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Feasibility of Computed Tomography-Guided Methods for Spatial Normalization of Dopamine Transporter Positron Emission Tomography Image

DC Field Value Language
dc.contributor.author류철형-
dc.contributor.author유영훈-
dc.contributor.author이명식-
dc.contributor.author조한나-
dc.date.accessioned2016-02-04T11:29:28Z-
dc.date.available2016-02-04T11:29:28Z-
dc.date.issued2015-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/140541-
dc.description.abstractBACKGROUND: Spatial normalization is a prerequisite step for analyzing positron emission tomography (PET) images both by using volume-of-interest (VOI) template and voxel-based analysis. Magnetic resonance (MR) or ligand-specific PET templates are currently used for spatial normalization of PET images. We used computed tomography (CT) images acquired with PET/CT scanner for the spatial normalization for [18F]-N-3-fluoropropyl-2-betacarboxymethoxy-3-beta-(4-iodophenyl) nortropane (FP-CIT) PET images and compared target-to-cerebellar standardized uptake value ratio (SUVR) values with those obtained from MR- or PET-guided spatial normalization method in healthy controls and patients with Parkinson's disease (PD). METHODS: We included 71 healthy controls and 56 patients with PD who underwent [18F]-FP-CIT PET scans with a PET/CT scanner and T1-weighted MR scans. Spatial normalization of MR images was done with a conventional spatial normalization tool (cvMR) and with DARTEL toolbox (dtMR) in statistical parametric mapping software. The CT images were modified in two ways, skull-stripping (ssCT) and intensity transformation (itCT). We normalized PET images with cvMR-, dtMR-, ssCT-, itCT-, and PET-guided methods by using specific templates for each modality and measured striatal SUVR with a VOI template. The SUVR values measured with FreeSurfer-generated VOIs (FSVOI) overlaid on original PET images were also used as a gold standard for comparison. RESULTS: The SUVR values derived from all four structure-guided spatial normalization methods were highly correlated with those measured with FSVOI (P < 0.0001). Putaminal SUVR values were highly effective for discriminating PD patients from controls. However, the PET-guided method excessively overestimated striatal SUVR values in the PD patients by more than 30% in caudate and putamen, and thereby spoiled the linearity between the striatal SUVR values in all subjects and showed lower disease discrimination ability. Two CT-guided methods showed comparable capability with the MR-guided methods in separating PD patients from controls and showed better correlation between putaminal SUVR values and the parkinsonian motor severity than the PET-guided method. CONCLUSION: CT-guided spatial normalization methods provided reliable striatal SUVR values comparable to those obtained with MR-guided methods. CT-guided methods can be useful for analyzing dopamine transporter PET images when MR images are unavailable.-
dc.description.statementOfResponsibilityopen-
dc.format.extente0132585-
dc.relation.isPartOfPLOS ONE-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/2.0/kr/-
dc.subject.MESHAged-
dc.subject.MESHCerebellum*/diagnostic imaging-
dc.subject.MESHCerebellum*/metabolism-
dc.subject.MESHDopamine Plasma Membrane Transport Proteins/metabolism*-
dc.subject.MESHFemale-
dc.subject.MESHHumans-
dc.subject.MESHMale-
dc.subject.MESHMiddle Aged-
dc.subject.MESHParkinson Disease*/diagnostic imaging-
dc.subject.MESHParkinson Disease*/metabolism-
dc.subject.MESHPositron-Emission Tomography/methods*-
dc.subject.MESHRadiography-
dc.subject.MESHTropanes/administration & dosage*-
dc.titleFeasibility of Computed Tomography-Guided Methods for Spatial Normalization of Dopamine Transporter Positron Emission Tomography Image-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Nuclear Medicine (핵의학)-
dc.contributor.googleauthorJin Su Kim-
dc.contributor.googleauthorHanna Cho-
dc.contributor.googleauthorJae Yong Choi-
dc.contributor.googleauthorSeung Ha Lee-
dc.contributor.googleauthorYoung Hoon Ryu-
dc.contributor.googleauthorChul Hyoung Lyoo-
dc.contributor.googleauthorMyung Sik Lee-
dc.identifier.doi10.1371/journal.pone.0132585-
dc.admin.authorfalse-
dc.admin.mappingfalse-
dc.contributor.localIdA01333-
dc.contributor.localIdA02485-
dc.contributor.localIdA02753-
dc.contributor.localIdA03920-
dc.relation.journalcodeJ02540-
dc.identifier.eissn1932-6203-
dc.identifier.pmid26147749-
dc.contributor.alternativeNameLyoo, Chul Hyoung-
dc.contributor.alternativeNameRyu, Young Hoon-
dc.contributor.alternativeNameLee, Myung Sik-
dc.contributor.alternativeNameCho, Hanna-
dc.contributor.affiliatedAuthorLyoo, Chul Hyoung-
dc.contributor.affiliatedAuthorRyu, Young Hoon-
dc.contributor.affiliatedAuthorLee, Myung Sik-
dc.contributor.affiliatedAuthorCho, Hanna-
dc.rights.accessRightsfree-
dc.citation.volume10-
dc.citation.number7-
dc.citation.startPagee0132585-
dc.identifier.bibliographicCitationPLOS ONE, Vol.10(7) : e0132585, 2015-
dc.identifier.rimsid30161-
dc.type.rimsART-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Neurology (신경과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Nuclear Medicine (핵의학교실) > 1. Journal Papers

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