reconstruction may improve lesion detection in oncologic PET, but can alter quantitation resulting in variable standardized uptake values (SUVs) between different PET systems. This study aims to validate a proprietary software tool (EQ.PET) to harmonize SUVs across different PET systems independent of the reconstruction algorithm used.MethodsNEMA NU2 phantom data were used to calculate the appropriate filter for each PSF or PSF+TOF reconstruction from three different PET systems, in order to obtain EANM compliant recovery coefficients. PET data from 517 oncology patients were reconstructed with a PSF or PSF+TOF reconstruction for optimal tumour detection and an ordered subset expectation maximization (OSEM3D) reconstruction known to fulfil EANM guidelines. Post-reconstruction, the proprietary filter was applied to the PSF or PSF+TOF data (PSFEQ or PSF+TOFEQ). SUVs for PSF or PSF+TOF and PSFEQ or PSF+TOFEQ were compared to SUVs for the OSEM3D reconstruction. The impact of potential confounders on the EQ.PET methodology including lesion and patient characteristics was studied, as was the adherence to imaging guidelines.ResultsFor the 1380 tumour lesions studied, Bland-Altman analysis showed a mean ratio between PSF or PSF+TOF and OSEM3D of 1.46 (95 %CI: 0.86–2.06) and 1.23 (95 %CI: 0.95–1.51) for SUVmax and SUVpeak, respectively. Application of the proprietary filter improved these ratios to 1.02 (95 %CI: 0.88–1.16) and 1.04 (95 %CI: 0.92–1.17) for SUVmax and SUVpeak, respectively. The influence of the different confounding factors studied (lesion size, location, radial offset and patient’s BMI) was less than 5 %. Adherence to the European Association of Nuclear Medicine (EANM) guidelines for tumour imaging was good.ConclusionThese data indicate that it is not necessary to sacrifice the superior lesion detection and image quality achieved by newer reconstruction techniques in the quest for harmonizing quantitative comparability between PET systems. More... »
PAGES2072-2082
http://scigraph.springernature.com/pub.10.1007/s00259-015-3128-0
DOIhttp://dx.doi.org/10.1007/s00259-015-3128-0
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1037717808
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/26219870
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/2008/1103",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Clinical Sciences",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Aged",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Carcinoma, Non-Small-Cell Lung",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Female",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Fluorodeoxyglucose F18",
"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": "Liver Neoplasms",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Lymphoma, Non-Hodgkin",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Male",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Melanoma",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Middle Aged",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Positron-Emission Tomography",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Radiopharmaceuticals",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Nuclear Medicine Department, Fran\u00e7ois Baclesse Cancer Centre, Caen, France",
"id": "http://www.grid.ac/institutes/None",
"name": [
"Nuclear Medicine Department, Fran\u00e7ois Baclesse Cancer Centre, Caen, France"
],
"type": "Organization"
},
"familyName": "Quak",
"givenName": "Elske",
"id": "sg:person.01233564514.37",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01233564514.37"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France",
"id": "http://www.grid.ac/institutes/None",
"name": [
"Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France"
],
"type": "Organization"
},
"familyName": "Le Roux",
"givenName": "Pierre-Yves",
"id": "sg:person.01156373352.82",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01156373352.82"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia",
"id": "http://www.grid.ac/institutes/grid.1055.1",
"name": [
"Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia"
],
"type": "Organization"
},
"familyName": "Hofman",
"givenName": "Michael S.",
"id": "sg:person.01012460764.55",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01012460764.55"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France",
"id": "http://www.grid.ac/institutes/None",
"name": [
"Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France"
],
"type": "Organization"
},
"familyName": "Robin",
"givenName": "Philippe",
"id": "sg:person.01307140060.86",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01307140060.86"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France",
"id": "http://www.grid.ac/institutes/None",
"name": [
"Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France"
