Featured Publications
EM reconstruction algorithms for emission and transmission tomography.
Lange K, Carson R. EM reconstruction algorithms for emission and transmission tomography. Journal Of Computer Assisted Tomography 1984, 8: 306-16. PMID: 6608535.Peer-Reviewed Original ResearchConceptsEM algorithmGood physical modelTransmission image reconstructionTransmission tomographyMaximum likelihood estimatesAlgebraic schemeRelevant physical featuresNon-negativity constraintsGlobal convergenceIterative techniquePoisson natureLikelihood estimatesParameter estimatesCounting noiseMaximum likelihoodDetector geometryPhysical modelAccurate incorporationEM reconstruction algorithmPhysical featuresSpecific algorithmsImage reconstructionAlgorithmReconstruction algorithmActual reconstructionImaging synaptic density in the living human brain
Finnema SJ, Nabulsi NB, Eid T, Detyniecki K, Lin SF, Chen MK, Dhaher R, Matuskey D, Baum E, Holden D, Spencer DD, Mercier J, Hannestad J, Huang Y, Carson RE. Imaging synaptic density in the living human brain. Science Translational Medicine 2016, 8: 348ra96. PMID: 27440727, DOI: 10.1126/scitranslmed.aaf6667.Peer-Reviewed Original ResearchConceptsSynaptic densityPositron emission tomographyPET imagingSynaptic vesicle glycoprotein 2ATemporal lobe epilepsyNumerous brain disordersCentral nervous systemNumber of synapsesJ PET imagingHuman brainHuman PET studiesPredominant neuronsSurgical resectionSynaptic lossLobe epilepsyPsychiatric disordersNervous systemBrain disordersPresynaptic boutonsAlzheimer's diseaseBrain tissueEmission tomographyNeuron contactsTherapeutic monitoringPET studiesConsensus Nomenclature for in vivo Imaging of Reversibly Binding Radioligands
Innis RB, Cunningham VJ, Delforge J, Fujita M, Gjedde A, Gunn RN, Holden J, Houle S, Huang SC, Ichise M, Iida H, Ito H, Kimura Y, Koeppe RA, Knudsen GM, Knuuti J, Lammertsma AA, Laruelle M, Logan J, Maguire RP, Mintun MA, Morris ED, Parsey R, Price JC, Slifstein M, Sossi V, Suhara T, Votaw JR, Wong DF, Carson RE. Consensus Nomenclature for in vivo Imaging of Reversibly Binding Radioligands. Cerebrovascular And Brain Metabolism Reviews 2007, 27: 1533-1539. PMID: 17519979, DOI: 10.1038/sj.jcbfm.9600493.Peer-Reviewed Original ResearchFirst-in-Human Evaluation of 18F-SynVesT-1, a Radioligand for PET Imaging of Synaptic Vesicle Glycoprotein 2A
Naganawa M, Li S, Nabulsi N, Henry S, Zheng MQ, Pracitto R, Cai Z, Gao H, Kapinos M, Labaree D, Matuskey D, Huang Y, Carson RE. First-in-Human Evaluation of 18F-SynVesT-1, a Radioligand for PET Imaging of Synaptic Vesicle Glycoprotein 2A. Journal Of Nuclear Medicine 2020, 62: 561-567. PMID: 32859701, PMCID: PMC8049363, DOI: 10.2967/jnumed.120.249144.Peer-Reviewed Original ResearchConceptsC-UCBSynaptic densityRegional time-activity curvesTime-activity curvesDistribution volumeMetabolite-corrected arterial input functionPET imagingMultilinear analysis 1Synaptic vesicle glycoprotein 2AAntiepileptic drug levetiracetamTotal distribution volumeNondisplaceable distribution volumeCentrum semiovaleBlocking doseHealthy volunteersHuman studiesDrug levetiracetamLassen plotNeuropsychiatric disordersPET radioligandArterial input functionNonhuman primatesLevetiracetamReference regionRadioligandAssessing Synaptic Density in Alzheimer Disease With Synaptic Vesicle Glycoprotein 2A Positron Emission Tomographic Imaging
