2024
Comparative study of functional and structural muscle changes in peripheral artery disease: rubidium-82 positron emission tomography and histological correlation
Alashi A, Vermillion B, Callegari S, Burns R, Guo L, Moulton E, Guerrera N, Depino A, Papademetris X, Zeiss C, Thorn S, Liu C, Sinusas A. Comparative study of functional and structural muscle changes in peripheral artery disease: rubidium-82 positron emission tomography and histological correlation. European Heart Journal - Cardiovascular Imaging 2024, 25: jeae142.087. DOI: 10.1093/ehjci/jeae142.087.Peer-Reviewed Original ResearchPeripheral arterial diseaseStandardized uptake valueHindlimb ischemia modelReactive hyperemiaSkeletal muscle perfusionPerfusion reserveCapillary densityPET imagingArtery diseaseNon-ischemicRubidium-82 positron emission tomographyType 2 muscle fibersRelevant pre-clinical modelIndicative of fibrosisManagement of peripheral arterial diseaseCapillary to muscle fiber ratioClinically relevant pre-clinical modelPre-clinical modelsMuscle perfusionFast myosinWeeks post-ligationRb-82 uptakeEvaluate treatment strategiesRabbit hindlimb ischemia modelPositron emission tomographyDesign and development of the DE-SPECT system: a clinical SPECT system for broadband multi-isotope imaging of peripheral vascular disease
Zannoni E, Sankar P, Jin Y, Liu C, Sinusas A, Metzler S, Meng L. Design and development of the DE-SPECT system: a clinical SPECT system for broadband multi-isotope imaging of peripheral vascular disease. Physics In Medicine And Biology 2024, 69: 125016. PMID: 38815617, PMCID: PMC11167601, DOI: 10.1088/1361-6560/ad5266.Peer-Reviewed Original ResearchConceptsCadmium zinc tellurideSPECT systemField of viewExcellent spectroscopic performanceExcellent energy resolutionBroad energy rangeIntrinsic spatial resolutionSpatial resolutionClinical SPECT systemEnergy resolutionPeripheral vascular diseaseEnergy rangeMm FWHMSpectroscopic performanceZinc tellurideWide-FOVCollimatorPreliminary experimental dataPartial ringDetection systemImaging capabilitiesImaging performanceExtremity imagingVascular diseaseScout imagesTAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction
Guo X, Shi L, Chen X, Liu Q, Zhou B, Xie H, Liu Y, Palyo R, Miller E, Sinusas A, Staib L, Spottiswoode B, Liu C, Dvornek N. TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction. Medical Image Analysis 2024, 96: 103190. PMID: 38820677, PMCID: PMC11180595, DOI: 10.1016/j.media.2024.103190.Peer-Reviewed Original ResearchGenerative adversarial networkAdversarial networkMotion estimation accuracyInter-frame motionIntensity-based image registration techniqueAll-to-oneSegmentation masksImage registration techniquesOriginal frameTemporal informationDiagnosis accuracyMyocardial blood flowEstimation accuracyFrame conversionPositron emission tomographyNovel methodImage qualityPET datasetsRegistration techniqueNetworkCardiac positron emission tomographyBlood flowDynamic cardiac positron emission tomographyMotion correctionCoronary artery diseasePopulation-based deep image prior for dynamic PET denoising: A data-driven approach to improve parametric quantification
Liu Q, Tsai Y, Gallezot J, Guo X, Chen M, Pucar D, Young C, Panin V, Casey M, Miao T, Xie H, Chen X, Zhou B, Carson R, Liu C. Population-based deep image prior for dynamic PET denoising: A data-driven approach to improve parametric quantification. Medical Image Analysis 2024, 95: 103180. PMID: 38657423, DOI: 10.1016/j.media.2024.103180.Peer-Reviewed Original ResearchDeep Image PriorImage priorsSupervised modelsNoise reductionIntrinsic image featuresDeep learning techniquesU-Net architectureNovel denoising techniqueQuality of parametric imagesDenoising modelDenoising techniquesStatic datasetsBaseline techniquesEffective noise reductionData-driven approachLearning techniquesDynamic datasetsOptimization processPrior informationStatic imagesHigh noise levelsImage featuresDatasetPrior imagePET datasetsDuDoCFNet: Dual-Domain Coarse-to-Fine Progressive Network for Simultaneous Denoising, Limited-View Reconstruction, and Attenuation Correction of Cardiac SPECT
