2019
Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features
Wang CJ, Hamm CA, Savic LJ, Ferrante M, Schobert I, Schlachter T, Lin M, Weinreb JC, Duncan JS, Chapiro J, Letzen B. Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features. European Radiology 2019, 29: 3348-3357. PMID: 31093705, PMCID: PMC7243989, DOI: 10.1007/s00330-019-06214-8.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAlgorithmsBile Duct NeoplasmsBile Ducts, IntrahepaticCarcinoma, HepatocellularCholangiocarcinomaDeep LearningFemaleHumansImage Interpretation, Computer-AssistedLiver NeoplasmsMachine LearningMagnetic Resonance ImagingMaleMiddle AgedNeural Networks, ComputerPredictive Value of TestsProof of Concept StudyRetrospective StudiesConceptsDeep learning systemConvolutional neural networkLearning systemRelevance scoresFeature mapsPre-trained CNN modelsFeature relevance scoresMulti-phasic MRINeural network interpretationEvidence-based decision supportDeep NeuralDeep learningCNN modelLesion classifierLearning prototypeNeural networkOriginal imageSystem prototypeDecision supportLesion classificationNetwork interpretationImage voxelsIncorrect featuresLesion classesTest setA 3D quantitative imaging biomarker in pre-treatment MRI predicts overall survival after stereotactic radiation therapy of patients with a singular brain metastasis
Della Seta M, Collettini F, Chapiro J, Angelidis A, Engeling F, Hamm B, Kaul D. A 3D quantitative imaging biomarker in pre-treatment MRI predicts overall survival after stereotactic radiation therapy of patients with a singular brain metastasis. Acta Radiologica 2019, 60: 1496-1503. PMID: 30841703, DOI: 10.1177/0284185119831692.Peer-Reviewed Original ResearchConceptsIntracranial progression-free survivalSingular brain metastasisStereotactic radiation therapyPre-treatment magnetic resonance imagingMagnetic resonance imagingBrain metastasesPrognostic factorsTumor volumeRadiation therapyCranial magnetic resonance imagingContrast-enhanced MRI scansMultivariable Cox regressionProgression-free survivalIntracranial malignant tumorPrediction of survivalOverall survivalMultivariable analysisPrognostic indexCox regressionRetrospective studyMalignant tumorsQuantitative imaging biomarkersMRI scansPatientsRadiomic biomarkers
2018
Predicting Treatment Response to Intra-arterial Therapies for Hepatocellular Carcinoma with the Use of Supervised Machine Learning—An Artificial Intelligence Concept
Abajian A, Murali N, Savic LJ, Laage-Gaupp FM, Nezami N, Duncan JS, Schlachter T, Lin M, Geschwind JF, Chapiro J. Predicting Treatment Response to Intra-arterial Therapies for Hepatocellular Carcinoma with the Use of Supervised Machine Learning—An Artificial Intelligence Concept. Journal Of Vascular And Interventional Radiology 2018, 29: 850-857.e1. PMID: 29548875, PMCID: PMC5970021, DOI: 10.1016/j.jvir.2018.01.769.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntineoplastic AgentsCarcinoma, HepatocellularChemoembolization, TherapeuticContrast MediaDoxorubicinEthiodized OilFemaleHumansLiver NeoplasmsMachine LearningMagnetic Resonance ImagingMaleMiddle AgedNeoplasm StagingPredictive Value of TestsRetrospective StudiesSensitivity and SpecificityTreatment OutcomeConceptsTransarterial chemoembolizationHepatocellular carcinomaTreatment responseLogistic regressionClinical patient dataPatient dataIntra-arterial therapyQuantitative European AssociationMagnetic resonance imagingLiver criteriaBaseline imagingClinical variablesTumor responseTherapeutic featuresTreatment respondersBaseline MRClinical informationImaging variablesChemoembolizationTherapeutic outcomesResonance imagingResponse criteriaEuropean AssociationPatientsMR imaging
2016
Imaging Biomarkers of Tumor Response in Neuroendocrine Liver Metastases Treated with Transarterial Chemoembolization: Can Enhancing Tumor Burden of the Whole Liver Help Predict Patient Survival?
Sahu S, Schernthaner R, Ardon R, Chapiro J, Zhao Y, Sohn JH, Fleckenstein F, Lin M, Geschwind JF, Duran R. Imaging Biomarkers of Tumor Response in Neuroendocrine Liver Metastases Treated with Transarterial Chemoembolization: Can Enhancing Tumor Burden of the Whole Liver Help Predict Patient Survival? Radiology 2016, 283: 160838. PMID: 27831830, PMCID: PMC5425309, DOI: 10.1148/radiol.2016160838.Peer-Reviewed Original ResearchConceptsNeuroendocrine liver metastasesWorld Health OrganizationContrast material-enhanced magnetic resonance (MR) imagesFirst TACE procedureResponse Evaluation CriteriaKaplan-Meier curvesTreatment response biomarkersTransarterial chemoembolization proceduresInstitutional review boardFirst TACELiver methodLiver metastasesIndependent predictorsTumor burdenRetrospective studyTACE proceduresCox regressionOnly biomarkerSurvival differencesChemoembolization proceduresTreatment responseResponse biomarkersPatientsSolid tumorsNormal liver