2024
Noninvasive quantification of [18F]SynVesT-1 binding using simplified reference tissue model 2
Naganawa M, Gallezot J, Li S, Nabulsi N, Henry S, Cai Z, Matuskey D, Huang Y, Carson R. Noninvasive quantification of [18F]SynVesT-1 binding using simplified reference tissue model 2. European Journal Of Nuclear Medicine And Molecular Imaging 2024, 1-9. PMID: 39155309, DOI: 10.1007/s00259-024-06885-6.Peer-Reviewed Original ResearchPositron emission tomographyCentrum semiovaleReference regionPositron emission tomography scanTest-retest variabilityTest-retest reproducibilitySynaptic vesicle glycoprotein 2AOne-tissue compartmentArterial blood samplesRetest scansGold standardBrain uptakeEmission tomographyBlood samplesCerebellumNoninvasive quantificationSRTM2ConclusionOur findingsPopulation averageHealthy participantsMetabolite analysisScan timeBPNDSemiovaleTranslational PET Imaging of HDAC6 Using 18F-Bavarostat in PTSD
Bonomi R, Girgenti M, Naganawa M, Matuskey D, Cosgrove K. Translational PET Imaging of HDAC6 Using 18F-Bavarostat in PTSD. Biological Psychiatry 2024, 95: s40-s41. DOI: 10.1016/j.biopsych.2024.02.102.Peer-Reviewed Original ResearchAuthor Correction: Synaptic loss and its association with symptom severity in Parkinson’s disease
Holmes S, Honhar P, Tinaz S, Naganawa M, Hilmer A, Gallezot J, Dias M, Yang Y, Toyonaga T, Esterlis I, Mecca A, Van Dyck C, Henry S, Ropchan J, Nabulsi N, Louis E, Comley R, Finnema S, Carson R, Matuskey D. Author Correction: Synaptic loss and its association with symptom severity in Parkinson’s disease. Npj Parkinson's Disease 2024, 10: 55. PMID: 38472206, PMCID: PMC10933370, DOI: 10.1038/s41531-024-00674-6.Peer-Reviewed Original ResearchSynaptic density patterns in early Alzheimer’s disease assessed by independent component analysis
Fang X, Raval N, O’Dell R, Naganawa M, Mecca A, Chen M, van Dyck C, Carson R. Synaptic density patterns in early Alzheimer’s disease assessed by independent component analysis. Brain Communications 2024, 6: fcae107. PMID: 38601916, PMCID: PMC11004947, DOI: 10.1093/braincomms/fcae107.Peer-Reviewed Original ResearchMedial temporal brain regionsAlzheimer's diseaseTemporal brain regionsCognitive deficitsBrain regionsCognitive impairmentPostmortem studiesBinds to SV2ASynaptic densityReduction of synaptic densityIndependent component analysisSynaptic lossAlzheimerDeficitsImpairmentBrainNeocortexComponent analysisPrimary pathologySV2ASynaptic loss and its association with symptom severity in Parkinson’s disease
Holmes S, Honhar P, Tinaz S, Naganawa M, Hilmer A, Gallezot J, Dias M, Yang Y, Toyonaga T, Esterlis I, Mecca A, Van Dyck C, Henry S, Ropchan J, Nabulsi N, Louis E, Comley R, Finnema S, Carson R, Matuskey D. Synaptic loss and its association with symptom severity in Parkinson’s disease. Npj Parkinson's Disease 2024, 10: 42. PMID: 38402233, PMCID: PMC10894197, DOI: 10.1038/s41531-024-00655-9.Peer-Reviewed Original ResearchSynaptic density lossPositron emission tomographyBinds to synaptic vesicle glycoprotein 2AAssociated with symptom severityParkinson's diseaseHigh-resolution positron emission tomographySynaptic vesicle glycoprotein 2ADuration of illnessPositron emission tomography scanBrain perfusionIllness durationSymptom severitySeverity of symptomsHC groupSubstantia nigraSynaptic densityLiving brainPD individualsClinical insightsDensity lossPD patientsEmission tomographyBrainSynaptic lossSynapse lossFirst-in-Human Study of 18F-SynVesT-2: An SV2A PET Imaging Probe with Fast Brain Kinetics and High Specific Binding