],
"type": "Organization"
},
"familyName": "Bourhis",
"givenName": "David",
"id": "sg:person.0636567456.08",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0636567456.08"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia",
"id": "http://www.grid.ac/institutes/grid.1055.1",
"name": [
"Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia"
],
"type": "Organization"
},
"familyName": "Callahan",
"givenName": "Jason",
"id": "sg:person.0616621550.24",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0616621550.24"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia",
"id": "http://www.grid.ac/institutes/grid.1055.1",
"name": [
"Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia"
],
"type": "Organization"
},
"familyName": "Binns",
"givenName": "David",
"id": "sg:person.01213140513.69",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01213140513.69"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Nuclear Medicine Department, University Hospital, Avenue C\u00f4te de Nacre, 14000, Caen, France",
"id": "http://www.grid.ac/institutes/grid.411149.8",
"name": [
"Nuclear Medicine Department, University Hospital, Avenue C\u00f4te de Nacre, 14000, Caen, France"
],
"type": "Organization"
},
"familyName": "Desmonts",
"givenName": "C\u00e9dric",
"id": "sg:person.0715336115.22",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0715336115.22"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France",
"id": "http://www.grid.ac/institutes/None",
"name": [
"Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France"
],
"type": "Organization"
},
"familyName": "Salaun",
"givenName": "Pierre-Yves",
"id": "sg:person.01021766527.49",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01021766527.49"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia",
"id": "http://www.grid.ac/institutes/grid.1055.1",
"name": [
"Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia"
],
"type": "Organization"
},
"familyName": "Hicks",
"givenName": "Rodney J.",
"id": "sg:person.01121233254.97",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01121233254.97"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Normandie University, Caen, France",
"id": "http://www.grid.ac/institutes/grid.460771.3",
"name": [
"Nuclear Medicine Department, Fran\u00e7ois Baclesse Cancer Centre, Caen, France",
"Nuclear Medicine Department, University Hospital, Avenue C\u00f4te de Nacre, 14000, Caen, France",
"INSERM 1199, Fran\u00e7ois Baclesse Cancer Centre, Caen, France",
"Normandie University, Caen, France"
],
"type": "Organization"
},
"familyName": "Aide",
"givenName": "Nicolas",
"id": "sg:person.01152406451.51",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01152406451.51"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1007/s00259-014-2689-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1024627703",
"https://doi.org/10.1007/s00259-014-2689-7"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00259-014-2961-x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1008918527",
"https://doi.org/10.1007/s00259-014-2961-x"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/2191-219x-1-16",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1025107920",
"https://doi.org/10.1186/2191-219x-1-16"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00259-014-2715-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1002676223",
"https://doi.org/10.1007/s00259-014-2715-9"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00259-013-2465-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1016939976",
"https://doi.org/10.1007/s00259-013-2465-0"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00259-013-2391-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1016046039",
"https://doi.org/10.1007/s00259-013-2391-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00259-006-0224-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1015743919",
"https://doi.org/10.1007/s00259-006-0224-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s12149-014-0815-z",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1021417424",
"https://doi.org/10.1007/s12149-014-0815-z"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00259-009-1297-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1021250910",
"https://doi.org/10.1007/s00259-009-1297-4"
],
"type": "CreativeWork"
}
],
"datePublished": "2015-07-30",
"datePublishedReg": "2015-07-30",