Chen MK, Mecca AP, Naganawa M, Finnema SJ, Toyonaga T, Lin SF, Najafzadeh S, Ropchan J, Lu Y, McDonald JW, Michalak HR, Nabulsi NB, Arnsten AFT, Huang Y, Carson RE, van Dyck CH. Assessing Synaptic Density in Alzheimer Disease With Synaptic Vesicle Glycoprotein 2A Positron Emission Tomographic Imaging. JAMA Neurology 2018, 75: 1215-1224. PMID: 30014145, PMCID: PMC6233853, DOI: 10.1001/jamaneurol.2018.1836.Peer-Reviewed Original ResearchConceptsPositron emission tomographic imagingSynaptic vesicle glycoprotein 2ASynaptic densityAlzheimer's diseaseEmission tomographic imagingHigh-resolution PET scanningPET scanningCognitive impairmentDisease-modifying therapiesDisease-modifying treatmentsNormal participantsCross-sectional studyPittsburgh compound BMajor structural correlateAmnestic mild cognitive impairmentMagnetic resonance imagingMild cognitive impairmentJ PET imagingRestoration of synapsesSpecific bindingNeurologic evaluationSynaptic lossDisease stagePostmortem studiesOutcome measuresReduced synaptic vesicle protein 2A binding in temporal lobe epilepsy: A [11C]UCB‐J positron emission tomography study
Finnema SJ, Toyonaga T, Detyniecki K, Chen M, Dias M, Wang Q, Lin S, Naganawa M, Gallezot J, Lu Y, Nabulsi NB, Huang Y, Spencer DD, Carson RE. Reduced synaptic vesicle protein 2A binding in temporal lobe epilepsy: A [11C]UCB‐J positron emission tomography study. Epilepsia 2020, 61: 2183-2193. PMID: 32944949, DOI: 10.1111/epi.16653.Peer-Reviewed Original ResearchConceptsMedial temporal lobe sclerosisTemporal lobe epilepsyTLE subjectsPositron emission tomographyLobe epilepsyJ BPSynaptic vesicle protein 2APartial volume correctionTemporal lobe sclerosisPositron emission tomography studyEmission tomography studiesSeizure onset zonePromising biomarker approachJ bindingPresurgical selectionSclerotic hippocampusHippocampal asymmetryTLE patientsRegional binding patternsControl subjectsCentrum semiovaleContralateral regionsEpilepsy patientsOutcome measuresOnset zoneLower synaptic density is associated with depression severity and network alterations
Holmes SE, Scheinost D, Finnema SJ, Naganawa M, Davis MT, DellaGioia N, Nabulsi N, Matuskey D, Angarita GA, Pietrzak RH, Duman RS, Sanacora G, Krystal JH, Carson RE, Esterlis I. Lower synaptic density is associated with depression severity and network alterations. Nature Communications 2019, 10: 1529. PMID: 30948709, PMCID: PMC6449365, DOI: 10.1038/s41467-019-09562-7.Peer-Reviewed Original ResearchConceptsMajor depressive disorderPost-traumatic stress disorderLower synaptic densitySynaptic densityPositron emission tomographyFunctional connectivityNetwork alterationsSynaptic vesicle glycoprotein 2ASymptoms of depressionSynaptic lossDepressive disorderHealthy controlsNerve terminalsDepressive symptomsDepression severityUnmedicated individualsSynaptic connectionsEmission tomographyStress disorderVivo evidenceSymptomsDepressionSeverityDisordersAlterationsNoise Reduction in the Simplified Reference Tissue Model for Neuroreceptor Functional Imaging
Wu Y, Carson RE. Noise Reduction in the Simplified Reference Tissue Model for Neuroreceptor Functional Imaging. Cerebrovascular And Brain Metabolism Reviews 2002, 22: 1440-1452. PMID: 12468889, DOI: 10.1097/01.wcb.0000033967.83623.34.Peer-Reviewed Original ResearchComparison of Bolus and Infusion Methods for Receptor Quantitation: Application to [18F]Cyclofoxy and Positron Emission Tomography
Carson R, Channing M, Blasberg R, Dunn B, Cohen R, Rice K, Herscovitch P. Comparison of Bolus and Infusion Methods for Receptor Quantitation: Application to [18F]Cyclofoxy and Positron Emission Tomography. Cerebrovascular And Brain Metabolism Reviews 1993, 13: 24-42. PMID: 8380178, DOI: 10.1038/jcbfm.1993.6.Peer-Reviewed Original ResearchQuantification of Amphetamine-Induced Changes in [11C] Raclopride Binding with Continuous Infusion