Drake L, Wu Y, Naganawa M, Asch R, Zheng C, Najafzadeh S, Pracitto R, Lindemann M, Li S, Ropchan J, Labaree D, Emery P, Dias M, Henry S, Nabulsi N, Matuskey D, Hillmer A, Gallezot J, Carson R, Cai Z, Huang Y. First-in-Human Study of 18F-SynVesT-2: An SV2A PET Imaging Probe with Fast Brain Kinetics and High Specific Binding. Journal Of Nuclear Medicine 2024, 65: jnumed.123.266470. PMID: 38360052, PMCID: PMC10924160, DOI: 10.2967/jnumed.123.266470.Peer-Reviewed Original ResearchFirst-in-human studyPlasma free fractionTime-activity curvesCentrum semiovaleNonhuman primate's resultsFirst-in-humanFree fractionNondisplaceable binding potentialRegional time-activity curvesLow nonspecific uptakeRegional distribution volumesHigh-resolution research tomograph scannerTest-retest reproducibilityCerebral blood flowSynaptic vesicle glycoprotein 2AHealthy volunteersArterial input functionNonspecific uptakePET imaging probeDistribution volumeSynapse densityIndividual MR imagesHighest specific bindingMR imagingPET imaging
2023
Markerless head motion tracking and event-by-event correction in brain PET
Zeng T, Lu Y, Jiang W, Zheng J, Zhang J, Gravel P, Wan Q, Fontaine K, Mulnix T, Jiang Y, Yang Z, Revilla E, Naganawa M, Toyonaga T, Henry S, Zhang X, Cao T, Hu L, Carson R. Markerless head motion tracking and event-by-event correction in brain PET. Physics In Medicine And Biology 2023, 68: 245019. PMID: 37983915, PMCID: PMC10713921, DOI: 10.1088/1361-6560/ad0e37.Peer-Reviewed Original ResearchConceptsPoint source studyHead motion correctionSmaller residual displacementMotion correctionIterative closest point (ICP) registration algorithmHead motion trackingSpatial resolutionResidual displacementData-driven evaluation methodHigh spatial resolutionLow noiseMotion trackingStereovision cameraMotion tracking deviceStructured lightEvent correctionBrain positron emission tomography (PET) imagingTracking deviceReconstruction resultsHMT methodPoint cloudsNegative biasReference cloudUMTEvaluation methodDose reduction in dynamic synaptic vesicle glycoprotein 2A PET imaging using artificial neural networks
Li A, Yang B, Naganawa M, Fontaine K, Toyonaga T, Carson R, Tang J. Dose reduction in dynamic synaptic vesicle glycoprotein 2A PET imaging using artificial neural networks. Physics In Medicine And Biology 2023, 68: 245006. PMID: 37857316, PMCID: PMC10739622, DOI: 10.1088/1361-6560/ad0535.Peer-Reviewed Original ResearchThe regional pattern of age-related synaptic loss in the human brain differs from gray matter volume loss: in vivo PET measurement with [11C]UCB-J
Toyonaga T, Khattar N, Wu Y, Lu Y, Naganawa M, Gallezot J, Matuskey D, Mecca A, Pittman B, Dias M, Nabulsi N, Finnema S, Chen M, Arnsten A, Radhakrishnan R, Skosnik P, D’Souza D, Esterlis I, Huang Y, van Dyck C, Carson R. The regional pattern of age-related synaptic loss in the human brain differs from gray matter volume loss: in vivo PET measurement with [11C]UCB-J. European Journal Of Nuclear Medicine And Molecular Imaging 2023, 51: 1012-1022. PMID: 37955791, DOI: 10.1007/s00259-023-06487-8.Peer-Reviewed Original ResearchSynaptic densityAge-related decreaseMagnetic resonance imagingBlood flowAge-related synaptic lossGray matter volume lossSynaptic density lossPositron emission tomography (PET) ligandSynaptic vesicle glycoprotein 2AVivo PET measurementsMedial occipital cortexGray matter volumeAge-related neurodegenerationGray matter regionsCognitive normal subjectsAge-related changesSynaptic lossNerve terminalsWide age rangeOccipital cortexTomography ligandNormal subjectsGM volumeAge-related functional lossesMatter volumeUnsupervised Deep Learning with Self-Validation in Dynamic PET Dose Reduction
