Home > Publications database > Image-Derived Input Functions for Quantification of A1 Adenosine Receptors Availability in Mice Brains Using PET and [18F]CPFPX > print |
001 | 872864 | ||
005 | 20220930130228.0 | ||
024 | 7 | _ | |a 10.3389/fphys.2019.01617 |2 doi |
024 | 7 | _ | |a 2128/24105 |2 Handle |
024 | 7 | _ | |a altmetric:74892229 |2 altmetric |
024 | 7 | _ | |a pmid:32063864 |2 pmid |
024 | 7 | _ | |a WOS:000514299600001 |2 WOS |
037 | _ | _ | |a FZJ-2020-00330 |
082 | _ | _ | |a 610 |
100 | 1 | _ | |0 P:(DE-Juel1)171331 |a He, Xuan |b 0 |
245 | _ | _ | |a Image-Derived Input Functions for Quantification of A1 Adenosine Receptors Availability in Mice Brains Using PET and [18F]CPFPX |
260 | _ | _ | |a Lausanne |b Frontiers Research Foundation |c 2020 |
336 | 7 | _ | |2 DRIVER |a article |
336 | 7 | _ | |2 DataCite |a Output Types/Journal article |
336 | 7 | _ | |0 PUB:(DE-HGF)16 |2 PUB:(DE-HGF) |a Journal Article |b journal |m journal |s 1580388991_17363 |
336 | 7 | _ | |2 BibTeX |a ARTICLE |
336 | 7 | _ | |2 ORCID |a JOURNAL_ARTICLE |
336 | 7 | _ | |0 0 |2 EndNote |a Journal Article |
520 | _ | _ | |a In vivo imaging for the A1 adenosine receptors (A1ARs) with positron emission tomography (PET) using 8-cyclopentyl-3-(3-[18F]fluoropropyl)-1-propylxanthine ([18F]CPFPX) has become an important tool for studying physiologic processes quantitatively in mice. However, the measurement of arterial input functions (AIFs) on mice is a method with restricted applicability because of the small total blood volume and the related difficulties in withdrawing blood. Therefore, the aim of this study was to extract an appropriate [18F]CPFPX image-derived input function (IDIF) from dynamic PET images of mice.In this study five mice were scanned with [18F]CPFPX for 60 min. Arterial blood samples (n=7 per animal) were collected from the femoral artery and corrected for metabolites. To generate IDIFs, three different approaches were selected: (A) volume of interest (VOI) placed over the heart (cube, 10mm); (B) VOI set over abdominal vena cava/aorta region with a cuboid (5 × 5 × 15mm); and (C) with 1 × 1 × 1mm voxels on 5 consecutive slices. A calculated scaling factor (α) was used to correct for partial volume effect, the method of obtaining the total metabolite correction of [18F]CPFPX for IDIFs was developed. Three IDIFs were validated by comparison with AIF. Validation included: visual performance; computing area under the curve (AUC) ratios (IDIF / AIF) of whole-blood curves and parent curves; in addition, the mean distribution volume (VT) ratios (IDIF / AIF) of A1ARs calculated by Logan plot and two-tissue compartment model (2TCM).Compared with the AIF, the IDIF with VOI over heart showed the best performance among the three IDIFs after scaling by 1.77 (α) in terms of visual analysis, AUC ratios (IDIF / AIF, whole-blood AUC ratio 1.03 ± 0.06, parent curve AUC ratio 1.01 ± 0.10) and VT ratios (IDIF / AIF; Logan VT ratio 1.00 ± 0.17, 2TCM VT ratio 1.00 ± 0.13) evaluation. The A1ARs distribution of average parametric images was in good accordance to autoradiography of the same mice brains.The proposed study provides evidence that IDIF with VOI over heart can replace AIF effectively for quantification of A1ARs by using PET and [18F]CPFPX in mice brains. |
536 | _ | _ | |0 G:(DE-HGF)POF3-573 |a 573 - Neuroimaging (POF3-573) |c POF3-573 |f POF III |x 0 |
588 | _ | _ | |a Dataset connected to CrossRef |
700 | 1 | _ | |0 P:(DE-Juel1)131711 |a Wedekind, Franziska |b 1 |
700 | 1 | _ | |0 P:(DE-Juel1)131691 |a Kroll, Tina |b 2 |
700 | 1 | _ | |0 P:(DE-Juel1)131712 |a Oskamp, Angela |b 3 |
700 | 1 | _ | |0 P:(DE-Juel1)133864 |a Beer, Simone |b 4 |
700 | 1 | _ | |0 P:(DE-Juel1)177611 |a Drzezga, Alexander |b 5 |
700 | 1 | _ | |0 P:(DE-Juel1)131818 |a Ermert, Johannes |b 6 |u fzj |
700 | 1 | _ | |0 P:(DE-Juel1)166419 |a Neumaier, Bernd |b 7 |
700 | 1 | _ | |0 P:(DE-Juel1)131672 |a Bauer, Andreas |b 8 |
700 | 1 | _ | |0 P:(DE-Juel1)131679 |a Elmenhorst, David |b 9 |e Corresponding author |