Carson R, Breier* A, de Bartolomeis* A, Saunders† R, Su* T, Schmall B, Der M, Pickar* D, Eckelman W. Quantification of Amphetamine-Induced Changes in [11C] Raclopride Binding with Continuous Infusion. Cerebrovascular And Brain Metabolism Reviews 1997, 17: 437-447. PMID: 9143226, DOI: 10.1097/00004647-199704000-00009.Peer-Reviewed Original Research
2024
Fast Energy-Based Scatter Correction for 3D TOF-PET on NeuroExplorer
Guo L, Fontaine K, Gravel P, Mulnix T, Zhang J, Liu C, Carson R. Fast Energy-Based Scatter Correction for 3D TOF-PET on NeuroExplorer. 2024, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57108.2024.10657901.Peer-Reviewed Original ResearchSingle scatter simulationScatter estimationEnergy spectrumTOF binsField of viewAxial field-of-viewHigh-energy scatteringLong axial field-of-viewLow-activity regionsList-mode dataEnergy informationTOF-PETContrast phantomUniform phantomScattering phantomCounting statisticsScatter correctionOSEM reconstructionMultiple-scatteringScatteringScattering simulationsPhantomEvent distributionImproved contrastMonte-CarloMOLAR-NX: building a PET reconstruction framework for exploring the novel features provided by the NeuroEXPLORER
Fontaine K, Gallezot J, Zhang J, He L, Gravel P, Zeng T, Li T, Li Y, Leung E, Sun X, Guo L, Mulnix T, Toyonaga T, Lu Y, Li H, Badawi R, Qi J, Carson R. MOLAR-NX: building a PET reconstruction framework for exploring the novel features provided by the NeuroEXPLORER. 2024, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57108.2024.10655187.Peer-Reviewed Original ResearchReconstruction processDepth of interactionReconstruction frameworkAdvanced frameworkFramework's effectivenessMask featuresNovel featuresContrast recoveryScatter correction methodReconstruction softwareFrameworkListmode dataDownsamplingMotion correctionPhantom studyListmode filesFeaturesCorrection methodSoftwareFilesNeuroExplorerReconstructionLarge human cohort study of markerless head motion tracking for brain PET
Zeng T, Zhang J, Gallezot J, Fontaine K, Gravel P, Jiang W, Mulnix T, Yang Z, Zhang X, Hu L, Carson R. Large human cohort study of markerless head motion tracking for brain PET. 2024, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57108.2024.10656091.Peer-Reviewed Original ResearchPost-reconstruction registrationEvent-by-eventBrain PET imagingMotion correction techniqueQuantitative PET imagingPET imagingBrain PETHead motionTime activity curvesStudy of brain functionImage qualityMotion tracking systemGray matter regionsCorrection techniqueMotionHuman cohort studiesAverage SUVPET measurementsMotion blurMatter regionsSuperior performanceTracking systemPolarisComparative analysis of two parametric imaging programs for NeuroEXPLORER studies
Zhang J, Gallezot J, Ye Q, Lu Y, Carson R. Comparative analysis of two parametric imaging programs for NeuroEXPLORER studies. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10655797.Peer-Reviewed Original ResearchHigh-resolution brain phantom data, with flexible contrast: Validation on the NeuroExplorer (NX)