Li A, Syed M, Naganawa M, Matuskery D, Carson R, Tang J. Unsupervised Deep Learning with Self-Validation in Dynamic PET Dose Reduction. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10337886.Peer-Reviewed Original ResearchNoise reductionSingle-frame methodsImage featuresImage framesTraining dataUnsupervised methodSpatiotemporal informationKinetic modelingDeep imageDynamic PETHard thresholdComposite imageBetter performanceImagesRobust performanceHigh noiseImaging dataFrame methodVast numberKinetic modeling analysisNoise levelFrameSelf-ValidationDynamic PET imagingCapabilityFast Reconstruction Enhances Deep Learning PET Head Motion Correction
Zeng T, Chen F, Zhang J, Lieffrig E, Cai Z, Naganawa M, You C, Lu Y, Onofrey J. Fast Reconstruction Enhances Deep Learning PET Head Motion Correction. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10338189.Peer-Reviewed Original ResearchFast Reconstruction for Deep Learning PET Head Motion Correction
Zeng T, Zhang J, Lieffrig E, Cai Z, Chen F, You C, Naganawa M, Lu Y, Onofrey J. Fast Reconstruction for Deep Learning PET Head Motion Correction. Lecture Notes In Computer Science 2023, 14229: 710-719. PMID: 38174207, PMCID: PMC10758999, DOI: 10.1007/978-3-031-43999-5_67.Peer-Reviewed Original ResearchEvaluating infusion methods and simplified quantification of synaptic density in vivo with [11C]UCB-J and [18F]SynVesT-1 PET
Asch R, Naganawa M, Nabulsi N, Huan Y, Esterlis I, Carson R. Evaluating infusion methods and simplified quantification of synaptic density in vivo with [11C]UCB-J and [18F]SynVesT-1 PET. Cerebrovascular And Brain Metabolism Reviews 2023, 43: 2120-2129. PMID: 37669455, PMCID: PMC10925870, DOI: 10.1177/0271678x231200423.Peer-Reviewed Original ResearchPET Quantification and Kinetic Analysis
Carson R, Naganawa M, Gallezot J. PET Quantification and Kinetic Analysis. 2023, 183-194. DOI: 10.1007/978-3-031-35098-6_12.ChaptersMathematical modelingLinearized techniqueModel simplificationApplication of modelingApplication of modelsModeling techniquesModel validationTracer kinetic modeling techniquesEquationsInput functionModelingKinetic modeling techniquesModelCompartment modelOptimizationAlternative approachAccurate measurementApplicationsSimplificationDynamicsPrincipal component analysis of synaptic density measured with [11C]UCB-J PET in early Alzheimer’s disease
O'Dell R, Higgins-Chen A, Gupta D, Chen M, Naganawa M, Toyonaga T, Lu Y, Ni G, Chupak A, Zhao W, Salardini E, Nabulsi N, Huang Y, Arnsten A, Carson R, van Dyck C, Mecca A. Principal component analysis of synaptic density measured with [11C]UCB-J PET in early Alzheimer’s disease. NeuroImage Clinical 2023, 39: 103457. PMID: 37422964, PMCID: PMC10338149, DOI: 10.1016/j.nicl.2023.103457.Peer-Reviewed Original ResearchConceptsCognitive domainsCognitive performanceSubjects' scoresCortical regionsNeuropsychological batteryEarly Alzheimer's diseaseAD groupBilateral regionsNormal participantsNegative loadingsCognitive impairmentCN participantsAlzheimer's diseaseParticipantsStructural correlatesStrong contributionParticipant characteristicsScoresPositive loadingsData-driven approachTotal variancePrincipal component analysisSpecific spatial patternsMultimodality Neuroimaging Biomarkers in Parkinson’s Disease
Zhang X, Mohan V, Wooten D, Hooker B, Zhuang Y, Honhar P, Holmes S, Naganawa M, Dias M, Comley R, Carson R, Tinaz S, Matuskey D, Luo Y, Finnema S. Multimodality Neuroimaging Biomarkers in Parkinson’s Disease. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2023 DOI: 10.58530/2023/2279.Peer-Reviewed Original ResearchReductions in synaptic marker SV2A in early-course Schizophrenia
