2025
Modeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model
Dong Y, Marin T, Zhuo Y, Najem E, Beddok A, Rozenblum L, Moteabbed M, Grogg K, Xing F, Woo J, Chen Y, Lim R, Liu X, Ma C, Fakhri G. Modeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model. Medical Physics 2025 PMID: 40317577, DOI: 10.1002/mp.17865.Peer-Reviewed Original ResearchClinical target volumeGross tumor volumeClinical target volume delineationSoft tissue sarcomasInter-reader variabilityTissue sarcomasClinical target volume contoursMagnetic resonance imagingCTV delineationTarget volume delineationComputed tomographyTreatment of soft tissue sarcomasFluorodeoxyglucose positron emission tomographyCTV contoursTarget volumeVolume delineationT1-weighted magnetic resonance imagingRadiotherapy treatmentEnergy distanceHigh Dice indexPositron emission tomographyTumor volumeMicroscopic spreadFDG-PETTreatment planningOptimizing imaging modalities for sarcoma subtypes in radiation therapy: State of the art
Beddok A, Kaur H, Khurana S, Dercle L, El Ayachi R, Jouglar E, Mammar H, Mahe M, Najem E, Rozenblum L, Thariat J, El Fakhri G, Helfre S. Optimizing imaging modalities for sarcoma subtypes in radiation therapy: State of the art. Critical Reviews In Oncology/Hematology 2025, 211: 104708. PMID: 40139581, DOI: 10.1016/j.critrevonc.2025.104708.Peer-Reviewed Original ResearchConceptsMagnetic resonance imagingRadiation therapyComputed tomographyRT planningImaging modalitiesSarcoma managementSarcoma subtypesAssessment of tumor extentIntegration of magnetic resonance imagingAlveolar soft part sarcomaSuperior soft tissue contrastSoft part sarcomaCombination of magnetic resonance imagingContext of radiation therapyIntegration of imaging modalitiesMetabolically active regionsActive regionPositron emission tomographyRT deliveryDose escalationSoft tissue contrastUterine sarcomaTumor extentTumor marginsOsseous involvementGross tumor volume confidence maps prediction for soft tissue sarcomas from multi-modality medical images using a diffusion model
Dong Y, Marin T, Zhuo Y, Najem E, Moteabbed M, Xing F, Beddok A, Lahoud R, Rozenblum L, Ding Z, Liu X, Grogg K, Woo J, Chen Y, Lim R, Ma C, Fakhri G. Gross tumor volume confidence maps prediction for soft tissue sarcomas from multi-modality medical images using a diffusion model. Physics And Imaging In Radiation Oncology 2025, 33: 100734. PMID: 40123775, PMCID: PMC11926426, DOI: 10.1016/j.phro.2025.100734.Peer-Reviewed Original ResearchGross tumor volumeSoft tissue sarcomasTissue sarcomasGross tumor volume delineationManual GTV delineationsMagnetic resonance imagingComputed tomographyFluorodeoxyglucose positron emission tomographyGTV delineationT1-weighted magnetic resonance imagingSingle-modePositron emission tomographyMulti-modal medical imagesTumor volumeIntra-reader variabilityFDG-PETTreatment planningSarcomaEmission tomographyImaging modalitiesResonance imagingDiffusion modelDice indexReader variabilityPatients
2023
Injectable ice slurry for reducing pericardial adipose tissue
Shuhaiber J, Tuchayi S, Bijari F, Guehl N, Wang Y, Farinelli W, Arkun K, Fakhri G, Anderson R, Garibyan L. Injectable ice slurry for reducing pericardial adipose tissue. Lasers In Surgery And Medicine 2023, 55: 674-679. PMID: 37464943, DOI: 10.1002/lsm.23709.Peer-Reviewed Original ResearchConceptsPericardial adipose tissuePericardial adipose tissue volumeChest computed tomographyPAT volumeBaseline chest computed tomographyAnimal modelsSubcutaneous adipose tissue volumesCardiovascular diseaseHigh risk of cardiovascular diseaseAdipose tissueLow patient complianceRisk of cardiovascular diseaseWeight lossPreclinical large animal modelAdipose tissue volumeLarge animal modelBariatric surgeryComputed tomographyPatient complianceHigh riskNovel treatmentTreated groupCT imagesTissue volumeCryolipolysisChapter 1 Computed tomography manifestations and prognosis of mild COVID-19 cases
Wang M, Fakhri G. Chapter 1 Computed tomography manifestations and prognosis of mild COVID-19 cases. 2023, 1-10. DOI: 10.1016/b978-0-443-18493-2.00001-2.Peer-Reviewed Original ResearchMild COVID-19 casesAsymptomatic patientsImaging findingsComputed tomographyAsymptomatic infectionNegative imaging findingsRespiratory tract specimensPositive nucleic acidCT manifestationsInfected casesComputed tomography manifestationsClinical symptomsMild casesAsymptomatic infected casesPatientsMild typeSARS-CoV-2InfectionSARS-CoV-2 virusClinical signsCommonest typeManifestationsCOVID-19 casesSymptomsPrognosisChapter 3 Computed tomography manifestations and prognosis of severe COVID-19 cases
Wang M, Fakhri G. Chapter 3 Computed tomography manifestations and prognosis of severe COVID-19 cases. 2023, 43-130. DOI: 10.1016/b978-0-443-18493-2.00003-6.Peer-Reviewed Original ResearchChapter 5 Multimodality medical imaging in the diagnosis and evaluation of COVID-19
