Tc‐99m ethylene cysteinate dimer SPECT in the differential diagnosis of parkinsonism
Identifieur interne : 002149 ( Main/Corpus ); précédent : 002148; suivant : 002150Tc‐99m ethylene cysteinate dimer SPECT in the differential diagnosis of parkinsonism
Auteurs : Andrew Feigin ; Angelo Antonini ; Masafumi Fukuda ; Roberta De Notaris ; Riccardo Benti ; Gianni Pezzoli ; Marc J. Mentis ; James R. Moeller ; David EidelbergSource :
- Movement Disorders [ 0885-3185 ] ; 2002-11.
English descriptors
Abstract
Positron emission tomography (PET) and network analysis have been used to identify a reproducible pattern of regional metabolic covariation that is associated with idiopathic Parkinson's disease (PD). The activity of this PD‐related pattern can be quantified in individual subjects and used to discriminate PD patients from atypical parkinsonians. Because PET is not commonly available, we sought to determine whether similar discrimination could be achieved using more routine single photon emission computed tomography (SPECT) perfusion methods. Twenty‐three subjects with PD (age, 63 ± 9 years), 22 subjects with multiple system atrophy (MSA; age, 64 ± 7 years), and 20 age‐matched healthy controls (age, 62 ± 13 years) underwent SPECT imaging of regional cerebral perfusion with Tc‐99m ethylene cysteinate dimer (ECD). Using network analysis, we determined whether a PD‐related pattern existed in the SPECT data, and whether its expression discriminated PD from MSA patients. Additionally, we compared the accuracy of group discrimination achieved by this pattern with that of the PET‐derived PD‐related pattern applied to the SPECT data. Network analysis of the SPECT data identified a significant pattern characterized by relative increases in cerebellar, lentiform, and thalamic perfusion covarying with decrements in the frontal operculum and in the medial temporal cortex. Subject scores for this pattern discriminated PD patients from controls (P < 0.01) and from MSA patients (P < 0.03). Subject scores for the PET‐derived PD‐related pattern computed in the individual SPECT scans more accurately distinguished PD patients from controls (P < 0.005) and from MSA patients (P = 0.0002). A significant PD‐related covariance pattern can be identified in SPECT perfusion data. Moreover, the disease related pattern identified previously with PET can be applied to individual SPECT perfusion scans to provide group discrimination between PD patients, healthy controls, and individuals with MSA. Because of significant individual subject overlap between groups, however, the clinical utility of this method in the differential diagnosis of Parkinsonism remains uncertain. © 2002 Movement Disorder Society
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DOI: 10.1002/mds.10270
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Network analysis of the SPECT data identified a significant pattern characterized by relative increases in cerebellar, lentiform, and thalamic perfusion covarying with decrements in the frontal operculum and in the medial temporal cortex. Subject scores for this pattern discriminated PD patients from controls (P < 0.01) and from MSA patients (P < 0.03). Subject scores for the PET‐derived PD‐related pattern computed in the individual SPECT scans more accurately distinguished PD patients from controls (P < 0.005) and from MSA patients (P = 0.0002). A significant PD‐related covariance pattern can be identified in SPECT perfusion data. Moreover, the disease related pattern identified previously with PET can be applied to individual SPECT perfusion scans to provide group discrimination between PD patients, healthy controls, and individuals with MSA. Because of significant individual subject overlap between groups, however, the clinical utility of this method in the differential diagnosis of Parkinsonism remains uncertain. © 2002 Movement Disorder Society</div></front></TEI><istex><corpusName>wiley</corpusName><author><json:item><name>Andrew Feigin MD</name><affiliations><json:string>Center for Neuroscience, North Shore University Hospital, Manhasset, New York and New York University School of Medicine, New York, New York, USA</json:string></affiliations></json:item><json:item><name>Angelo Antonini MD</name><affiliations><json:string>Instituti Clinici Di Perfezionamento, Parkinson's Institute, Milan, Italy</json:string></affiliations></json:item><json:item><name>Masafumi Fukuda MD</name><affiliations><json:string>Center for Neuroscience, North Shore University Hospital, Manhasset, New York and New York University School of Medicine, New York, New York, USA</json:string></affiliations></json:item><json:item><name>Roberta De Notaris MD</name><affiliations><json:string>Instituti Clinici Di Perfezionamento, Parkinson's Institute, Milan, Italy</json:string></affiliations></json:item><json:item><name>Riccardo Benti MD</name><affiliations><json:string>Instituti Clinici Di Perfezionamento, Parkinson's Institute, Milan, Italy</json:string></affiliations></json:item><json:item><name>Gianni Pezzoli MD</name><affiliations><json:string>Instituti Clinici Di Perfezionamento, Parkinson's Institute, Milan, Italy</json:string></affiliations></json:item><json:item><name>Marc J. 