Image Derived Input Function for [18F]-FEPPA: Application to Quantify Translocator Protein (18 kDa) in the Human Brain
Identifieur interne : 001A19 ( Ncbi/Merge ); précédent : 001A18; suivant : 001A20Image Derived Input Function for [18F]-FEPPA: Application to Quantify Translocator Protein (18 kDa) in the Human Brain
Auteurs : Rostom Mabrouk [Canada] ; Pablo M. Rusjan [Canada] ; Romina Mizrahi [Canada] ; Mark F. Jacobs [Canada] ; Yuko Koshimori [Canada] ; Sylvain Houle [Canada] ; Ji Hyun Ko [Canada] ; Antonio P. Strafella [Canada]Source :
- PLoS ONE [ 1932-6203 ] ; 2014.
English descriptors
- KwdEn :
- MESH :
- chemical , genetics : Receptors, GABA.
- metabolism : Brain, Receptors, GABA.
- methods : Positron-Emission Tomography.
- Adult, Aged, Algorithms, Female, Genotype, Humans, Kinetics, Linear Models, Male, Middle Aged, Polymorphism, Genetic, Principal Component Analysis, Software.
Abstract
In [18F]-FEPPA positron emission topography (PET) imaging, automatic blood sampling system (ABSS) is currently the gold standard to obtain the blood time activity curve (TAC) required to extract the input function (IF). Here, we compare the performance of two image-based methods of IF extraction to the ABSS gold standard method for the quantification of translocator protein (TSPO) in the human brain. The IFs were obtained from a direct delineation of the internal carotid signal (CS) and a new concept of independent component analysis (ICA). PET scans were obtained from 18 healthy volunteers. The estimated total distribution volume (VT) by CS-IF and ICA-IF were compared to the reference VT obtained by ABSS-IF in the frontal and temporal cortex, cerebellum, striatum and thalamus regions. The VT values estimated using ICA-IF were more reliable than CS-IF for all brain regions. Specifically, the slope regression in the frontal cortex with ICA-IF was r2 = 0.91 (
Url:
DOI: 10.1371/journal.pone.0115768
PubMed: 25549260
PubMed Central: 4280118
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PMC:4280118Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>In [<sup>18</sup>
F]-FEPPA positron emission topography (PET) imaging, automatic blood sampling system (ABSS) is currently the gold standard to obtain the blood time activity curve (TAC) required to extract the input function (IF). Here, we compare the performance of two image-based methods of IF extraction to the ABSS gold standard method for the quantification of translocator protein (TSPO) in the human brain. The IFs were obtained from a direct delineation of the internal carotid signal (CS) and a new concept of independent component analysis (ICA). PET scans were obtained from 18 healthy volunteers. The estimated total distribution volume (V<sub>T</sub>
) by CS-IF and ICA-IF were compared to the reference V<sub>T</sub>
obtained by ABSS-IF in the frontal and temporal cortex, cerebellum, striatum and thalamus regions. The V<sub>T</sub>
values estimated using ICA-IF were more reliable than CS-IF for all brain regions. Specifically, the slope regression in the frontal cortex with ICA-IF was r<sup>2</sup>
= 0.91 (<italic>p</italic>
<0.05), and r<sup>2</sup>
= 0.71 (<italic>p</italic>
<0.05) using CS-IF.</p>
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<country xml:lang="fr">Canada</country>
<wicri:regionArea>Division of Brain, Imaging and Behaviour, Systems Neuroscience, Toronto Western Research Institute, UHN, University of Toronto, Toronto, Ontario</wicri:regionArea>
<orgName type="university">Université de Toronto</orgName>
<placeName><settlement type="city">Toronto</settlement>
<region type="state">Ontario</region>
</placeName>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">PMC</idno>
<idno type="pmid">25549260</idno>
<idno type="pmc">4280118</idno>
<idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4280118</idno>
<idno type="RBID">PMC:4280118</idno>
<idno type="doi">10.1371/journal.pone.0115768</idno>
<date when="2014">2014</date>
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Image Derived Input Function for [<sup>18</sup>
F]-FEPPA: Application to Quantify Translocator Protein (18 kDa) in the Human Brain</title>
<author><name sortKey="Mabrouk, Rostom" sort="Mabrouk, Rostom" uniqKey="Mabrouk R" first="Rostom" last="Mabrouk">Rostom Mabrouk</name>
<affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada</addr-line>
</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario</wicri:regionArea>
<wicri:noRegion>Ontario</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Rusjan, Pablo M" sort="Rusjan, Pablo M" uniqKey="Rusjan P" first="Pablo M." last="Rusjan">Pablo M. Rusjan</name>
<affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada</addr-line>
</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario</wicri:regionArea>