Chen X, Zhou B, Guo X, Xie H, Liu Q, Duncan J, Sinusas A, Liu C. DuDoCFNet: Dual-Domain Coarse-to-Fine Progressive Network for Simultaneous Denoising, Limited-View Reconstruction, and Attenuation Correction of Cardiac SPECT. IEEE Transactions On Medical Imaging 2024, PP: 1-1. PMID: 38578853, DOI: 10.1109/tmi.2024.3385650.Peer-Reviewed Original ResearchMulti-task learning methodCross-domainLimited-viewLearning methodsCoarse-to-fine estimationProgressive networkDual domainCross-modal feature fusionDual-domain networkProgressive learning strategyCross-modal informationSimultaneous denoisingFeature fusionSingle-photon emission computed tomographyImage domainCardiac single-photon emission computed tomographyReconstruction accuracyDenoisingHardware expenseFusion mechanismAccelerated scansImage noiseM-mapSuperior accuracyNetworkASSESSING VASCULAR FLOW IN ACUTE AND CHRONIC RABBIT MODELS OF HINDLIMB ISCHEMIA USING HIGH-RESOLUTION 2D ANGIOGRAPHY: IMPLICATIONS FOR PET FLOW QUANTIFICATION
Callegari S, Vermillion B, Alashi A, Burns R, Jang S, Guerrera N, Guo L, Depino A, Zohora F, Smolderen K, Hurtado C, Liu C, Thorn S, Sinusas A. ASSESSING VASCULAR FLOW IN ACUTE AND CHRONIC RABBIT MODELS OF HINDLIMB ISCHEMIA USING HIGH-RESOLUTION 2D ANGIOGRAPHY: IMPLICATIONS FOR PET FLOW QUANTIFICATION. Journal Of The American College Of Cardiology 2024, 83: 2251. DOI: 10.1016/s0735-1097(24)04241-4.Peer-Reviewed Original ResearchA Review on Low-Dose Emission Tomography Post-Reconstruction Denoising With Neural Network Approaches
Bousse A, Kandarpa V, Shi K, Gong K, Lee J, Liu C, Visvikis D. A Review on Low-Dose Emission Tomography Post-Reconstruction Denoising With Neural Network Approaches. IEEE Transactions On Radiation And Plasma Medical Sciences 2024, 8: 333-347. PMID: 38313194, PMCID: PMC10836084, DOI: 10.1109/trpms.2023.3349194.Peer-Reviewed Original Research
2023
Unified Noise-Aware Network for Low-Count PET Denoising With Varying Count Levels
Xie H, Liu Q, Zhou B, Chen X, Guo X, Wang H, Li B, Rominger A, Shi K, Liu C. Unified Noise-Aware Network for Low-Count PET Denoising With Varying Count Levels. IEEE Transactions On Radiation And Plasma Medical Sciences 2023, 8: 366-378. DOI: 10.1109/trpms.2023.3334105.Peer-Reviewed Original ResearchLarge-scale dataDeep learningDynamic PET imagesLow-count dataNeural networkMultiple networksSpecific noise levelDifferent vendorsDifferent noise levelsDenoised resultsNoisy counterpartDynamic frameInput noise levelNetworkData availabilityHigher image noiseImage qualityImage noiseSuperior performanceImportant topicAdditional challengesNoise levelPET imagesLimited data availabilityVendorsSelf-supervised Noise-aware Network for Dynamic Rubidium-82 Cardiac PET Image Denoising
Xie H, Guo L, Guo X, Liu Q, Zhou B, Chen X, Wang G, Sinusas A, Liu C. Self-supervised Noise-aware Network for Dynamic Rubidium-82 Cardiac PET Image Denoising. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10338703.Peer-Reviewed Original ResearchThe DE-SPECT System: A Hyperspectral SPECT System for in Vivo 3-D Gamma-Ray Spectrometry of Molecular Theranostics
