Nicolas Guehl
Assistant Professor of Radiology and Biomedical ImagingCards
About
Research
Publications
2026
Bayesian modelling demonstrates clinically relevant heterogeneity in Tau PET patterns in Alzheimer’s disease
Xia Y, Johnson K, Fakhri G, Guehl N, van de Giessen E, Coomans E, Pijnenburg Y, Ossenkoppele R, Groot C. Bayesian modelling demonstrates clinically relevant heterogeneity in Tau PET patterns in Alzheimer’s disease. European Journal Of Nuclear Medicine And Molecular Imaging 2026, 53: 4664-4676. PMID: 41915038, PMCID: PMC13197381, DOI: 10.1007/s00259-026-07868-5.Peer-Reviewed Original ResearchConceptsTemporo-parietal cortexTau patternsTau heterogeneityLimbic regionsAlzheimer's diseaseCognitive performanceFactor loadingsLeft temporo-parietal cortexCognitive declineCognitive domain scoresData-driven Bayesian modelAmyloid-positive individualsADNI cohortTau profileSlow cognitive declineCognitive domainsVisuospatial performanceLanguage scoresBaseline cognitionDevelopment of personalized therapeutic strategiesBaseline MMSEAlzheimer's Disease Neuroimaging InitiativeDevelopment of individualized treatment strategiesIndependent validation sampleTau deposition
2025
YRT-PET: An Open-Source GPU-Accelerated Image Reconstruction Engine for Positron Emission Tomography
Najmaoui Y, Chemli Y, Toussaint M, Petibon Y, Marty B, Fontaine K, Gallezot J, Razdevsek G, Orehar M, Dhaynaut M, Guehl N, Dolenec R, Pestotnik R, Johnson K, Ouyang J, Normandin M, Tetrault M, Lecomte R, Fakhri G, Marin T. YRT-PET: An Open-Source GPU-Accelerated Image Reconstruction Engine for Positron Emission Tomography. IEEE Transactions On Radiation And Plasma Medical Sciences 2025, 10: 535-546. PMID: 41424471, PMCID: PMC12714321, DOI: 10.1109/trpms.2025.3619872.Peer-Reviewed Original ResearchThis study introduces YRT-PET, an open-source GPU-accelerated software for PET image reconstruction, demonstrating high flexibility, speed, and compatibility with existing tools for dynamic imaging and motion correction.Bayesian Posterior Distribution Estimation of Kinetic Parameters in Dynamic Brain PET Using Generative Deep Learning Models
Djebra Y, Liu X, Marin T, Tiss A, Dhaynaut M, Guehl N, Johnson K, Fakhri G, Ma C, Ouyang J. Bayesian Posterior Distribution Estimation of Kinetic Parameters in Dynamic Brain PET Using Generative Deep Learning Models. IEEE Transactions On Medical Imaging 2025, 44: 5089-5102. PMID: 40663684, PMCID: PMC12318411, DOI: 10.1109/tmi.2025.3588859.Peer-Reviewed Original ResearchPosterior distributions of kinetic parametersEfficiency of deep learningGenerative deep learning modelsConditional variational autoencoderDeep learning modelsComputational efficiencyMetropolis-Hastings MCMCPosterior distributionHyperphosphorylated tauDynamic brain positron emission tomographyWGAN-GPDual decodersWasserstein GANVariational autoencoderKinetic parametersDeep learningComputational needsBayesian inferenceP-tauLearning modelsAlzheimer's diseaseNeurodegenerative diseasesComputation timeMCMC methodsEstimation of kinetic parametersQuantitative Measurement of Tau Burden in a Dual-Time-Window Dynamic PET Imaging Protocol with [18F]MK6240
Xia Y, Dhaynaut M, Chemli Y, Lois C, Hanseeuw B, Thibault E, Groot C, Ossenkoppele R, Johnson K, El Fakhri G, Normandin M, Guehl N. Quantitative Measurement of Tau Burden in a Dual-Time-Window Dynamic PET Imaging Protocol with [18F]MK6240. Journal Of Nuclear Medicine 2025, 66: 1299-1306. PMID: 40533354, PMCID: PMC12320581, DOI: 10.2967/jnumed.125.270165.Peer-Reviewed Original ResearchPET Mapping of Receptor Occupancy Using Joint Direct Parametric Reconstruction