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Moeller PhD</name><affiliations><json:string>Department of Psychiatry, Columbia College of Physicians and Surgeons, New York, New York, USA</json:string></affiliations></json:item><json:item><name>David Eidelberg MD</name><affiliations><json:string>Center for Neuroscience, North Shore University Hospital, Manhasset, New York and New York University School of Medicine, New York, New York, USA</json:string></affiliations></json:item></author><subject><json:item><lang><json:string>eng</json:string></lang><value>ECD/SPECT</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>parkinsonism</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>differential diagnosis</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>network analysis</value></json:item></subject><articleId><json:string>MDS10270</json:string></articleId><language><json:string>eng</json:string></language><abstract>Positron emission tomography (PET) and network analysis have been used to identify a reproducible pattern of regional metabolic covariation that is associated with idiopathic Parkinson's disease (PD). The activity of this PD‐related pattern can be quantified in individual subjects and used to discriminate PD patients from atypical parkinsonians. Because PET is not commonly available, we sought to determine whether similar discrimination could be achieved using more routine single photon emission computed tomography (SPECT) perfusion methods. Twenty‐three subjects with PD (age, 63 ± 9 years), 22 subjects with multiple system atrophy (MSA; age, 64 ± 7 years), and 20 age‐matched healthy controls (age, 62 ± 13 years) underwent SPECT imaging of regional cerebral perfusion with Tc‐99m ethylene cysteinate dimer (ECD). Using network analysis, we determined whether a PD‐related pattern existed in the SPECT data, and whether its expression discriminated PD from MSA patients. Additionally, we compared the accuracy of group discrimination achieved by this pattern with that of the PET‐derived PD‐related pattern applied to the SPECT data. Network analysis of the SPECT data identified a significant pattern characterized by relative increases in cerebellar, lentiform, and thalamic perfusion covarying with decrements in the frontal operculum and in the medial temporal cortex. Subject scores for this pattern discriminated PD patients from controls (P > 0.01) and from MSA patients (P > 0.03). Subject scores for the PET‐derived PD‐related pattern computed in the individual SPECT scans more accurately distinguished PD patients from controls (P > 0.005) and from MSA patients (P = 0.0002). A significant PD‐related covariance pattern can be identified in SPECT perfusion data. Moreover, the disease related pattern identified previously with PET can be applied to individual SPECT perfusion scans to provide group discrimination between PD patients, healthy controls, and individuals with MSA. 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The activity of this PD‐related pattern can be quantified in individual subjects and used to discriminate PD patients from atypical parkinsonians. Because PET is not commonly available, we sought to determine whether similar discrimination could be achieved using more routine single photon emission computed tomography (SPECT) perfusion methods. Twenty‐three subjects with PD (age, 63 ± 9 years), 22 subjects with multiple system atrophy (MSA; age, 64 ± 7 years), and 20 age‐matched healthy controls (age, 62 ± 13 years) underwent SPECT imaging of regional cerebral perfusion with Tc‐99m ethylene cysteinate dimer (ECD). Using network analysis, we determined whether a PD‐related pattern existed in the SPECT data, and whether its expression discriminated PD from MSA patients. Additionally, we compared the accuracy of group discrimination achieved by this pattern with that of the PET‐derived PD‐related pattern applied to the SPECT data. Network analysis of the SPECT data identified a significant pattern characterized