<wicri:noRegion>Ontario</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Mizrahi, Romina" sort="Mizrahi, Romina" uniqKey="Mizrahi R" first="Romina" last="Mizrahi">Romina Mizrahi</name>
<affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada</addr-line>
</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario</wicri:regionArea>
<wicri:noRegion>Ontario</wicri:noRegion>
</affiliation>
<affiliation wicri:level="4"><nlm:aff id="aff5"><addr-line>Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada</addr-line>
</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Department of Psychiatry, University of Toronto, Toronto, Ontario</wicri:regionArea>
<orgName type="university">Université de Toronto</orgName>
<placeName><settlement type="city">Toronto</settlement>
<region type="state">Ontario</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Jacobs, Mark F" sort="Jacobs, Mark F" uniqKey="Jacobs M" first="Mark F." last="Jacobs">Mark F. Jacobs</name>
<affiliation wicri:level="4"><nlm:aff id="aff3"><addr-line>Division of Brain, Imaging and Behaviour, Systems Neuroscience, Toronto Western Research Institute, UHN, University of Toronto, Toronto, Ontario, Canada</addr-line>
</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Division of Brain, Imaging and Behaviour, Systems Neuroscience, Toronto Western Research Institute, UHN, University of Toronto, Toronto, Ontario</wicri:regionArea>
<orgName type="university">Université de Toronto</orgName>
<placeName><settlement type="city">Toronto</settlement>
<region type="state">Ontario</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Koshimori, Yuko" sort="Koshimori, Yuko" uniqKey="Koshimori Y" first="Yuko" last="Koshimori">Yuko Koshimori</name>
<affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada</addr-line>
</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario</wicri:regionArea>
<wicri:noRegion>Ontario</wicri:noRegion>
</affiliation>
<affiliation wicri:level="4"><nlm:aff id="aff3"><addr-line>Division of Brain, Imaging and Behaviour, Systems Neuroscience, Toronto Western Research Institute, UHN, University of Toronto, Toronto, Ontario, Canada</addr-line>
</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Division of Brain, Imaging and Behaviour, Systems Neuroscience, Toronto Western Research Institute, UHN, University of Toronto, Toronto, Ontario</wicri:regionArea>
<orgName type="university">Université de Toronto</orgName>
<placeName><settlement type="city">Toronto</settlement>
<region type="state">Ontario</region>
</placeName>
</affiliation>
</author>
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<affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada</addr-line>
</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario</wicri:regionArea>
<wicri:noRegion>Ontario</wicri:noRegion>
</affiliation>
</author>
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<affiliation wicri:level="4"><nlm:aff id="aff4"><addr-line>Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, Manitoba, Canada</addr-line>
</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, Manitoba</wicri:regionArea>
<orgName type="university">Université du Manitoba</orgName>
<placeName><settlement type="city">Winnipeg</settlement>
<region type="state">Manitoba</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Strafella, Antonio P" sort="Strafella, Antonio P" uniqKey="Strafella A" first="Antonio P." last="Strafella">Antonio P. Strafella</name>
<affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada</addr-line>
</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario</wicri:regionArea>
<wicri:noRegion>Ontario</wicri:noRegion>
</affiliation>
<affiliation wicri:level="4"><nlm:aff id="aff2"><addr-line>Morton and Gloria Shulman Movement Disorder Unit, E.J. Safra Parkinson Disease Program, Toronto Western Hospital, UHN, University of Toronto, Toronto, Canada</addr-line>
</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Morton and Gloria Shulman Movement Disorder Unit, E.J. Safra Parkinson Disease Program, Toronto Western Hospital, UHN, University of Toronto, Toronto</wicri:regionArea>
<orgName type="university">Université de Toronto</orgName>
<placeName><settlement type="city">Toronto</settlement>
<region type="state">Ontario</region>
</placeName>
</affiliation>
<affiliation wicri:level="4"><nlm:aff id="aff3"><addr-line>Division of Brain, Imaging and Behaviour, Systems Neuroscience, Toronto Western Research Institute, UHN, University of Toronto, Toronto, Ontario, Canada</addr-line>
</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Division of Brain, Imaging and Behaviour, Systems Neuroscience, Toronto Western Research Institute, UHN, University of Toronto, Toronto, Ontario</wicri:regionArea>
<orgName type="university">Université de Toronto</orgName>
<placeName><settlement type="city">Toronto</settlement>
