2021
Quantitative Automated Segmentation of Lipiodol Deposits on Cone-Beam CT Imaging Acquired during Transarterial Chemoembolization for Liver Tumors: A Deep Learning Approach
Malpani R, Petty CW, Yang J, Bhatt N, Zeevi T, Chockalingam V, Raju R, Petukhova-Greenstein A, Santana JG, Schlachter TR, Madoff DC, Chapiro J, Duncan J, Lin M. Quantitative Automated Segmentation of Lipiodol Deposits on Cone-Beam CT Imaging Acquired during Transarterial Chemoembolization for Liver Tumors: A Deep Learning Approach. Journal Of Vascular And Interventional Radiology 2021, 33: 324-332.e2. PMID: 34923098, PMCID: PMC8972393, DOI: 10.1016/j.jvir.2021.12.017.Peer-Reviewed Original ResearchComparison of metabolic and immunologic responses to transarterial chemoembolization with different chemoembolic regimens in a rabbit VX2 liver tumor model
Doemel LA, Santana JG, Savic LJ, Gaupp FML, Borde T, Petukhova-Greenstein A, Kucukkaya AS, Schobert IT, Hamm CA, Gebauer B, Walsh JJ, Rexha I, Hyder F, Lin M, Madoff DC, Schlachter T, Chapiro J, Coman D. Comparison of metabolic and immunologic responses to transarterial chemoembolization with different chemoembolic regimens in a rabbit VX2 liver tumor model. European Radiology 2021, 32: 2437-2447. PMID: 34718844, PMCID: PMC9359419, DOI: 10.1007/s00330-021-08337-3.Peer-Reviewed Original ResearchConceptsDrug-eluting embolicsImmune cell infiltrationAntigen-presenting cellsBicarbonate infusionConventional TACEDEE-TACETransarterial chemotherapyCell infiltrationImmune cellsPeritumoral infiltrationT lymphocytesIntratumoral immune cell infiltrationTumor modelRabbit VX2 liver tumor modelImmunological tumor microenvironmentVX2 liver tumor modelIntra-arterial therapyIntra-arterial treatmentRabbit VX2 tumor modelLiver tumor modelTumor-bearing rabbitsVX2 tumor modelMann-Whitney U testIntratumoral presenceTransarterial chemoembolizationLipiodol as an intra-procedural imaging biomarker for liver tumor response to transarterial chemoembolization: Post-hoc analysis of a prospective clinical trial
Letzen BS, Malpani R, Miszczuk M, de Ruiter QMB, Petty CW, Rexha I, Nezami N, Laage-Gaupp F, Lin M, Schlachter TR, Chapiro J. Lipiodol as an intra-procedural imaging biomarker for liver tumor response to transarterial chemoembolization: Post-hoc analysis of a prospective clinical trial. Clinical Imaging 2021, 78: 194-200. PMID: 34022765, PMCID: PMC8364875, DOI: 10.1016/j.clinimag.2021.05.007.Peer-Reviewed Original ResearchConceptsConventional trans-arterial chemoembolizationMedian overall survivalProspective clinical trialsLipiodol depositionTumor responsePredictive biomarkersClinical trialsModified Response Evaluation CriteriaPost-TACE CTResponse Evaluation CriteriaMetastatic liver cancerKaplan-Meier analysisTrans-arterial chemoembolizationTumor response criteriaLiver tumor responsePrediction of survivalSelective drug targetingArterial embolizationLiver metastasesOverall survivalBland-Altman plotsTransarterial chemoembolizationPortal veinTumor respondersHepatocellular carcinoma
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 responseProspective study of Lipiodol distribution as an imaging marker for doxorubicin pharmacokinetics during conventional transarterial chemoembolization of liver malignancies
Savic LJ, Chapiro J, Funai E, Bousabarah K, Schobert IT, Isufi E, Geschwind JH, Stark S, He P, Rudek MA, Perez Lozada JC, Ayyagari R, Pollak J, Schlachter T. Prospective study of Lipiodol distribution as an imaging marker for doxorubicin pharmacokinetics during conventional transarterial chemoembolization of liver malignancies. European Radiology 2020, 31: 3002-3014. PMID: 33063185, DOI: 10.1007/s00330-020-07380-w.Peer-Reviewed Original ResearchConceptsConventional transarterial chemoembolizationProspective clinical trialsTumor responseConventional TACEAdverse eventsTransarterial chemoembolizationLiver malignanciesClinical trialsMarker predictiveTumor volumeExact testChild-Pugh B classVolumetric tumor responseChild-Pugh BPeak concentrationNon-compartmental analysisFisher's exact testDose normalizationQuantitative European AssociationStandard non-compartmental analysisTime-concentration curveLiver criteriaLobar distributionDoxorubicin pharmacokineticsNeuroendocrine metastasesMolecular 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
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