"description": "PurposePoint-spread function (PSF) or PSF + time-of-flight (TOF) reconstruction may improve lesion detection in oncologic PET, but can alter quantitation resulting in variable standardized uptake values (SUVs) between different PET systems. This study aims to validate a proprietary software tool (EQ.PET) to harmonize SUVs across different PET systems independent of the reconstruction algorithm used.MethodsNEMA NU2 phantom data were used to calculate the appropriate filter for each PSF or PSF+TOF reconstruction from three different PET systems, in order to obtain EANM compliant recovery coefficients. PET data from 517 oncology patients were reconstructed with a PSF or PSF+TOF reconstruction for optimal tumour detection and an ordered subset expectation maximization (OSEM3D) reconstruction known to fulfil EANM guidelines. Post-reconstruction, the proprietary filter was applied to the PSF or PSF+TOF data (PSFEQ or PSF+TOFEQ). SUVs for PSF or PSF+TOF and PSFEQ or PSF+TOFEQ were compared to SUVs for the OSEM3D reconstruction. The impact of potential confounders on the EQ.PET methodology including lesion and patient characteristics was studied, as was the adherence to imaging guidelines.ResultsFor the 1380 tumour lesions studied, Bland-Altman analysis showed a mean ratio between PSF or PSF+TOF and OSEM3D of 1.46 (95\u00a0%CI: 0.86\u20132.06) and 1.23 (95\u00a0%CI: 0.95\u20131.51) for SUVmax and SUVpeak, respectively. Application of the proprietary filter improved these ratios to 1.02 (95\u00a0%CI: 0.88\u20131.16) and 1.04 (95\u00a0%CI: 0.92\u20131.17) for SUVmax and SUVpeak, respectively. The influence of the different confounding factors studied (lesion size, location, radial offset and patient\u2019s BMI) was less than 5\u00a0%. Adherence to the European Association of Nuclear Medicine (EANM) guidelines for tumour imaging was good.ConclusionThese data indicate that it is not necessary to sacrifice the superior lesion detection and image quality achieved by newer reconstruction techniques in the quest for harmonizing quantitative comparability between PET systems.",
"genre": "article",
"id": "sg:pub.10.1007/s00259-015-3128-0",
"isAccessibleForFree": true,
"isPartOf": [
{
"id": "sg:journal.1297401",
"issn": [
"1619-7070",
"1619-7089"
],
"name": "European Journal of Nuclear Medicine and Molecular Imaging",
"publisher": "Springer Nature",
"type": "Periodical"
},
{
"issueNumber": "13",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "42"
}
],
"keywords": [
"standardized uptake value",
"oncology patients",
"different PET systems",
"optimal tumour detection",
"optimal lesion detection",
"lesion detection",
"Nuclear Medicine (EANM) guidelines",
"different confounding factors",
"superior lesion detection",
"patient characteristics",
"Medicine guidelines",
"potential confounders",
"FDG-PET quantification",
"Bland-Altman analysis",
"ConclusionThese data",
"tumor lesions",
"uptake value",
"confounding factors",
"EANM guidelines",
"multicentre validation",
"European Association",
"mean ratio",
"patients",
"SUVmax",
"lesions",
"oncologic PET",
"SUVpeak",
"PET methodology",
"tumor imaging",
"adherence",
"tumor detection",
"subsets expectation maximization (OSEM) reconstruction",
"guidelines",
"PET quantification",
"PET data",
"new reconstruction technique",
"confounders",
"ResultsFor",
"association",
"reconstruction technique",
"flight reconstruction",
"reconstruction",
"imaging",
"PET",
"data",
"detection",
"image quality",
"factors",
"quantitative comparability",
"study",
"quantitation",
"ratio",
"expectation maximization reconstruction",
"comparability",
"function",
"quality",
"PET system",
"quantification",
"time",
"phantom data",
"impact",
"analysis",
"validation",
"system",
"characteristics",
"tool",
"values",
"appropriate filters",
"proprietary software tools",
"technique",
"influence",
"software tools",
"recovery coefficient",
"reconstruction algorithm",
"order",
"quest",
"algorithm",
"coefficient",
"eq",
"filter",
"methodology",
"applications",
"OSEM3D"
],
"name": "Harmonizing FDG PET quantification while maintaining optimal lesion detection: prospective multicentre validation in 517 oncology patients",
"pagination": "2072-2082",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1037717808"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s00259-015-3128-0"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"26219870"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s00259-015-3128-0",
"https://app.dimensions.ai/details/publication/pub.1037717808"
],
"sdDataset": "articles",
"sdDatePublished": "2022-08-04T17:02",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-springernature-scigraph/baseset/20220804/entities/gbq_results/article/article_675.jsonl",
"type": "ScholarlyArticle",
"url": "https://doi.org/10.1007/s00259-015-3128-0"
}
]Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00259-015-3128-0'
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/s00259-015-3128-0'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00259-015-3128-0'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00259-015-3128-0'
This table displays all metadata directly associated to this object as RDF triples.
316 TRIPLES
21 PREDICATES
130 URIs
113 LITERALS
20 BLANK NODES