2017
Application of a Novel CD206+ Macrophage-Specific Arterial Imaging Strategy in HIV-Infected Individuals
Zanni M, Toribio M, Wilks M, Lu M, Burdo T, Walker J, Autissier P, Foldyna B, Stone L, Martin A, Cope F, Abbruzzese B, Brady T, Hoffmann U, Williams K, El-Fakhri G, Grinspoon S. Application of a Novel CD206+ Macrophage-Specific Arterial Imaging Strategy in HIV-Infected Individuals. The Journal Of Infectious Diseases 2017, 215: 1264-1269. PMID: 28204544, PMCID: PMC5853590, DOI: 10.1093/infdis/jix095.Peer-Reviewed Original ResearchMeSH KeywordsAortaAtherosclerosisCase-Control StudiesCross-Sectional StudiesDextransHIV InfectionsHumansLectins, C-TypeLymph NodesMacrophagesMaleMannansMannose ReceptorMannose-Binding LectinsMiddle AgedPlaque, AtheroscleroticRadiopharmaceuticalsReceptors, Cell SurfaceRegression AnalysisSingle Photon Emission Computed Tomography Computed TomographyTechnetium Tc 99m PentetateUnited StatesConceptsSingle-photon emission computed tomography/computed tomographyFirst-in-human dataNon-HIV-infected subjectsAortic plaque volumeHIV-infected subjectsHIV-infected individualsMacrophages ex vivoComputed tomographic angiographyCD206+ macrophagesTomography/computed tomographyTomographic angiographyImaging techniquesTechnetium TcHIV statusPlaque volumeCardiovascular diseaseHIVImaging strategiesCD206In vivo applicationsSubjectsTilmanoceptAngiographyMacrophagesTomography
2015
A Spectral Graph Regression Model for Learning Brain Connectivity of Alzheimer’s Disease
Hu C, Cheng L, Sepulcre J, Johnson K, Fakhri G, Lu Y, Li Q. A Spectral Graph Regression Model for Learning Brain Connectivity of Alzheimer’s Disease. PLOS ONE 2015, 10: e0128136. PMID: 26024224, PMCID: PMC4449104, DOI: 10.1371/journal.pone.0128136.Peer-Reviewed Original ResearchConceptsNetwork featuresAlzheimer's diseaseConsistent with known pathologyUnknown graphConnection weightsReconstruction networkCortical hubsDegree statisticsData modelSmooth signalsFeatures of brain pathologyOptimization frameworkAmyloid-bPartial correlation estimationImage dataNetworkGraphGlobal connectivity measuresPositron emission tomographyConnectivity measuresNeurodegenerative diseasesConnectivity patternsSample correlationClinical ADSimulated data
2014
4D numerical observer for lesion detection in respiratory‐gated PET
Lorsakul A, Li Q, Trott C, Hoog C, Petibon Y, Ouyang J, Laine A, Fakhri G. 4D numerical observer for lesion detection in respiratory‐gated PET. Medical Physics 2014, 41: 102504. PMID: 25281979, PMCID: PMC4281099, DOI: 10.1118/1.4895975.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsComputer SimulationFluorodeoxyglucose F18HumansImage Interpretation, Computer-AssistedLung DiseasesModels, BiologicalMonte Carlo MethodMotionPhantoms, ImagingPositron-Emission TomographyRadiopharmaceuticalsRegression AnalysisRespiratory-Gated Imaging TechniquesSignal-To-Noise RatioConceptsRespiratory-gated positron emission tomographyMotion-corrected imagesDetection signal-to-noise ratioLesion detection taskNumerical observationsLesion detection performanceSignal-to-noise ratioPositron emission tomography sinogramsSpherical lesionsHotelling observerMotion correction methodPositron emission tomographyGeant4 ApplicationTomographic EmissionChannelized Hotelling observerAnthropomorphic phantomScanner geometryOSEM algorithmMonte Carlo simulationsPET framesImprove lesion detectionLesion detectionSignal-to-noise ratio measurementsActivity distributionConventional 3D approach