2021
Thermal ablation alone vs thermal ablation combined with transarterial chemoembolization for patients with small (<3 cm) hepatocellular carcinoma
Chai NX, Chapiro J, Petukhova A, Gross M, Kucukkaya A, Raju R, Zeevi T, Elbanan M, Lin M, Perez-Lozada JC, Schlachter T, Strazzabosco M, Pollak JS, Madoff DC. Thermal ablation alone vs thermal ablation combined with transarterial chemoembolization for patients with small (<3 cm) hepatocellular carcinoma. Clinical Imaging 2021, 76: 123-129. PMID: 33592550, PMCID: PMC8217099, DOI: 10.1016/j.clinimag.2021.01.043.Peer-Reviewed Original ResearchConceptsOverall survivalTransarterial chemoembolizationHepatocellular carcinomaThermal ablationTA groupEarly-stage hepatocellular carcinomaMedian overall survivalTherapy-naïve patientsKaplan-Meier analysisMaximum tumor diameterStage hepatocellular carcinomaLog-rank testDrug-eluting beadsSmall hepatocellular carcinomaTerms of TTPHIPAA-compliant IRBSignificant differencesLipiodol-TACELocoregional therapyBCLC stageComplication rateTreatment cohortsTumor diameterAFP levelsPatient group
2020
Automated feature quantification of Lipiodol as imaging biomarker to predict therapeutic efficacy of conventional transarterial chemoembolization of liver cancer
Stark S, Wang C, Savic LJ, Letzen B, Schobert I, Miszczuk M, Murali N, Oestmann P, Gebauer B, Lin M, Duncan J, Schlachter T, Chapiro J. Automated feature quantification of Lipiodol as imaging biomarker to predict therapeutic efficacy of conventional transarterial chemoembolization of liver cancer. Scientific Reports 2020, 10: 18026. PMID: 33093524, PMCID: PMC7582153, DOI: 10.1038/s41598-020-75120-7.Peer-Reviewed Original ResearchConceptsConventional transarterial chemoembolizationLipiodol depositionTransarterial chemoembolizationLiver cancerPeripheral depositionLipiodol depositsTherapeutic efficacyNecrotic tumor areasBaseline MRITherapy optionsTumor responseTreatment responseTumor volumeLiver lesionsLipiodolH postTumor areaH-CTHounsfield unitsBiomarkersChemoembolizationHigh rateTumorsCancerImproved responseIdarubicin-Loaded ONCOZENE Drug-Eluting Bead Chemoembolization in a Rabbit Liver Tumor Model: Investigating Safety, Therapeutic Efficacy, and Effects on Tumor Microenvironment
Borde T, Gaupp F, Geschwind JF, Savic LJ, Miszczuk M, Rexha I, Adam L, Walsh JJ, Huber S, Duncan JS, Peters DC, Sinusas A, Schlachter T, Gebauer B, Hyder F, Coman D, van Breugel JMM, Chapiro J. Idarubicin-Loaded ONCOZENE Drug-Eluting Bead Chemoembolization in a Rabbit Liver Tumor Model: Investigating Safety, Therapeutic Efficacy, and Effects on Tumor Microenvironment. Journal Of Vascular And Interventional Radiology 2020, 31: 1706-1716.e1. PMID: 32684417, PMCID: PMC7541537, DOI: 10.1016/j.jvir.2020.04.010.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAntibiotics, AntineoplasticBiosensing TechniquesCell Line, TumorCell ProliferationChemoembolization, TherapeuticDiffusion Magnetic Resonance ImagingHydrogen-Ion ConcentrationIdarubicinLiver Neoplasms, ExperimentalMaleMicrospheresMultidetector Computed TomographyParticle SizeRabbitsTumor MicroenvironmentConceptsMultiparametric magnetic resonanceRabbit liver tumor modelDiffusion-weighted imagingLiver tumor modelDEE chemoembolizationDrug-eluting embolic transarterial chemoembolizationTumor microenvironmentTumor modelMale New Zealand white rabbitsTumor acidosisNew Zealand white rabbitsVX2 liver tumorsZealand white rabbitsLaboratory parametersTransarterial chemoembolizationBead chemoembolizationMultiparametric MRDCE MR imagingLiver enzymesPostprocedural increaseIntratumoral hypoxiaLiver tumorsEntire lesionTherapeutic mechanismChemoembolizationNeutrophil-to-lymphocyte and platelet-to-lymphocyte ratios as predictors of tumor response in hepatocellular carcinoma after DEB-TACE