Wang M, Fakhri G. Chapter 5 Multimodality medical imaging in the diagnosis and evaluation of COVID-19. 2023, 157-158. DOI: 10.1016/b978-0-443-18493-2.00005-x.Peer-Reviewed Original Research
2019
Attenuation correction using 3D deep convolutional neural network for brain 18F-FDG PET/MR: Comparison with Atlas, ZTE and CT based attenuation correction
Blanc-Durand P, Khalife M, Sgard B, Kaushik S, Soret M, Tiss A, Fakhri G, Habert M, Wiesinger F, Kas A. Attenuation correction using 3D deep convolutional neural network for brain 18F-FDG PET/MR: Comparison with Atlas, ZTE and CT based attenuation correction. PLOS ONE 2019, 14: e0223141. PMID: 31589623, PMCID: PMC6779234, DOI: 10.1371/journal.pone.0223141.Peer-Reviewed Original ResearchConceptsZero echo timeAC mapsAttenuation correctionPET attenuation correctionCT-based ACComputed tomographyAC methodPhoton attenuationZTE-ACInvestigation of suspected dementiaMR imagingBrain computed tomographyAtlas-ACBrain metabolismZTE-MRIConvolutional neural networkEcho timeHead atlasFDG-PET/MRPET imagingLow biasRegions-of-interestPatientsCorrectionNeural network
2017
Low‐dose CT reconstruction using spatially encoded nonlocal penalty
Kim K, Fakhri G, Li Q. Low‐dose CT reconstruction using spatially encoded nonlocal penalty. Medical Physics 2017, 44: e376-e390. PMID: 29027240, PMCID: PMC5927365, DOI: 10.1002/mp.12523.Peer-Reviewed Original ResearchConceptsLow Dose CT Grand ChallengeDose imagesDose dataFlying focal spotQuadratic surrogatesLow-dose CT reconstructionCT reconstruction methodImage qualityRadiation doseCT phantomFBP imagesRaw projectionsRebinning methodFocal spotLog-likelihoodReconstructed test imagesEfficient memory usageNesterov's momentum methodPoisson log-likelihoodGrand ChallengeComputed tomographyLow radiation doseCT reconstructionAccurate diagnostic featuresTest images
2016
Numerical observer for atherosclerotic plaque classification in spectral computed tomography
Lorsakul A, Fakhri G, Worstell W, Ouyang J, Rakvongthai Y, Laine A, Li Q. Numerical observer for atherosclerotic plaque classification in spectral computed tomography. Journal Of Medical Imaging 2016, 3: 035501-035501. PMID: 27429999, PMCID: PMC4940624, DOI: 10.1117/1.jmi.3.3.035501.Peer-Reviewed Original ResearchSignal-to-noise ratioChannelized Hotelling observerMatched filterSignal-to-noise ratio improvementDual-energy CTMultienergy CTSpectral computed tomographyBinary classification taskHotelling observerNumerical observationsArea under the receiver operating characteristic curveObjective image assessmentAcquisition methodImage atherosclerotic plaquesMaterial characterizationComputed tomographyClassification taskPerformance metricsAnthropomorphic digital phantomIdentification applicationsSpectral CT dataConventional CT systemsCalcified plaqueSignal variationsAnalytical computation
2013
Clinical Application of In-Room Positron Emission Tomography for In Vivo Treatment Monitoring in Proton Radiation Therapy
Min C, Zhu X, Winey B, Grogg K, Testa M, Fakhri G, Bortfeld T, Paganetti H, Shih H. Clinical Application of In-Room Positron Emission Tomography for In Vivo Treatment Monitoring in Proton Radiation Therapy. International Journal Of Radiation Oncology • Biology • Physics 2013, 86: 183-189. PMID: 23391817, PMCID: PMC3640852, DOI: 10.1016/j.ijrobp.2012.12.010.Peer-Reviewed Original ResearchConceptsIn-room positron emission tomographyProton therapyIn-roomPositron emission tomography scanIn-room PET scannerPassive scattering proton therapyShapes of target volumesPositron emission tomographyMC predictionBeam range uncertaintiesMeasured PET imagesMonte CarloProton radiation therapyLocal elemental compositionBiological washoutScan timeTreatment headTreatment verificationRange uncertaintiesTarget volumePET scan timePET scannerPET systemComputed tomographyMC results
2008
SU‐GG‐I‐74: New IAEA Document On Acceptance Testing, Quality Assurance and Quality Control for PET and PET/CT Systems
Fakhri G, Fulton R, Gray J, Marengo M, Zimmerman B, Dondi M, McLean I, Palm S. SU‐GG‐I‐74: New IAEA Document On Acceptance Testing, Quality Assurance and Quality Control for PET and PET/CT Systems. Medical Physics 2008, 35: 2659-2659. DOI: 10.1118/1.2961472.Peer-Reviewed Original ResearchPET/CT scannerTime-of-flight systemDetector materialPET/CTPET/CT unitComputed tomographyPET indicatorPET/CT systemCT componentPET technologyCT dataNatural radioactivityLesion detectionRadioactivity concentrationPETQuality assuranceDefinition of applicationsIAEAIAEA documentsGuidelinesAcceptance testsReference valuesScannerLesionsDetector
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