Maeva Dhaynaut
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Maeva Dhaynaut is a translational neuroimaging scientist and faculty member at Yale University. She specializes in PET imaging and multimodal approaches to study brain disorders such as Alzheimer’s disease. Her work focuses on developing imaging biomarkers to better understand disease mechanisms and improve diagnosis and treatment.
Last Updated on April 15, 2026.
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Radiology & Biomedical Imaging
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Public Health Interests
Mental Health; Women's Health; Biomarkers; Aging
ORCID
0000-0002-8529-5746
Research at a Glance
Yale Co-Authors
Frequent collaborators of Maeva Dhaynaut's published research.
Publications Timeline
A big-picture view of Maeva Dhaynaut's research output by year.
Georges El Fakhri, PhD, DABR
Marc David Normandin, PhD
Nicolas Guehl
Yanis Chemli, PhD
Chao Ma, PhD
Jinsong Ouyang, PhD
30Publications
544Citations
Publications
2025
O119 / #388 EVALUATION OF CARDIO-RESPIRATORY-GATING FOR PROTON CARDIAC ABLATION: A LARGE-ANIMAL STUDY.
Depauw N, Bijari F, Garonna A, Kang J, Chemli Y, Deng H, Dhaynaut M, Kim H, Macdonald-Soccorso M, Moon S, Normandin M, Woodcock R, Yaghoubian M, Fakhri G, Levine R, Lehmann H, Chen Y, Jee K. O119 / #388 EVALUATION OF CARDIO-RESPIRATORY-GATING FOR PROTON CARDIAC ABLATION: A LARGE-ANIMAL STUDY. International Journal Of Particle Therapy 2025, 17: 100875. DOI: 10.1016/j.ijpt.2025.100875.Peer-Reviewed Original ResearchYRT-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, PP: 1-1. PMID: 41424471, PMCID: PMC12714321, DOI: 10.1109/trpms.2025.3619872.Peer-Reviewed Original ResearchConceptsOpen-sourceImage reconstructionPositron emission tomography image reconstructionReconstruction algorithmAdvanced image reconstruction algorithmsOpen-source toolkitDevelopment of advanced algorithmsTime-of-flightScanner geometryNovel reconstruction algorithmImage reconstruction algorithmMotion correctionReusable codeGPU accelerationTime-of-flight informationPython bindingsPlugin systemSoftware toolkitMeaningful imagesData formatsFast implementationRigid motion correctionAdvanced algorithmsPoint spread function modelProprietary softwareBayesian 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 ResearchAltmetricConceptsPosterior 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 ResearchCitationsAltmetric3748 A large-animal pilot study of cardio-respiratory-gated radiation ablation for ventricular tachycardia targets using proton therapy
Jee K, Bijari F, Chemli Y, Chen Y, Deng H, Depauw N, Dhaynaut M, Garonna A, Kang J, Kim H, Macdonald-Soccorso M, Moon S, Normandin M, Woodcock R, Yaghoubian K, Levine R, Lehmann H, Fakhri G. 3748 A large-animal pilot study of cardio-respiratory-gated radiation ablation for ventricular tachycardia targets using proton therapy. Radiotherapy And Oncology 2025, 206: s3543-s3544. DOI: 10.1016/s0167-8140(25)01927-9.Peer-Reviewed Original ResearchPO-04-096 NEW CARDIO-RESPIRATORY-GATED (5D) DELIVERY OF PROTON BEAMS FOR ABLATION OF VENTRICULAR ARRHYTHMIAS IN A PORCINE MODEL: LESION OUTCOMES AND COMPARISON TO RESPIRATORY GATED DELIVERY
Kang J, Bijari F, Jee K, Chemli Y, Chen Y, Deng H, Depauw N, Dhaynaut M, Garonna A, Kim H, Macdonald-Soccorso M, Moon S, Normandin M, Woodcock R, Yaghoubian K, Fakhri G, Levine R, Lehmann H. PO-04-096 NEW CARDIO-RESPIRATORY-GATED (5D) DELIVERY OF PROTON BEAMS FOR ABLATION OF VENTRICULAR ARRHYTHMIAS IN A PORCINE MODEL: LESION OUTCOMES AND COMPARISON TO RESPIRATORY GATED DELIVERY. Heart Rhythm 2025, 22: s484. DOI: 10.1016/j.hrthm.2025.03.1230.Peer-Reviewed Original ResearchSelective Mu-Opioid Receptor Imaging Using 18F‑Labeled Carfentanils
Lee S, Pearson T, Dhaynaut M, MacDonagh A, Wey H, Wilks M, Roth B, Hooker J, Normandin M. Selective Mu-Opioid Receptor Imaging Using 18F‑Labeled Carfentanils. Journal Of Medicinal Chemistry 2025, 68: 1632-1644. PMID: 39772615, DOI: 10.1021/acs.jmedchem.4c02287.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsMu-opioid receptorsPositron emission tomographyIn vivo PET scansCarbon-11Neurobiological studiesCopper-mediated radiofluorinationMu-opioidReceptor imagingPET scansBrain uptakeFavorable pharmacokineticsImaging evaluationHigh molar activityMass doseEmission tomographyHalf-life of fluorine-18Synthetic opioidsFluorine-18Half-lifeIn vitro binding assaysBinding assaysClinical research useMolar activityCarfentanilResearch use
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 ResearchConceptsConditional 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 distributionsAutoencoderNovel multi-modal methodology to investigate placebo response in major depressive disorder
Cusin C, Dillon D, Belleau E, Normandin M, Petibon Y, El-Fakri G, Dhaynaut M, Hooker J, Kaptchuk T, McKee M, Hayden E, Meyer A, Jahan A, Origlio J, Ang Y, Brunner D, Kang M, Long Y, Fava M, Pizzagalli D. Novel multi-modal methodology to investigate placebo response in major depressive disorder. Journal Of Affective Disorders 2024, 368: 1-7. PMID: 39233242, PMCID: PMC12933866, DOI: 10.1016/j.jad.2024.08.226.Peer-Reviewed Original ResearchAltmetricConceptsPlacebo responseDepressive disorderRates of placebo responseMesocorticolimbic dopaminergic pathwayExpectation of rewardAntidepressant responseMesolimbic systemReward circuitryNeurobiological underpinningsNeurobiological mechanismsDopaminergic activityDopaminergic systemPlacebo respondersSymptom reductionDopaminergic pathwaysMulti-modal methodologyPlacebo phenomenonPsychological constructsTreatment developmentMDDPlacebo-ControlledClinical trialsDouble-blindRewardDesigning Clinical TrialsDiffusion 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 ResearchCitationsConceptsPosterior distributions of kinetic parametersDenoising diffusion probabilistic modelHyperphosphorylated tauP-tauDiffusion probabilistic modelAlzheimer's diseaseNeurodegenerative diseasesKinetic parametersPosterior distributionInference efficiencyComputational needsEstimate kinetic parametersProbabilistic modelComputation time
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- October 29, 2025
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