2022
Identifying the individual metabolic abnormities from a systemic perspective using whole-body PET imaging
Sun T, Wang Z, Wu Y, Gu F, Li X, Bai Y, Shen C, Hu Z, Liang D, Liu X, Zheng H, Yang Y, El Fakhri G, Zhou Y, Wang M. Identifying the individual metabolic abnormities from a systemic perspective using whole-body PET imaging. European Journal Of Nuclear Medicine And Molecular Imaging 2022, 49: 2994-3004. PMID: 35567627, PMCID: PMC9106794, DOI: 10.1007/s00259-022-05832-7.Peer-Reviewed Original ResearchConceptsPET imagingNormal control databaseTotal-body imagingWhole-body PET imagingNon-invasive modalitySUV measurementsGastrointestinal bleedingMetabolic abnormitiesSystem abnormalitiesTotal bodyLung cancerHealthy subjectsMetabolic dysfunctionFocal lesionsCOVID-19 diseaseGlucose metabolismControl databaseSUV imagesPatientsAbnormal networkBiological mechanismsDiseasePETMetabolic connectivity
2021
Detecting lumbar lesions in 99mTc‐MDP SPECT by deep learning: Comparison with physicians
Petibon Y, Fahey F, Cao X, Levin Z, Sexton‐Stallone B, Falone A, Zukotynski K, Kwatra N, Lim R, Bar‐Sever Z, Chemli Y, Treves S, Fakhri G, Ouyang J. Detecting lumbar lesions in 99mTc‐MDP SPECT by deep learning: Comparison with physicians. Medical Physics 2021, 48: 4249-4261. PMID: 34101855, DOI: 10.1002/mp.15033.Peer-Reviewed Original ResearchConceptsSingle-photon emission computed tomographyLow back painLumbar lesionsPediatric patientsTc-MDPEvaluate low back painCause of low back painTc-MDP scanLesion-presentEmission computed tomographyConvolutional neural networkClinical likelihoodBack painInterreader variabilityDeep convolutional neural networkLumbar locationLesionsStress lesionsFocal lesionsDeep learningPatientsLumbar stressPhysiciansDL systemsLROC studies