773 | _ | _ | |0 PERI:(DE-600)2564217-0 |a 10.3389/fphys.2019.01617 |g Vol. 10, p. 1617 |p 1617 |t Frontiers in physiology |v 10 |x 1664-042X |y 2020 |
856 | 4 | _ | |u https://juser.fz-juelich.de/record/872864/files/fphys-10-01617.pdf |y OpenAccess |
856 | 4 | _ | |u https://juser.fz-juelich.de/record/872864/files/fphys-10-01617.pdf?subformat=pdfa |x pdfa |y OpenAccess |
909 | C | O | |o oai:juser.fz-juelich.de:872864 |p openaire |p open_access |p OpenAPC |p driver |p VDB |p openCost |p dnbdelivery |
910 | 1 | _ | |0 I:(DE-588b)5008462-8 |6 P:(DE-Juel1)171331 |a Forschungszentrum Jülich |b 0 |k FZJ |
910 | 1 | _ | |0 I:(DE-HGF)0 |6 P:(DE-Juel1)171331 |a 2Department of Neurophysiology, Institute of Zoology (Bio-II), RWTH Aachen University, Aachen, Germany |b 0 |
910 | 1 | _ | |0 I:(DE-588b)5008462-8 |6 P:(DE-Juel1)131711 |a Forschungszentrum Jülich |b 1 |k FZJ |
910 | 1 | _ | |0 I:(DE-588b)5008462-8 |6 P:(DE-Juel1)131691 |a Forschungszentrum Jülich |b 2 |k FZJ |
910 | 1 | _ | |0 I:(DE-588b)5008462-8 |6 P:(DE-Juel1)131712 |a Forschungszentrum Jülich |b 3 |k FZJ |
910 | 1 | _ | |0 I:(DE-588b)5008462-8 |6 P:(DE-Juel1)133864 |a Forschungszentrum Jülich |b 4 |k FZJ |
910 | 1 | _ | |0 I:(DE-588b)5008462-8 |6 P:(DE-Juel1)177611 |a Forschungszentrum Jülich |b 5 |k FZJ |
910 | 1 | _ | |0 I:(DE-HGF)0 |6 P:(DE-Juel1)177611 |a Department of Nuclear Medicine, University Hospital of Cologne, Cologne, Germany |b 5 |
910 | 1 | _ | |0 I:(DE-588b)5008462-8 |6 P:(DE-Juel1)131818 |a Forschungszentrum Jülich |b 6 |k FZJ |
910 | 1 | _ | |0 I:(DE-588b)5008462-8 |6 P:(DE-Juel1)166419 |a Forschungszentrum Jülich |b 7 |k FZJ |
910 | 1 | _ | |0 I:(DE-588b)5008462-8 |6 P:(DE-Juel1)131672 |a Forschungszentrum Jülich |b 8 |k FZJ |
910 | 1 | _ | |0 I:(DE-HGF)0 |6 P:(DE-Juel1)131672 |a Neurological Department, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany |b 8 |
910 | 1 | _ | |0 I:(DE-588b)5008462-8 |6 P:(DE-Juel1)131679 |a Forschungszentrum Jülich |b 9 |k FZJ |
910 | 1 | _ | |0 I:(DE-HGF)0 |6 P:(DE-Juel1)131679 |a Division of Medical Psychology, University of Bonn, Bonn, Germany |b 9 |
913 | 1 | _ | |0 G:(DE-HGF)POF3-573 |1 G:(DE-HGF)POF3-570 |2 G:(DE-HGF)POF3-500 |a DE-HGF |b Key Technologies |l Decoding the Human Brain |v Neuroimaging |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |
914 | 1 | _ | |y 2020 |
915 | _ | _ | |0 StatID:(DE-HGF)0200 |2 StatID |a DBCoverage |b SCOPUS |
915 | _ | _ | |0 StatID:(DE-HGF)1050 |2 StatID |a DBCoverage |b BIOSIS Previews |
915 | _ | _ | |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |a Creative Commons Attribution CC BY 4.0 |
915 | _ | _ | |0 StatID:(DE-HGF)0100 |2 StatID |a JCR |b FRONT PHYSIOL : 2017 |
915 | _ | _ | |0 StatID:(DE-HGF)0501 |2 StatID |a DBCoverage |b DOAJ Seal |
915 | _ | _ | |0 StatID:(DE-HGF)0500 |2 StatID |a DBCoverage |b DOAJ |
915 | _ | _ | |0 StatID:(DE-HGF)0111 |2 StatID |a WoS |b Science Citation Index Expanded |
915 | _ | _ | |0 StatID:(DE-HGF)0150 |2 StatID |a DBCoverage |b Web of Science Core Collection |
915 | _ | _ | |0 StatID:(DE-HGF)9900 |2 StatID |a IF < 5 |
915 | _ | _ | |0 StatID:(DE-HGF)0510 |2 StatID |a OpenAccess |
915 | _ | _ | |0 StatID:(DE-HGF)0030 |2 StatID |a Peer Review |b DOAJ : Blind peer review |
915 | _ | _ | |0 StatID:(DE-HGF)0310 |2 StatID |a DBCoverage |b NCBI Molecular Biology Database |
915 | _ | _ | |0 StatID:(DE-HGF)0300 |2 StatID |a DBCoverage |b Medline |
915 | _ | _ | |0 StatID:(DE-HGF)0320 |2 StatID |a DBCoverage |b PubMed Central |
915 | _ | _ | |0 StatID:(DE-HGF)0199 |2 StatID |a DBCoverage |b Clarivate Analytics Master Journal List |
920 | _ | _ | |l yes |
920 | 1 | _ | |0 I:(DE-Juel1)INM-2-20090406 |k INM-2 |l Molekulare Organisation des Gehirns |x 0 |
920 | 1 | _ | |0 I:(DE-Juel1)INM-5-20090406 |k INM-5 |l Nuklearchemie |x 1 |
980 | _ | _ | |a journal |
980 | _ | _ | |a VDB |
980 | _ | _ | |a UNRESTRICTED |
980 | _ | _ | |a I:(DE-Juel1)INM-2-20090406 |
980 | _ | _ | |a I:(DE-Juel1)INM-5-20090406 |
980 | _ | _ | |a APC |
980 | 1 | _ | |a APC |
980 | 1 | _ | |a FullTexts |
Library | Collection | CLSMajor | CLSMinor | Language | Author |
---|