Zannoni E, Jin Y, Sankar P, Gura D, Wu R, Zhang F, Streicher M, Yang H, He Z, Metzler S, Liu C, Sinusas A, Meng L. The DE-SPECT System: A Hyperspectral SPECT System for in Vivo 3-D Gamma-Ray Spectrometry of Molecular Theranostics. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10337964.Peer-Reviewed Original ResearchFedFTN: Personalized Federated Learning with Deep Feature Transformation Network for Multi-institutional Low-count PET Denoising
Zhou B, Zhou B, Xie H, Liu Q, Chen X, Guo X, Zhou K, Li B, Rominger A, Shi K, Duncan J, Liu C. FedFTN: Personalized Federated Learning with Deep Feature Transformation Network for Multi-institutional Low-count PET Denoising. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10338446.Peer-Reviewed Original ResearchPopulation-based Deep Image Prior for Dynamic PET Denoising
Liu Q, Tsai Y, Gallezot J, Guo X, Chen M, Pucar D, Young C, Panin V, Miao T, Xie H, Chen X, Zhou B, Carson R, Liu C. Population-based Deep Image Prior for Dynamic PET Denoising. 2023, 00: 1-2. DOI: 10.1109/nssmicrtsd49126.2023.10338619.Peer-Reviewed Original ResearchCross-Domain Iterative Network for Simultaneous Denoising, Limited-Angle Reconstruction, and Attenuation Correction of Cardiac SPECT
Chen X, Zhou B, Xie H, Guo X, Liu Q, Sinusas A, Liu C. Cross-Domain Iterative Network for Simultaneous Denoising, Limited-Angle Reconstruction, and Attenuation Correction of Cardiac SPECT. Lecture Notes In Computer Science 2023, 14348: 12-22. DOI: 10.1007/978-3-031-45673-2_2.Peer-Reviewed Original ResearchSimultaneous denoisingAttenuation correctionCardiac single-photon emission computed tomographySingle-photon emission computed tomographyLimited-angleCross-domainIterative networkLow reconstruction accuracyDeep learning methodsEnd-to-endReduce hardware costIncreased image noiseAblation studiesReconstruction performanceInput featuresSingle-photonHardware costLearning methodsAttenuation mapLow-doseReconstruction accuracyLimited-angle reconstructionRadiation exposureExtra radiation exposureMultiple iterationsDual-Domain Iterative Network with Adaptive Data Consistency for Joint Denoising and Few-Angle Reconstruction of Low-Dose Cardiac SPECT
Chen X, Zhou B, Xie H, Guo X, Liu Q, Sinusas A, Liu C. Dual-Domain Iterative Network with Adaptive Data Consistency for Joint Denoising and Few-Angle Reconstruction of Low-Dose Cardiac SPECT. Lecture Notes In Computer Science 2023, 14307: 49-59. DOI: 10.1007/978-3-031-44917-8_5.Peer-Reviewed Original ResearchIterative networkAuxiliary modulesJoint denoisingLow reconstruction accuracySource codeData consistencyNetwork performanceAblation studiesReconstruction accuracyCardiac SPECTConsistency moduleHardware expensePrediction accuracyAngle reconstructionNetworkDenoisingImage noiseAngle projectionsModuleADC moduleAccuracyReconstructionImagesMPI dataCodeTAI-GAN: Temporally and Anatomically Informed GAN for Early-to-Late Frame Conversion in Dynamic Cardiac PET Motion Correction
Guo X, Shi L, Chen X, Zhou B, Liu Q, Xie H, Liu Y, Palyo R, Miller E, Sinusas A, Spottiswoode B, Liu C, Dvornek N. TAI-GAN: Temporally and Anatomically Informed GAN for Early-to-Late Frame Conversion in Dynamic Cardiac PET Motion Correction. Lecture Notes In Computer Science 2023, 14288: 64-74. PMID: 38464964, PMCID: PMC10923183, DOI: 10.1007/978-3-031-44689-4_7.Peer-Reviewed Original ResearchFedFTN: Personalized federated learning with deep feature transformation network for multi-institutional low-count PET denoising