Schobert IT, Savic LJ, Chapiro J, Bousabarah K, Chen E, Laage-Gaupp F, Tefera J, Nezami N, Lin M, Pollak J, Schlachter T. Neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios as predictors of tumor response in hepatocellular carcinoma after DEB-TACE. European Radiology 2020, 30: 5663-5673. PMID: 32424595, PMCID: PMC7483919, DOI: 10.1007/s00330-020-06931-5.Peer-Reviewed Original ResearchMeSH KeywordsAgedBlood PlateletsCarcinoma, HepatocellularChemoembolization, TherapeuticFemaleHumansInflammationKaplan-Meier EstimateLiver NeoplasmsLymphocytesMagnetic Resonance ImagingMaleMiddle AgedMultivariate AnalysisNeutrophilsPrognosisProgression-Free SurvivalProportional Hazards ModelsRetrospective StudiesTreatment OutcomeConceptsProgression-free survivalTreatment-naïve hepatocellular carcinomaShorter progression-free survivalPoor tumor responseDEB-TACELymphocyte ratioTumor responseHepatocellular carcinomaMagnetic resonance imagingTumor growthInflammatory biomarkersDrug-eluting bead transarterial chemoembolizationContrast-enhanced magnetic resonance imagingHigher baseline NLRHigher baseline plateletsRadiomic featuresVolumetric tumor responseLoco-regional therapyAlpha-fetoprotein levelsBead transarterial chemoembolizationKaplan-Meier analysisMethodsThis retrospective studyDifferential blood countQuantitative European AssociationNodular tumor growthMolecular Imaging of Extracellular Tumor pH to Reveal Effects of Locoregional Therapy on Liver Cancer Microenvironment
Savic LJ, Schobert I, Peters D, Walsh JJ, Laage-Gaupp F, Hamm CA, Tritz N, Doemel LA, Lin M, Sinusas A, Schlachter T, Duncan JS, Hyder F, Coman D, Chapiro J. Molecular Imaging of Extracellular Tumor pH to Reveal Effects of Locoregional Therapy on Liver Cancer Microenvironment. Clinical Cancer Research 2020, 26: 428-438. PMID: 31582517, PMCID: PMC7244230, DOI: 10.1158/1078-0432.ccr-19-1702.Peer-Reviewed Original ResearchConceptsMR spectroscopic imagingLocoregional therapyLiver cancer microenvironmentConventional transarterial chemoembolizationNew Zealand white rabbitsTumor pHMost liver tumorsZealand white rabbitsMolecular imaging paradigmsPositive therapeutic outcomesTumor residualsTransarterial chemoembolizationTumor devascularizationHistopathologic markersViable tumorSurrogate biomarkerLiver tumorsLiver cancerTumor enhancementLiver parenchymaMetabolic markersMultiparametric MRITherapeutic outcomesHIF-1αVX2 tumors
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 setDeep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI
