2024
Outcomes of repeat conventional transarterial chemoembolization in patients with liver metastases
Ghabili K, Windham-Herman A, Konstantinidis M, Murali N, Borde T, Adam L, Laage-Gaupp F, Lin M, Chapiro J, Georgiades C, Nezami N. Outcomes of repeat conventional transarterial chemoembolization in patients with liver metastases. Annals Of Hepatology 2024, 29: 101529. PMID: 39033928, PMCID: PMC11558520, DOI: 10.1016/j.aohep.2024.101529.Peer-Reviewed Original ResearchConventional transarterial chemoembolizationLiver metastasesNeuroendocrine tumorsColorectal carcinomaTransarterial chemoembolizationOverall survivalLung cancerAssociated with improved patient survivalManagement of liver metastasesMetastatic liver lesionsSingle-institution analysisNonresponding patientsSurvival outcomesPatient survivalResponse assessmentTarget lesionsMetastasisLiver lesionsPatientsResponse rateChemoembolizationSurvivalLiverLesionsCancer
2022
Optimization of the BCLC Staging System for Locoregional Therapy for Hepatocellular Carcinoma by Using Quantitative Tumor Burden Imaging Biomarkers at MRI.
Borde T, Nezami N, Laage Gaupp F, Savic LJ, Taddei T, Jaffe A, Strazzabosco M, Lin M, Duran R, Georgiades C, Hong K, Chapiro J. Optimization of the BCLC Staging System for Locoregional Therapy for Hepatocellular Carcinoma by Using Quantitative Tumor Burden Imaging Biomarkers at MRI. Radiology 2022, 304: 228-237. PMID: 35412368, PMCID: PMC9270683, DOI: 10.1148/radiol.212426.Peer-Reviewed Original ResearchConceptsMedian overall survivalAdvanced-stage hepatocellular carcinomaTransarterial chemoembolizationHepatocellular carcinomaBCLC BBCLC COverall survivalTumor burdenBarcelona Clinic Liver Cancer (BCLC) staging systemLiver Cancer staging systemCancer (AJCC) staging systemConventional transarterial chemoembolizationDrug-eluting beadsAllocation of patientsContrast-enhanced MRIBackground PatientsSurvival benefitRetrospective studyStaging systemC tumorsTumor volumePatientsHeterogeneous patientsMonthsChemoembolization
2021
Role of 3D quantitative tumor analysis for predicting overall survival after conventional chemoembolization of intrahepatic cholangiocarcinoma
Rexha I, Laage-Gaupp F, Chapiro J, Miszczuk MA, van Breugel JMM, Lin M, Konstantinidis M, Duran R, Gebauer B, Georgiades C, Hong K, Nezami N. Role of 3D quantitative tumor analysis for predicting overall survival after conventional chemoembolization of intrahepatic cholangiocarcinoma. Scientific Reports 2021, 11: 9337. PMID: 33927226, PMCID: PMC8085245, DOI: 10.1038/s41598-021-88426-x.Peer-Reviewed Original ResearchConceptsTotal tumor volumeConventional transarterial chemoembolizationTumor diameterIntrahepatic cholangiocarcinomaOverall survivalTumor areaICC patientsTumor volumeHigh tumor burden groupTumor analysisOS of patientsHazard ratioTransarterial chemoembolizationTumor burdenBurden groupConventional chemoembolizationHTB groupRetrospective analysisPatientsSurvival curvesMultivariate analysisChemoembolizationCholangiocarcinomaETVBaseline images
2020
Lipiodol as an Imaging Biomarker of Tumor Response After Conventional Transarterial Chemoembolization: Prospective Clinical Validation in Patients with Primary and Secondary Liver Cancer
Miszczuk MA, Chapiro J, Geschwind JH, Thakur V, Nezami N, Laage-Gaupp F, Kulon M, van Breugel JMM, Fereydooni A, Lin M, Savic LJ, Tegel B, Wahlin T, Funai E, Schlachter T. Lipiodol as an Imaging Biomarker of Tumor Response After Conventional Transarterial Chemoembolization: Prospective Clinical Validation in Patients with Primary and Secondary Liver Cancer. Translational Oncology 2020, 13: 100742. PMID: 32092672, PMCID: PMC7036424, DOI: 10.1016/j.tranon.2020.01.003.Peer-Reviewed Original Research
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