2024
PET imaging of M4 muscarinic acetylcholine receptors in rhesus macaques using [11C]MK-6884: Quantification with kinetic modeling and receptor occupancy by CVL-231 (emraclidine), a novel positive allosteric modulator
Belov V, Guehl N, Duvvuri S, Iredale P, Moon S, Dhaynaut M, Chakilam S, MacDonagh A, Rice P, Yokell D, Renger J, Fakhri G, Normandin M. PET imaging of M4 muscarinic acetylcholine receptors in rhesus macaques using [11C]MK-6884: Quantification with kinetic modeling and receptor occupancy by CVL-231 (emraclidine), a novel positive allosteric modulator. Cerebrovascular And Brain Metabolism Reviews 2024, 44: 1329-1342. PMID: 38477292, PMCID: PMC11342722, DOI: 10.1177/0271678x241238820.Peer-Reviewed Original ResearchConceptsPositive allosteric modulatorsReceptor occupancyNon-human primatesBinding potentialPositron emission tomographyMuscarinic acetylcholine receptorsAllosteric modulatorsNon-human primate brainM4 muscarinic acetylcholine receptorStriatal hyperdopaminergiaAcetylcholine receptorsBrain regionsCaudate nucleusTotal volume of distributionDose-dependent blockReference regionVolume of distributionPositron emission tomography imagingEmission tomographyReceptor levelsFunction of dosePET scansClinical trialsBlood-basedRhesus macaques
2022
Kinetic evaluation and assessment of longitudinal changes in reference region and extracerebral [18F]MK-6240 PET uptake
Fu J, Lois C, Sanchez J, Becker J, Rubinstein Z, Thibault E, Salvatore A, Sari H, Farrell M, Guehl N, Normandin M, Fakhri G, Johnson K, Price J. Kinetic evaluation and assessment of longitudinal changes in reference region and extracerebral [18F]MK-6240 PET uptake. Cerebrovascular And Brain Metabolism Reviews 2022, 43: 581-594. PMID: 36420769, PMCID: PMC10063833, DOI: 10.1177/0271678x221142139.Peer-Reviewed Original ResearchConceptsPartial volume correctionLongitudinal changesReference regionStandardized uptake valueFollow-up scansExtracerebral signalsAssessment of longitudinal changesCross-sectional effect sizesUptake valuePET uptakeDistribution volumeRegional uptakeArterial samplesExtracerebral contaminationOne-yearCognitively-normalEffect sizePonsGroup differentiationVolume correctionSubject levelSubjects
2017
Pseudoreference Regions for Glial Imaging with 11C-PBR28: Investigation in 2 Clinical Cohorts
Albrecht D, Normandin M, Shcherbinin S, Wooten D, Schwarz A, Zürcher N, Barth V, Guehl N, Akeju O, Atassi N, Veronese M, Turkheimer F, Hooker J, Loggia M. Pseudoreference Regions for Glial Imaging with 11C-PBR28: Investigation in 2 Clinical Cohorts. Journal Of Nuclear Medicine 2017, 59: 107-114. PMID: 28818984, PMCID: PMC5750517, DOI: 10.2967/jnumed.116.178335.Peer-Reviewed Original ResearchConceptsChronic low back painPseudoreference regionGroup differencesDistribution volume ratioOccipital cortexArterial input functionChronic low back pain patientsAbsence of group differencesNo significant group differencesTranslocator protein imagingLow back painRegional group differencesSignificant group differencesAmyotrophic lateral sclerosisTranslocator proteinMatched healthy controlsDetect group differencesWithin-group variabilityBack painNeuroimmune activationVoxelwise analysisPET scansHealthy controlsClinical cohortDistribution volume
2016
A Bayesian spatial temporal mixtures approach to kinetic parametric images in dynamic positron emission tomography
Zhu W, Ouyang J, Rakvongthai Y, Guehl N, Wooten D, Fakhri G, Normandin M, Fan Y. A Bayesian spatial temporal mixtures approach to kinetic parametric images in dynamic positron emission tomography. Medical Physics 2016, 43: 1222-1234. PMID: 26936707, PMCID: PMC5025019, DOI: 10.1118/1.4941010.Peer-Reviewed Original ResearchConceptsPositron emission tomographySpatial mixture modelNearby voxelsMixture modelEmission tomographyDynamic positron emission tomographyK-means methodKinetic modelKinetic parametric imagesOne-compartment kinetic modelNovel algorithmTemporal informationClassification purposesMeasurement of local perfusionLocal perfusionTime activity curvesNormal ROIsTemporal modelBayesian algorithmCardiac studiesMarkov chain Monte CarloParameter estimationNoise regionSimulation experimentsSimulated data sets
2012
Selection of weighting factors for quantification of PET radioligand binding using simplified reference tissue models with noisy input functions
Normandin M, Koeppe R, Morris E. Selection of weighting factors for quantification of PET radioligand binding using simplified reference tissue models with noisy input functions. Physics In Medicine And Biology 2012, 57: 609-629. PMID: 22241524, PMCID: PMC3361066, DOI: 10.1088/0031-9155/57/3/609.Peer-Reviewed Original Research
2007
Estimating neurotransmitter kinetics with ntPET: A simulation study of temporal precision and effects of biased data
Normandin MD, Morris ED. Estimating neurotransmitter kinetics with ntPET: A simulation study of temporal precision and effects of biased data. NeuroImage 2007, 39: 1162-1179. PMID: 18023364, PMCID: PMC2271120, DOI: 10.1016/j.neuroimage.2007.09.046.Peer-Reviewed Original Research
2005
ntPET: A New Application of PET Imaging for Characterizing the Kinetics of Endogenous Neurotransmitter Release
Morris ED, Yoder KK, Wang C, Normandin MD, Zheng QH, Mock B, Raymond F, Froehlich JC. ntPET: A New Application of PET Imaging for Characterizing the Kinetics of Endogenous Neurotransmitter Release. Molecular Imaging 2005, 4: 7290.2005.05130. PMID: 16285909, DOI: 10.2310/7290.2005.05130.Peer-Reviewed Original ResearchConceptsNeurotransmitter releaseArterial blood samplingEndogenous neurotransmitter releasePositron emission tomographyEndogenous dopamineDrug treatmentRat striatumBlood samplingBlood flowEmission tomographyFalse-positive responsesD3 receptor ligandsDopamine concentrationsPET imagingReceptor ligandsNoninvasive assayTracer kinetic modelReference regionStimulus conditionsDopamine