Marin T, Belov V, Chemli Y, Ouyang J, Najmaoui Y, Fakhri G, Duvvuri S, Iredale P, Guehl N, Normandin M, Petibon Y. PET Mapping of Receptor Occupancy Using Joint Direct Parametric Reconstruction. IEEE Transactions On Biomedical Engineering 2025, 72: 1057-1066. PMID: 39446540, PMCID: PMC11875991, DOI: 10.1109/tbme.2024.3486191.Peer-Reviewed Original ResearchCentral nervous systemReceptor occupancyLow-binding regionsPET scansSimulation resultsPreclinical in vivo experimentsDynamic PET scansPairs of baselineEstimation of receptor occupancyEstimation frameworkPET neuroimagingReconstruction frameworkModulating drugsTime activity curvesParametric reconstructionDevelopment of drugs[18F]MK-6240 Radioligand Delivery Indices as Surrogates of Cerebral Perfusion: Bias and Correlation Against [15O]Water
Fu J, Juttukonda M, Garimella A, Salvatore A, Lois C, Ranasinghe A, Efthimiou N, Sari H, Aye W, Guehl N, El Fakhri G, Johnson K, Dickerson B, Izquierdo-Garcia D, Catana C, Price J. [18F]MK-6240 Radioligand Delivery Indices as Surrogates of Cerebral Perfusion: Bias and Correlation Against [15O]Water. Journal Of Nuclear Medicine 2025, 66: 410-417. PMID: 39947916, PMCID: PMC11876731, DOI: 10.2967/jnumed.124.268701.Peer-Reviewed Original Research
2024
Diffusion-based Bayesian posterior distribution prediction of kinetic parameters in dynamic PET
Djebra Y, Liu X, Marin T, Tiss A, Dhaynaut M, Guehl N, Johnson K, Fakhri G, Ma C, Ouyang J. Diffusion-based Bayesian posterior distribution prediction of kinetic parameters in dynamic PET. 2024, 00: 1-1. DOI: 10.1109/nss/mic/rtsd57108.2024.10657955.Peer-Reviewed Original ResearchConditional variational autoencoderEfficient deep learning-based approachMarkov chain Monte CarloDenoising diffusion probabilistic modelDeep learning-based approachDiffusion probabilistic modelLearning-based approachApproximate posterior distributionPosterior distributionVariational autoencoderHeavy computationTau protein aggregationBayesian inferenceProbabilistic modelData-DrivenStudy molecular processesBayesian posterior distributionProtein aggregationMetropolis-Hastings Markov chain Monte CarloMolecular processesAlzheimer's diseaseNeurodegenerative diseasesKinetic parametersEstimate posterior distributionsAutoencoderEffects of List-Mode-Based Intraframe Motion Correction in Dynamic Brain PET Imaging
Tiss A, Chemli Y, Guehl N, Marin T, Johnson K, Fakhri G, Ouyang J. Effects of List-Mode-Based Intraframe Motion Correction in Dynamic Brain PET Imaging. IEEE Transactions On Radiation And Plasma Medical Sciences 2024, 8: 950-958. PMID: 39507127, PMCID: PMC11540417, DOI: 10.1109/trpms.2024.3432322.Peer-Reviewed Original ResearchDiffusion Model-Based Posterior Distribution Prediction for Kinetic Parameter Estimation in Dynamic PET
Djebra Y, Liu X, Marin T, Tiss A, Dhaynaut M, Guehl N, Johnson K, Fakhri G, Ma C, Ouyang J. Diffusion Model-Based Posterior Distribution Prediction for Kinetic Parameter Estimation in Dynamic PET. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2024, 00: 1-5. PMID: 39530051, PMCID: PMC11554386, DOI: 10.1109/isbi56570.2024.10635805.Peer-Reviewed Original ResearchPosterior distributions of kinetic parametersDenoising diffusion probabilistic modelHyperphosphorylated tauP-tauDiffusion probabilistic modelAlzheimer's diseaseNeurodegenerative diseasesKinetic parametersPosterior distributionInference efficiencyComputational needsEstimate kinetic parametersProbabilistic modelComputation timeRadiosynthesis automation, non-human primate biodistribution and dosimetry of K+ channel tracer [11C]3MeO4AP
Zhou Y, Wilks M, Dhaynaut M, Guehl N, Vesper D, Moon S, Rice P, El Fakhri G, Normandin M, Brugarolas P. Radiosynthesis automation, non-human primate biodistribution and dosimetry of K+ channel tracer [11C]3MeO4AP. EJNMMI Research 2024, 14: 43. PMID: 38683467, PMCID: PMC11058135, DOI: 10.1186/s13550-024-01092-8.Peer-Reviewed Original ResearchRadiation dosimetryAverage effective doseWhole-body biodistributionTotal scan timeNon-decayEffective doseNon-human primatesSymptomatic treatment of multiple sclerosisIn vivo binding affinityBed positionTreatment of multiple sclerosisHigh-resolution CTDynamic acquisition protocolDosimetryPET dataAdult rhesus macaquesScan timeImaging demyelinationOLINDA softwareRadiationAcquisition protocolsPreclinical studiesNo significant changesHigh dosesPET imaging