Hamm CA, Wang CJ, Savic LJ, Ferrante M, Schobert I, Schlachter T, Lin M, Duncan JS, Weinreb JC, Chapiro J, Letzen B. Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI. European Radiology 2019, 29: 3338-3347. PMID: 31016442, PMCID: PMC7251621, DOI: 10.1007/s00330-019-06205-9.Peer-Reviewed Original ResearchAdultAgedBile Duct NeoplasmsBile Ducts, IntrahepaticCarcinoma, HepatocellularCholangiocarcinomaDeep LearningFemaleHumansImage Interpretation, Computer-AssistedLiver NeoplasmsMagnetic Resonance ImagingMaleMiddle AgedNeural Networks, ComputerReproducibility of ResultsROC CurveSensitivity and SpecificityUnited StatesQuantitative Imaging Biomarkers for 90Y Distribution on Bremsstrahlung SPECT After Resin-Based Radioembolization
Schobert I, Chapiro J, Nezami N, Hamm CA, Gebauer B, Lin M, Pollak J, Saperstein L, Schlachter T, Savic LJ. Quantitative Imaging Biomarkers for 90Y Distribution on Bremsstrahlung SPECT After Resin-Based Radioembolization. Journal Of Nuclear Medicine 2019, 60: 1066-1072. PMID: 30655331, PMCID: PMC6681698, DOI: 10.2967/jnumed.118.219691.Peer-Reviewed Original ResearchMeSH KeywordsAgedAngiographyBiomarkersCarcinoma, HepatocellularEmbolization, TherapeuticFeasibility StudiesFemaleHumansImaging, Three-DimensionalLiverLiver NeoplasmsMagnetic Resonance ImagingMaleMicrospheresMiddle AgedMultimodal ImagingPrognosisRegression AnalysisRetrospective StudiesTomography, Emission-Computed, Single-PhotonTomography, X-Ray ComputedTreatment OutcomeYttrium RadioisotopesConceptsNon-HCC patientsTransarterial radioembolizationHepatocellular carcinomaBaseline imagingTumor responseTumor volumeChild-Pugh class B patientsBaseline imaging featuresClass B patientsNormal liver ratiosTotal tumor volumeSPECT/CTContrast-enhanced MRIQuantitative European AssociationMultiphasic contrast-enhanced MRIInstitutional review boardHigh TNRPreprocedural MRIChild-PughB patientsLiver criteriaTumor burdenClinical parametersHepatic malignanciesRetrospective study
2018
Irinotecan-Eluting 75–150-μm Embolics Lobar Chemoembolization in Patients with Colorectal Cancer Liver Metastases: A Prospective Single-Center Phase I Study
Fereydooni A, Letzen B, Ghani MA, Miszczuk MA, Huber S, Chapiro J, Schlachter T, Geschwind JF, Georgiades C. Irinotecan-Eluting 75–150-μm Embolics Lobar Chemoembolization in Patients with Colorectal Cancer Liver Metastases: A Prospective Single-Center Phase I Study. Journal Of Vascular And Interventional Radiology 2018, 29: 1646-1653.e5. PMID: 30337148, DOI: 10.1016/j.jvir.2018.08.010.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overAntineoplastic AgentsBiomarkers, TumorChemoembolization, TherapeuticColorectal NeoplasmsConnecticutDrug CarriersFeasibility StudiesFemaleHumansIrinotecanLiver NeoplasmsMaleMicrospheresMiddle AgedPalliative CareProspective StudiesTime FactorsTomography, X-Ray ComputedTreatment OutcomeVascular Endothelial Growth Factor AVascular Endothelial Growth Factor Receptor-1Vascular Endothelial Growth Factor Receptor-2ConceptsVascular endothelial growth factor receptor 1Transarterial chemoembolizationAdverse eventsMetastatic diseaseObjective responseColorectal cancer liver metastasesLiver-dominant metastatic diseaseMetastatic colorectal cancer refractorySingle-center phase IColorectal cancer refractoryLines of chemotherapyMedian overall survivalPrimary end pointCancer liver metastasesResponse Evaluation CriteriaOnly grade 3Drug-eluting embolicsImaging-based criteriaGrowth factor receptor 1Factor receptor 1World Health OrganizationCancer refractoryAbdominal painSystemic chemotherapyLiver metastasesPredicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma.
