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 ResearchConceptsNeural 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
2021
Partial volume correction analysis for 11C-UCB-J PET studies of Alzheimer's disease
Lu Y, Toyonaga T, Naganawa M, Gallezot JD, Chen MK, Mecca AP, van Dyck CH, Carson RE. Partial volume correction analysis for 11C-UCB-J PET studies of Alzheimer's disease. NeuroImage 2021, 238: 118248. PMID: 34119639, PMCID: PMC8454285, DOI: 10.1016/j.neuroimage.2021.118248.Peer-Reviewed Original Research
2017
Players of ‘hypoxia orchestra’ – what is the role of FMISO?
Toyonaga T, Hirata K, Shiga T, Nagara T. Players of ‘hypoxia orchestra’ – what is the role of FMISO? European Journal Of Nuclear Medicine And Molecular Imaging 2017, 44: 1679-1681. PMID: 28634683, DOI: 10.1007/s00259-017-3754-9.Commentaries, Editorials and Letters
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 ResearchConceptsProgression-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