by relative increases in cerebellar, lentiform, and thalamic perfusion covarying with decrements in the frontal operculum and in the medial temporal cortex. Subject scores for this pattern discriminated PD patients from controls (P < 0.01) and from MSA patients (P < 0.03). Subject scores for the PET‐derived PD‐related pattern computed in the individual SPECT scans more accurately distinguished PD patients from controls (P < 0.005) and from MSA patients (P = 0.0002). A significant PD‐related covariance pattern can be identified in SPECT perfusion data. Moreover, the disease related pattern identified previously with PET can be applied to individual SPECT perfusion scans to provide group discrimination between PD patients, healthy controls, and individuals with MSA. 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href="file:MDS.MDS10270.pdf"></link></linkGroup></publicationMeta><contentMeta><countGroup><count type="figureTotal" number="5"></count><count type="tableTotal" number="0"></count><count type="referenceTotal" number="32"></count><count type="wordTotal" number="3430"></count></countGroup><titleGroup><title type="main" xml:lang="en">Tc‐99m ethylene cysteinate dimer SPECT in the differential diagnosis of parkinsonism</title><title type="short" xml:lang="en">ECD SPECT in Parkinsonism</title></titleGroup><creators><creator xml:id="au1" creatorRole="author" affiliationRef="#af1" corresponding="yes"><personName><givenNames>Andrew</givenNames><familyName>Feigin</familyName><degrees>MD</degrees></personName><contactDetails><email>asfeigin@aol.com</email></contactDetails></creator><creator xml:id="au2" creatorRole="author" affiliationRef="#af2"><personName><givenNames>Angelo</givenNames><familyName>Antonini</familyName><degrees>MD</degrees></personName></creator><creator xml:id="au3" creatorRole="author" affiliationRef="#af1"><personName><givenNames>Masafumi</givenNames><familyName>Fukuda</familyName><degrees>MD</degrees></personName></creator><creator xml:id="au4" creatorRole="author" affiliationRef="#af2"><personName><givenNames>Roberta</givenNames><familyName>De Notaris</familyName><degrees>MD</degrees></personName></creator><creator xml:id="au5" creatorRole="author" affiliationRef="#af2"><personName><givenNames>Riccardo</givenNames><familyName>Benti</familyName><degrees>MD</degrees></personName></creator><creator xml:id="au6" creatorRole="author" affiliationRef="#af2"><personName><givenNames>Gianni</givenNames><familyName>Pezzoli</familyName><degrees>MD</degrees></personName></creator><creator xml:id="au7" creatorRole="author" affiliationRef="#af1"><personName><givenNames>Marc J.</givenNames><familyName>Mentis</familyName><degrees>MD</degrees></personName></creator><creator xml:id="au8" creatorRole="author" affiliationRef="#af3"><personName><givenNames>James R.</givenNames><familyName>Moeller</familyName><degrees>PhD</degrees></personName></creator><creator xml:id="au9" creatorRole="author" affiliationRef="#af1"><personName><givenNames>David</givenNames><familyName>Eidelberg</familyName><degrees>MD</degrees></personName></creator></creators><affiliationGroup><affiliation xml:id="af1" countryCode="US" type="organization"><unparsedAffiliation>Center for Neuroscience, North Shore University Hospital, Manhasset, New York and New York University School of Medicine, New York, New York, USA</unparsedAffiliation></affiliation><affiliation xml:id="af2" countryCode="IT" type="organization"><unparsedAffiliation>Instituti Clinici Di Perfezionamento, Parkinson's Institute, Milan, Italy</unparsedAffiliation></affiliation><affiliation xml:id="af3" countryCode="US" type="organization"><unparsedAffiliation>Department of Psychiatry, Columbia College of Physicians and Surgeons, New York, New York, USA</unparsedAffiliation></affiliation></affiliationGroup><keywordGroup xml:lang="en" type="author"><keyword xml:id="kwd1">ECD/SPECT</keyword><keyword xml:id="kwd2">parkinsonism</keyword><keyword xml:id="kwd3">differential diagnosis</keyword><keyword xml:id="kwd4">network analysis</keyword></keywordGroup><abstractGroup><abstract type="main" xml:lang="en"><title type="main">Abstract</title><p>Positron emission tomography (PET) and network analysis have been used to identify a reproducible pattern of regional metabolic covariation that is associated with idiopathic Parkinson's disease (PD). The activity of this PD‐related pattern can be quantified in individual subjects and used to discriminate PD patients from atypical parkinsonians. Because PET is not commonly available, we sought to determine whether similar discrimination could be achieved using more routine