Yoon J, Zhang Z, Mormino E, Davidzon G, Minzenberg M, Ballon J, Kalinowski A, Hardy K, Naganawa M, Carson R, Khalighi M, Park J, Levinson D, Chin F. Reductions in synaptic marker SV2A in early-course Schizophrenia. Journal Of Psychiatric Research 2023, 161: 213-217. PMID: 36934603, DOI: 10.1016/j.jpsychires.2023.02.026.Peer-Reviewed Original ResearchConceptsChronic patientsSynaptic pruningStage of illnessEarly course patientsEarly course schizophreniaSeverity of delusionsWidespread reductionMajor disease mechanismsSynaptic deficitsSynaptic markersSynaptic eliminationPET scansFormal onsetBrain regionsSignificant positive correlationPatientsSchizophrenia studiesSchizophreniaDisease mechanismsCognitive performanceIllnessEarly phaseSpecific bindingPresent studyPositive correlation
2022
Drug characteristics derived from kinetic modeling: combined 11C-UCB-J human PET imaging with levetiracetam and brivaracetam occupancy of SV2A
Naganawa M, Gallezot J, Finnema S, Maguire R, Mercier J, Nabulsi N, Kervyn S, Henry S, Nicolas J, Huang Y, Chen M, Hannestad J, Klitgaard H, Stockis A, Carson R. Drug characteristics derived from kinetic modeling: combined 11C-UCB-J human PET imaging with levetiracetam and brivaracetam occupancy of SV2A. EJNMMI Research 2022, 12: 71. PMID: 36346513, PMCID: PMC9643320, DOI: 10.1186/s13550-022-00944-5.Peer-Reviewed Original ResearchTime-activity curvesBrain entryDrug concentrationsNon-human primate brainAnti-seizure activitySynaptic vesicle glycoprotein 2APlasma drug concentrationsPrevious human studiesBackgroundAntiepileptic drugsHealthy subjectsBlood samplesHuman studiesLevetiracetamPrimate brainEmission tomography dataBrivaracetamDistribution volumeArterial input functionBrainDrug characteristicsPositron emission tomography dataDrug entryFree fractionDrugsKinetic parameters k1Imaging of Synaptic Density in Neurodegenerative Disorders
Carson RE, Naganawa M, Toyonaga T, Koohsari S, Yang Y, Chen MK, Matuskey D, Finnema SJ. Imaging of Synaptic Density in Neurodegenerative Disorders. Journal Of Nuclear Medicine 2022, 63: 60s-67s. PMID: 35649655, DOI: 10.2967/jnumed.121.263201.Peer-Reviewed Original ResearchConceptsSynaptic densityAlzheimer's diseaseNeurodegenerative disordersNeurodegenerative diseasesSynaptic vesicle protein 2APotential reference regionsSynaptic density lossLewy body dementiaProgressive supranuclear palsyDisease-modifying therapiesSpecific brain proteinsLarge patient cohortAntiepileptic drug levetiracetamPET imaging resultsMultiple neurodegenerative disordersSynaptic lossSupranuclear palsyCorticobasal degenerationNeuropathologic diseasePatient cohortRat modelClinical valueF-FDGParkinson's diseaseEfficacy assessmentAdaptive data-driven motion detection and optimized correction for brain PET
Revilla EM, Gallezot JD, Naganawa M, Toyonaga T, Fontaine K, Mulnix T, Onofrey JA, Carson RE, Lu Y. Adaptive data-driven motion detection and optimized correction for brain PET. NeuroImage 2022, 252: 119031. PMID: 35257856, PMCID: PMC9206767, DOI: 10.1016/j.neuroimage.2022.119031.Peer-Reviewed Original ResearchConceptsDetection algorithmMotion correction methodMotion tracking informationExternal motion tracking devicesMotion detection algorithmMotion tracking methodImage registration algorithmHead motionReal human datasetsData-driven methodUser-defined parametersImage quality degradationMotion tracking deviceMultiple usersDynamic datasetsTracking informationManual interventionRegistration algorithmMotion detectionTracking methodComparable performanceAlgorithmQuality degradationHuman datasetsTracking device