Zhou B, Xie H, Liu Q, Chen X, Guo X, Feng Z, Hou J, Zhou S, Li B, Rominger A, Shi K, Duncan J, Liu C. FedFTN: Personalized federated learning with deep feature transformation network for multi-institutional low-count PET denoising. Medical Image Analysis 2023, 90: 102993. PMID: 37827110, PMCID: PMC10611438, DOI: 10.1016/j.media.2023.102993.Peer-Reviewed Original ResearchConceptsFederated learning processFederated learning algorithmFederated learning strategyLarge domain shiftDifferent data distributionsTransformation networkLarge-scale datasetsDeep learningDomain shiftLearning algorithmDownstream tasksNetwork weightsFeature outputFeature transformationSecurity concernsData distributionCollaborative trainingPersonalized modelPET image qualityReconstructed imagesReconstruction methodImage qualityNetworkEfficient wayLocal dataTransformer-Based Dual-Domain Network for Few-View Dedicated Cardiac SPECT Image Reconstructions
Xie H, Zhou B, Chen X, Guo X, Thorn S, Liu Y, Wang G, Sinusas A, Liu C. Transformer-Based Dual-Domain Network for Few-View Dedicated Cardiac SPECT Image Reconstructions. Lecture Notes In Computer Science 2023, 14229: 163-172. DOI: 10.1007/978-3-031-43999-5_16.Peer-Reviewed Original ResearchDual-domain networkSPECT image reconstructionImage reconstructionDeep learning methodsPrevious baseline methodsCardiac SPECT imagesHigh-quality imagesReconstruction networkIterative reconstruction processView reconstructionBaseline methodsReconstruction outputLearning methodsClinical softwareReconstruction processImaging problemsProjection dataImage qualityNetworkImagesStationary dataSPECT scannerDiagnosis of CVDLimited amountSoftware99mTc/123I Dual-Radionuclide Correction for Self-Scatter, Down-Scatter, and Tailing Effect for a CZT SPECT With Varying Tracer Distributions
Velo A, Fan P, Xie H, Chen X, Boutagy N, Feher A, Sinusas A, Ljungberg M, Liu C. 99mTc/123I Dual-Radionuclide Correction for Self-Scatter, Down-Scatter, and Tailing Effect for a CZT SPECT With Varying Tracer Distributions. IEEE Transactions On Radiation And Plasma Medical Sciences 2023, 7: 839-850. PMID: 38745858, PMCID: PMC11090119, DOI: 10.1109/trpms.2023.3297443.Peer-Reviewed Original ResearchMCP-Net: Introducing Patlak Loss Optimization to Whole-Body Dynamic PET Inter-Frame Motion Correction
Guo X, Zhou B, Chen X, Chen M, Liu C, Dvornek N. MCP-Net: Introducing Patlak Loss Optimization to Whole-Body Dynamic PET Inter-Frame Motion Correction. IEEE Transactions On Medical Imaging 2023, 42: 3512-3523. PMID: 37368811, PMCID: PMC10751388, DOI: 10.1109/tmi.2023.3290003.Peer-Reviewed Original ResearchMotion estimation blockDeep learning benchmarksGood generalization capabilityMotion correctionMotion correction frameworkMotion prediction errorGeneralization capabilityNetwork performanceNeural networkMotion correction techniqueLearning benchmarksRegistration problemLoss functionEstimation blockLoss optimizationPenalty componentDynamic frameFitting errorSpatial alignmentParametric imagesSpatial misalignmentDynamic positron emission tomographySubject motionPrediction errorCorrection frameworkMultimodality Imaging of Aortic Valve Calcification and Function in a Murine Model of Calcific Aortic Valve Disease and Bicuspid Aortic Valve
Ahmad A, Ghim M, Toczek J, Neishabouri A, Ojha D, Zhang Z, Gona K, Raza M, Jung J, Kukreja G, Zhang J, Guerrera N, Liu C, Sadeghi M. Multimodality Imaging of Aortic Valve Calcification and Function in a Murine Model of Calcific Aortic Valve Disease and Bicuspid Aortic Valve. Journal Of Nuclear Medicine 2023, 64: 1487-1494. PMID: 37321825, PMCID: PMC10478817, DOI: 10.2967/jnumed.123.265516.Peer-Reviewed Original ResearchConceptsF-NaF PET/CTCalcific aortic valve diseaseBicuspid aortic valvePET/CTAortic valve calcificationAortic valve diseaseAortic valveAortic stenosisValve calcificationValvular calcificationValve diseaseF-NaFSubset of miceTricuspid aortic valveDevelopment of calcificationSignificant correlationUnderwent echocardiographyMedical therapyHigh prevalencePreclinical modelsMurine modelTherapeutic interventionsAge groupsAutoradiography dataMultimodality imaging