Gravel P, Toyonaga T, Gallezot J, Fontaine K, Martins S, Mulnix T, Carson R. High-resolution brain phantom data, with flexible contrast: Validation on the NeuroExplorer (NX). 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10656366.Peer-Reviewed Original ResearchQuantitative accuracyPhantom dataSpatial resolutionIterative reconstruction algorithmListmode dataAttenuation correctionPhantom studyPhantomResolution measurementsAttenuation propertiesReconstructed imagesReconstruction algorithmPET imagingCorrection accuracyResolutionScatteringAxial directionAttenuationContrastCorrectionMotion correction quality control of markerless head motion tracking for ultrahigh performance brain PET
Zeng T, Zhang J, Volpi T, Gallezot J, Fontaine K, Khattar N, Jiang W, Yang Z, Wan Q, Wang S, Li T, Zhang X, Hu L, Carson R. Motion correction quality control of markerless head motion tracking for ultrahigh performance brain PET. 2024, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57108.2024.10658040.Peer-Reviewed Original ResearchBrain PET studiesMotion correctionMotion-free imagesImpact of motionPET systemCombined metricImage qualityResolution degradationBrain PETGating methodPET dataFacial expression experimentsSpatial resolutionDetect facial expressionsNon-rigid movementEnhanced image qualityHuman scansGateMotion blurPET studiesMotion tracking systemPlanned motionTracking failureMotionNeuroimaging studiesAdaptive Deep Image Prior Enhances Ultra-Low Dose PET Imaging with NeuroEXPLORER
Li A, Gravel P, Gallezot J, Toyonaga T, Fontaine K, Carson R, Tang J. Adaptive Deep Image Prior Enhances Ultra-Low Dose PET Imaging with NeuroEXPLORER. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10657691.Peer-Reviewed Original ResearchContrast recovery coefficientCounting imagingLearning-based denoising methodsHead motion correctionDeep Image PriorLow-dose imagesOptimal stopping iterationsDose imagesAttenuation mapBrain phantomDeep imagingFull-count dataImage priorsMotion correctionSignal-to-noise ratioDenoising methodSequence of outputsTraining dataPET imagingStopping iterationDecreased signal-to-noise ratioNoise ratioPost-processing techniquesReconstructed imagesRecovery coefficientGeneration of Synthetic brain PET images of synaptic density from MRI and FDG-PET using a Multi-stage U-Net
Zheng X, Worhunsky P, Liu Q, Zhou B, Chen X, Guo X, Xie H, Sun H, Zhang J, Toyonaga T, Mecca A, O’Dell R, van Dyck C, Carson R, Radhakrishnan R, Liu C. Generation of Synthetic brain PET images of synaptic density from MRI and FDG-PET using a Multi-stage U-Net. 2024, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57108.2024.10655600.Peer-Reviewed Original ResearchImage-Derived Input Functions on an Ultra-High Performance Brain PET Scanner: Minimizing the Carotid Partial Volume Effect
Volpi T, Zeng T, Khattar N, Toyonaga T, Martins S, Mulnix T, Fontaine K, Gallezot J, Carson R. Image-Derived Input Functions on an Ultra-High Performance Brain PET Scanner: Minimizing the Carotid Partial Volume Effect. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10658264.Peer-Reviewed Original ResearchPatlak-Guided Self-Supervised Learning for Dynamic PET Denoising
Liu Q, Guo X, Tsai Y, Gallezot J, Chen M, Guo L, Xie H, Pucar D, Young C, Panin V, Carson R, Liu C. Patlak-Guided Self-Supervised Learning for Dynamic PET Denoising. 2024, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57108.2024.10655866.Peer-Reviewed Original ResearchPre-trained modelsSelf-supervised learning methodSuperior noise reductionNoise reductionDynamic framesImage quality improvementUpsampling blockSignal-to-noise ratioWeight initializationWeak supervisionDynamic PET datasetsEnhanced noise reductionUNet modelLearning methodsTraining schemeTemporal dataStatic imagesDenoisingReconstruction methodPET datasetsLesion signal-to-noise ratioSize constraintsLesion SNRImagesRecon