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 Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma. Journal Of Visualized Experiments 2018 PMID: 30371657, PMCID: PMC6235502, DOI: 10.3791/58382.Peer-Reviewed Original ResearchConceptsIntra-arterial therapyN patientsHepatocellular carcinomaTrans-arterial therapiesIntra-arterial treatmentCohort of patientsStandard of careLikelihood of responseClinical research questionsSurgical resectionNew patientsTreatment responseUnivariate associationsPatientsTraining patientsInterventional radiologyTherapyCarcinomaTreatmentImage-guided therapyOutcomesFinal modelImaging dataResectionResponsePredicting 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 imagingSensitivity and Reproducibility of Automated Feeding Artery Detection Software during Transarterial Chemoembolization of Hepatocellular Carcinoma
Chiaradia M, Izamis ML, Radaelli A, Prevoo W, Maleux G, Schlachter T, Mayer J, Luciani A, Kobeiter H, Tacher V. Sensitivity and Reproducibility of Automated Feeding Artery Detection Software during Transarterial Chemoembolization of Hepatocellular Carcinoma. Journal Of Vascular And Interventional Radiology 2018, 29: 425-431. PMID: 29402612, DOI: 10.1016/j.jvir.2017.10.025.Peer-Reviewed Original Research
2017
Intra-arterial therapy of neuroendocrine tumour liver metastases: comparing conventional TACE, drug-eluting beads TACE and yttrium-90 radioembolisation as treatment options using a propensity score analysis model
Do Minh D, Chapiro J, Gorodetski B, Huang Q, Liu C, Smolka S, Savic LJ, Wainstejn D, Lin M, Schlachter T, Gebauer B, Geschwind JF. Intra-arterial therapy of neuroendocrine tumour liver metastases: comparing conventional TACE, drug-eluting beads TACE and yttrium-90 radioembolisation as treatment options using a propensity score analysis model. European Radiology 2017, 27: 4995-5005. PMID: 28677067, PMCID: PMC5675796, DOI: 10.1007/s00330-017-4856-2.Peer-Reviewed Original ResearchConceptsMultivariate Cox proportional hazards modelConventional transarterial chemoembolisationMedian overall survivalPropensity score analysisHepatic progression-free survivalDrug-eluting beads TACEYttrium-90 radioembolisationProgression-free survivalDEB-TACELiver metastasesOverall survivalBeads TACENeuroendocrine tumor liver metastasesWorld Health Organization criteriaCox proportional hazards modelIntra-arterial therapyMethodsThis retrospective analysisResponse Evaluation CriteriaScore analysisSignificant survival benefitLonger overall survivalGastroenteropancreatic neuroendocrine tumorsLog-rank testEntire study populationProportional hazards model
2016
Advanced-stage hepatocellular carcinoma with portal vein thrombosis: conventional versus drug-eluting beads transcatheter arterial chemoembolization
Gorodetski B, Chapiro J, Schernthaner R, Duran R, Lin M, Lee H, Lenis D, Stuart EA, Nonyane BA, Pekurovsky V, Tamrazi A, Gebauer B, Schlachter T, Pawlik TM, Geschwind JF. Advanced-stage hepatocellular carcinoma with portal vein thrombosis: conventional versus drug-eluting beads transcatheter arterial chemoembolization. European Radiology 2016, 27: 526-535. PMID: 27277261, PMCID: PMC5470590, DOI: 10.1007/s00330-016-4445-9.Peer-Reviewed Original ResearchConceptsMedian overall survivalPortal venous thrombosisAdvanced-stage hepatocellular carcinomaConventional TACEDEB-TACEHepatocellular carcinomaOverall survivalAdverse eventsBeads TACEDrug-eluting bead transcatheter arterial chemoembolizationConventional trans-arterial chemoembolizationPropensity scoreDrug-eluting beads TACECommon adverse eventsConclusionOur retrospective studyEqual safety profileChild-Pugh classMethodsThis retrospective analysisPortal vein thrombosisPost-embolization syndromeTranscatheter arterial chemoembolizationStage hepatocellular carcinomaTrans-arterial chemoembolizationSub-group analysisArterial chemoembolization
2014
Transarterial chemoembolization in soft-tissue sarcoma metastases to the liver – The use of imaging biomarkers as predictors of patient survival
Chapiro J, Duran R, Lin M, Mungo B, Schlachter T, Schernthaner R, Gorodetski B, Wang Z, Geschwind JF. Transarterial chemoembolization in soft-tissue sarcoma metastases to the liver – The use of imaging biomarkers as predictors of patient survival. European Journal Of Radiology 2014, 84: 424-430. PMID: 25542065, PMCID: PMC4315698, DOI: 10.1016/j.ejrad.2014.11.034.Peer-Reviewed Original ResearchConceptsMetastatic soft tissue sarcomaProgression-free survivalConventional transarterial chemoembolizationSoft tissue sarcomasOverall survivalTumor responseTransarterial chemoembolizationPatient survivalSafety profileCox proportional hazard ratio analysisProportional hazard ratio analysisSoft tissue sarcoma metastasisMedian overall survivalSalvage therapy optionsHazard ratio analysisReliable clinical dataSize-based criteriaEASL guidelinesModified RECISTIntraarterial therapySarcoma metastasisSurvival outcomesGrade IIIKaplan-MeierTherapy options