2023
Deep learning-based attenuation map generation with simultaneously reconstructed PET activity and attenuation and low-dose application
Shi L, Zhang J, Toyonaga T, Shao D, Onofrey J, Lu Y. Deep learning-based attenuation map generation with simultaneously reconstructed PET activity and attenuation and low-dose application. Physics In Medicine And Biology 2023, 68: 035014. PMID: 36584395, DOI: 10.1088/1361-6560/acaf49.Peer-Reviewed Original ResearchAlgorithmsDeep LearningFluorodeoxyglucose F18HumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMultimodal ImagingNeoplasmsPositron Emission Tomography Computed TomographyPositron-Emission Tomography
2022
Deep learning–based attenuation correction for whole-body PET — a multi-tracer study with 18F-FDG, 68 Ga-DOTATATE, and 18F-Fluciclovine
Toyonaga T, Shao D, Shi L, Zhang J, Revilla EM, Menard D, Ankrah J, Hirata K, Chen MK, Onofrey JA, Lu Y. Deep learning–based attenuation correction for whole-body PET — a multi-tracer study with 18F-FDG, 68 Ga-DOTATATE, and 18F-Fluciclovine. European Journal Of Nuclear Medicine And Molecular Imaging 2022, 49: 3086-3097. PMID: 35277742, PMCID: PMC10725742, DOI: 10.1007/s00259-022-05748-2.Peer-Reviewed Original ResearchMeSH KeywordsDeep LearningFluorodeoxyglucose F18HumansImage Processing, Computer-AssistedNeoplasmsPositron Emission Tomography Computed TomographyPositron-Emission TomographyRadionuclide ImagingRadiopharmaceuticalsConceptsNeural networkNovel deep learningNet neural networkPET/CT datasetsImage analysis metricsPhysics-based loss functionDeep learningCT-derived attenuation mapAttenuation mapLoss functionAnalysis metricsDetail recoveryTumor volume estimationMLAACT datasetsOSEM algorithmNetworkAlgorithmAttenuation correctionCorrection framework
2016
Hypoxic glucose metabolism in glioblastoma as a potential prognostic factor
Toyonaga T, Yamaguchi S, Hirata K, Kobayashi K, Manabe O, Watanabe S, Terasaka S, Kobayashi H, Hattori N, Shiga T, Kuge Y, Tanaka S, Ito YM, Tamaki N. Hypoxic glucose metabolism in glioblastoma as a potential prognostic factor. European Journal Of Nuclear Medicine And Molecular Imaging 2016, 44: 611-619. PMID: 27752745, DOI: 10.1007/s00259-016-3541-z.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedBlood GlucoseBrain NeoplasmsCell HypoxiaFemaleFluorodeoxyglucose F18GlioblastomaGlycolysisHumansMagnetic Resonance ImagingMaleMiddle AgedMisonidazoleOxygenPositron Emission Tomography Computed TomographyRadiopharmaceuticalsConceptsProgression-free survivalExtent of resectionStandardized uptake valuePositron emission tomographyGross tumor volumeFMISO positron emission tomographyMagnetic resonance imagingKarnofsky Performance ScaleOverall survivalTumor volumeGlioblastoma patientsHypoxia volumeFDG positron emission tomographyFluorodeoxyglucose positron emission tomographyPotential prognostic factorsTotal lesion glycolysisMetabolic tumor volumeHypoxic volumeVolume of interestGadolinium-enhanced T1-weighted MR imagesReference regionT1-weighted MR imagesCytoreduction surgeryFree survivalPrognostic factors