single photon emission computed tomography (SPECT) perfusion methods. Twenty‐three subjects with PD (age, 63 ± 9 years), 22 subjects with multiple system atrophy (MSA; age, 64 ± 7 years), and 20 age‐matched healthy controls (age, 62 ± 13 years) underwent SPECT imaging of regional cerebral perfusion with Tc‐99m ethylene cysteinate dimer (ECD). Using network analysis, we determined whether a PD‐related pattern existed in the SPECT data, and whether its expression discriminated PD from MSA patients. Additionally, we compared the accuracy of group discrimination achieved by this pattern with that of the PET‐derived PD‐related pattern applied to the SPECT data. Network analysis of the SPECT data identified a significant pattern characterized by relative increases in cerebellar, lentiform, and thalamic perfusion covarying with decrements in the frontal operculum and in the medial temporal cortex. Subject scores for this pattern discriminated PD patients from controls (<i>P</i> < 0.01) and from MSA patients (<i>P</i> < 0.03). Subject scores for the PET‐derived PD‐related pattern computed in the individual SPECT scans more accurately distinguished PD patients from controls (<i>P</i> < 0.005) and from MSA patients (<i>P</i> = 0.0002). A significant PD‐related covariance pattern can be identified in SPECT perfusion data. Moreover, the disease related pattern identified previously with PET can be applied to individual SPECT perfusion scans to provide group discrimination between PD patients, healthy controls, and individuals with MSA. Because of significant individual subject overlap between groups, however, the clinical utility of this method in the differential diagnosis of Parkinsonism remains uncertain. © 2002 Movement Disorder Society</p></abstract></abstractGroup></contentMeta></header></component></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Tc‐99m ethylene cysteinate dimer SPECT in the differential diagnosis of parkinsonism</title></titleInfo><titleInfo type="abbreviated" lang="en"><title>ECD SPECT in Parkinsonism</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Tc‐99m ethylene cysteinate dimer SPECT in the differential diagnosis of parkinsonism</title></titleInfo><name type="personal"><namePart type="given">Andrew</namePart><namePart type="family">Feigin</namePart><namePart type="termsOfAddress">MD</namePart><affiliation>Center for Neuroscience, North Shore University Hospital, Manhasset, New York and New York University School of Medicine, New York, New York, USA</affiliation><description>Correspondence: Center for Neuroscience, North Shore University Hospital, 350 Community Drive, Manhasset, NY 11030</description><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Angelo</namePart><namePart type="family">Antonini</namePart><namePart type="termsOfAddress">MD</namePart><affiliation>Instituti Clinici Di Perfezionamento, Parkinson's Institute, Milan, Italy</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Masafumi</namePart><namePart type="family">Fukuda</namePart><namePart type="termsOfAddress">MD</namePart><affiliation>Center for Neuroscience, North Shore University Hospital, Manhasset, New York and New York University School of Medicine, New York, New York, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Roberta</namePart><namePart type="family">De Notaris</namePart><namePart type="termsOfAddress">MD</namePart><affiliation>Instituti Clinici Di Perfezionamento, Parkinson's Institute, Milan, Italy</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Riccardo</namePart><namePart type="family">Benti</namePart><namePart type="termsOfAddress">MD</namePart><affiliation>Instituti Clinici Di Perfezionamento, Parkinson's Institute, Milan, Italy</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Gianni</namePart><namePart type="family">Pezzoli</namePart><namePart type="termsOfAddress">MD</namePart><affiliation>Instituti Clinici Di Perfezionamento, Parkinson's Institute, Milan, Italy</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Marc J.</namePart><namePart type="family">Mentis</namePart><namePart type="termsOfAddress">MD</namePart><affiliation>Center for Neuroscience, North Shore University Hospital, Manhasset, New York and New York University School of Medicine, New York, New York, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">James R.