<region type="state">Ontario</region>
</placeName>
</affiliation>
</author>
</analytic>
<series><title level="j">PLoS ONE</title>
<idno type="eISSN">1932-6203</idno>
<imprint><date when="2014">2014</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass></textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en"><p>In [<sup>18</sup>
F]-FEPPA positron emission topography (PET) imaging, automatic blood sampling system (ABSS) is currently the gold standard to obtain the blood time activity curve (TAC) required to extract the input function (IF). Here, we compare the performance of two image-based methods of IF extraction to the ABSS gold standard method for the quantification of translocator protein (TSPO) in the human brain. The IFs were obtained from a direct delineation of the internal carotid signal (CS) and a new concept of independent component analysis (ICA). PET scans were obtained from 18 healthy volunteers. The estimated total distribution volume (V<sub>T</sub>
) by CS-IF and ICA-IF were compared to the reference V<sub>T</sub>
obtained by ABSS-IF in the frontal and temporal cortex, cerebellum, striatum and thalamus regions. The V<sub>T</sub>
values estimated using ICA-IF were more reliable than CS-IF for all brain regions. Specifically, the slope regression in the frontal cortex with ICA-IF was r<sup>2</sup>
= 0.91 (<italic>p</italic>
<0.05), and r<sup>2</sup>
= 0.71 (<italic>p</italic>
<0.05) using CS-IF.</p>
</div>
</front>
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<author><name sortKey="Strafella, Antonio P" sort="Strafella, Antonio P" uniqKey="Strafella A" first="Antonio P" last="Strafella">Antonio P. Strafella</name>
<affiliation wicri:level="4"><nlm:affiliation>Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Morton and Gloria Shulman Movement Disorder Unit, E.J. Safra Parkinson Disease Program, Toronto Western Hospital, UHN, University of Toronto, Toronto, Canada; Division of Brain, Imaging and Behaviour, Systems Neuroscience, Toronto Western Research Institute, UHN, University of Toronto, Toronto, Ontario, Canada.</nlm:affiliation>
<country xml:lang="fr">Canada</country>
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<series><title level="j">PloS one</title>
<idno type="eISSN">1932-6203</idno>
<imprint><date when="2014" type="published">2014</date>
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<term>Aged</term>
<term>Algorithms</term>
<term>Brain (metabolism)</term>
<term>Female</term>
<term>Genotype</term>
<term>Humans</term>
<term>Kinetics</term>
<term>Linear Models</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Polymorphism, Genetic</term>
<term>Positron-Emission Tomography (methods)</term>
<term>Principal Component Analysis</term>
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<term>Receptors, GABA (metabolism)</term>
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<keywords scheme="MESH" type="chemical" qualifier="genetics" xml:lang="en"><term>Receptors, GABA</term>
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<keywords scheme="MESH" qualifier="metabolism" xml:lang="en"><term>Brain</term>
<term>Receptors, GABA</term>
</keywords>
<keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Positron-Emission Tomography</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Adult</term>
<term>Aged</term>
<term>Algorithms</term>
<term>Female</term>
<term>Genotype</term>
<term>Humans</term>
<term>Kinetics</term>
<term>Linear Models</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Polymorphism, Genetic</term>
<term>Principal Component Analysis</term>
<term>Software</term>
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<front><div type="abstract" xml:lang="en">In [18F]-FEPPA positron emission topography (PET) imaging, automatic blood sampling system (ABSS) is currently the gold standard to obtain the blood time activity curve (TAC) required to extract the input function (IF). Here, we compare the performance of two image-based methods of IF extraction to the ABSS gold standard method for the quantification of translocator protein (TSPO) in the human brain. The IFs were obtained from a direct delineation of the internal carotid signal (CS) and a new concept of independent component analysis (ICA). PET scans were obtained from 18 healthy volunteers. The estimated total distribution volume (V(T)) by CS-IF and ICA-IF were compared to the reference V(T) obtained by ABSS-IF in the frontal and temporal cortex, cerebellum, striatum and thalamus regions. The V(T) values estimated using ICA-IF were more reliable than CS-IF for all brain regions. Specifically, the slope regression in the frontal cortex with ICA-IF was r² = 0.91 (p<0.05), and r² = 0.71 (p<0.05) using CS-IF.</div>
</front>
</TEI>
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