</namePart><namePart type="family">Moeller</namePart><namePart type="termsOfAddress">PhD</namePart><affiliation>Department of Psychiatry, Columbia College of Physicians and Surgeons, New York, New York, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">David</namePart><namePart type="family">Eidelberg</namePart><namePart type="termsOfAddress">MD</namePart><affiliation>Center for Neuroscience, North Shore University Hospital, Manhasset, New York and New York University School of Medicine, New York, New York, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="article" displayLabel="article"></genre><originInfo><publisher>Wiley Subscription Services, Inc., A Wiley Company</publisher><place><placeTerm type="text">New York</placeTerm></place><dateIssued encoding="w3cdtf">2002-11</dateIssued><dateCaptured encoding="w3cdtf">2001-06-01</dateCaptured><dateValid encoding="w3cdtf">2002-04-16</dateValid><copyrightDate encoding="w3cdtf">2002</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType><extent unit="figures">5</extent><extent unit="references">32</extent><extent unit="words">3430</extent></physicalDescription><abstract lang="en">Positron emission tomography (PET) and network analysis have been used to identify a reproducible pattern of regional metabolic covariation that is associated with idiopathic Parkinson's disease (PD). The activity of this PD‐related pattern can be quantified in individual subjects and used to discriminate PD patients from atypical parkinsonians. Because PET is not commonly available, we sought to determine whether similar discrimination could be achieved using more routine single photon emission computed tomography (SPECT) perfusion methods. Twenty‐three subjects with PD (age, 63 ± 9 years), 22 subjects with multiple system atrophy (MSA; age, 64 ± 7 years), and 20 age‐matched healthy controls (age, 62 ± 13 years) underwent SPECT imaging of regional cerebral perfusion with Tc‐99m ethylene cysteinate dimer (ECD). Using network analysis, we determined whether a PD‐related pattern existed in the SPECT data, and whether its expression discriminated PD from MSA patients. Additionally, we compared the accuracy of group discrimination achieved by this pattern with that of the PET‐derived PD‐related pattern applied to the SPECT data. Network analysis of the SPECT data identified a significant pattern characterized by relative increases in cerebellar, lentiform, and thalamic perfusion covarying with decrements in the frontal operculum and in the medial temporal cortex. Subject scores for this pattern discriminated PD patients from controls (P < 0.01) and from MSA patients (P < 0.03). Subject scores for the PET‐derived PD‐related pattern computed in the individual SPECT scans more accurately distinguished PD patients from controls (P < 0.005) and from MSA patients (P = 0.0002). A significant PD‐related covariance pattern can be identified in SPECT perfusion data. Moreover, the disease related pattern identified previously with PET can be applied to individual SPECT perfusion scans to provide group discrimination between PD patients, healthy controls, and individuals with MSA. Because of significant individual subject overlap between groups, however, the clinical utility of this method in the differential diagnosis of Parkinsonism remains uncertain. © 2002 Movement Disorder Society</abstract><subject lang="en"><genre>Keywords</genre><topic>ECD/SPECT</topic><topic>parkinsonism</topic><topic>differential diagnosis</topic><topic>network analysis</topic></subject><relatedItem type="host"><titleInfo><title>Movement Disorders</title><subTitle>Official Journal of the Movement Disorder Society</subTitle></titleInfo><titleInfo type="abbreviated"><title>Mov. Disord.</title></titleInfo><genre type="Journal">journal</genre><subject><genre>article category</genre><topic>Research Article</topic></subject><identifier type="ISSN">0885-3185</identifier><identifier type="eISSN">1531-8257</identifier><identifier type="DOI">10.1002/(ISSN)1531-8257</identifier><identifier type="PublisherID">MDS</identifier><part><date>2002</date><detail type="volume"><caption>vol.</caption><number>17</number></detail><detail type="issue"><caption>no.</caption><number>6</number></detail><extent unit="pages"><start>1265</start><end>1270</end><total>6</total></extent></part></relatedItem><identifier type="istex">651CB3617DCFB9477C491184DD4E6E44F617C254</identifier><identifier type="DOI">10.1002/mds.10270</identifier><identifier type="ArticleID">MDS10270</identifier><accessCondition type="use and reproduction" contentType="copyright">Copyright © 2002 Movement Disorders Society</accessCondition><recordInfo><recordContentSource>WILEY</recordContentSource><recordOrigin>Wiley Subscription Services, Inc., A Wiley Company</recordOrigin></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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