2023
Consensus report from the 10th Global Forum for Liver Magnetic Resonance Imaging: developments in HCC management
Taouli B, Ba-Ssalamah A, Chapiro J, Chhatwal J, Fowler K, Kang T, Knobloch G, Koh D, Kudo M, Lee J, Murakami T, Pinato D, Ringe K, Song B, Tabrizian P, Wang J, Yoon J, Zeng M, Zhou J, Vilgrain V. Consensus report from the 10th Global Forum for Liver Magnetic Resonance Imaging: developments in HCC management. European Radiology 2023, 33: 9152-9166. PMID: 37500964, PMCID: PMC10730664, DOI: 10.1007/s00330-023-09928-y.Peer-Reviewed Original ResearchConceptsGadoxetic acid-enhanced magnetic resonance imagingLiver magnetic resonance imagingMagnetic resonance imagingHCC managementResonance imagingOutcome of HCCScreening/surveillanceLiver cancer screeningPrediction of prognosisWestern guidelinesCancer screeningLiver surgeonsLiver surgeryConsensus statementHCC screeningTreatment responseConsensus reportLiver cancerInterventional radiologistsClinical relevanceClinical practiceGadoxetic acidEmerging DataHCCDiagnosisConsensus report from the 10th global forum for liver magnetic resonance imaging: multidisciplinary team discussion
Taouli B, Ba-Ssalamah A, Chapiro J, Chhatwal J, Fowler K, Kang T, Knobloch G, Koh D, Kudo M, Lee J, Murakami T, Pinato D, Ringe K, Song B, Tabrizian P, Wang J, Yoon J, Zeng M, Zhou J, Vilgrain V. Consensus report from the 10th global forum for liver magnetic resonance imaging: multidisciplinary team discussion. European Radiology 2023, 33: 9167-9181. PMID: 37439935, PMCID: PMC10667403, DOI: 10.1007/s00330-023-09919-z.Peer-Reviewed Original ResearchMeSH KeywordsCarcinoma, HepatocellularConsensusContrast MediaGadolinium DTPAHumansLiver NeoplasmsMagnetic Resonance ImagingMagnetic Resonance SpectroscopyPatient Care TeamConceptsLiver magnetic resonance imagingLiver surgeonsMagnetic resonance imagingHCC managementInterventional radiologistsResonance imagingLate-stage HCCMultidisciplinary team discussionMultidisciplinary tumor boardMultidisciplinary team approachHepatocellular carcinoma managementLiver cancer patientsCancer patientsTumor boardConsensus reportClinical relevanceTeam approachMultidisciplinary expertsOncologistsSurgeonsTeam discussionRadiologistsImagingMultidisciplinary facultyManagementPredicting tumor recurrence on baseline MR imaging in patients with early-stage hepatocellular carcinoma using deep machine learning
Kucukkaya A, Zeevi T, Chai N, Raju R, Haider S, Elbanan M, Petukhova-Greenstein A, Lin M, Onofrey J, Nowak M, Cooper K, Thomas E, Santana J, Gebauer B, Mulligan D, Staib L, Batra R, Chapiro J. Predicting tumor recurrence on baseline MR imaging in patients with early-stage hepatocellular carcinoma using deep machine learning. Scientific Reports 2023, 13: 7579. PMID: 37165035, PMCID: PMC10172370, DOI: 10.1038/s41598-023-34439-7.Peer-Reviewed Original ResearchMeSH KeywordsCarcinoma, HepatocellularHumansLiver NeoplasmsMachine LearningMagnetic Resonance ImagingNeoplasm Recurrence, LocalRetrospective Studies
2022
MR Imaging–Based In Vivo Macrophage Imaging to Monitor Immune Response after Radiofrequency Ablation of the Liver
Santana J, Petukhova-Greenstein A, Gross M, Hyder F, Pekurovsky V, Gottwald L, Boustani A, Walsh J, Kucukkaya A, Malpani R, Madoff D, Goldberg S, Ahmed M, Joshi N, Coman D, Chapiro J. MR Imaging–Based In Vivo Macrophage Imaging to Monitor Immune Response after Radiofrequency Ablation of the Liver. Journal Of Vascular And Interventional Radiology 2022, 34: 395-403.e5. PMID: 36423815, PMCID: PMC11042914, DOI: 10.1016/j.jvir.2022.11.013.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsContrast MediaImmunityLiverMacrophagesMagnetic Resonance ImagingMiceMice, Inbred C57BLRadiofrequency AblationConceptsImmune responseT1-weighted MRPrussian blue stainingRadiofrequency ablationRF ablationC57BL/6 wild-type miceMR imagingDose-escalation studyLocal immune responseMass cytometryWild-type miceRadiological-pathological correlationBlue stainingT1-weighted MR imagingHepatic radiofrequency ablationCD68 antibodyUntreated lobeVivo doseHepatic RF ablationVivo macrophagesMacrophagesMiceMR imaging scannerCoagulation areaCD68Machine Learning Models for Prediction of Posttreatment Recurrence in Early-Stage Hepatocellular Carcinoma Using Pretreatment Clinical and MRI Features: A Proof-of-Concept Study.
Iseke S, Zeevi T, Kucukkaya AS, Raju R, Gross M, Haider SP, Petukhova-Greenstein A, Kuhn TN, Lin M, Nowak M, Cooper K, Thomas E, Weber MA, Madoff DC, Staib L, Batra R, Chapiro J. Machine Learning Models for Prediction of Posttreatment Recurrence in Early-Stage Hepatocellular Carcinoma Using Pretreatment Clinical and MRI Features: A Proof-of-Concept Study. American Journal Of Roentgenology 2022, 220: 245-255. PMID: 35975886, PMCID: PMC10015590, DOI: 10.2214/ajr.22.28077.Peer-Reviewed Original ResearchMeSH KeywordsCarcinoma, HepatocellularFemaleHumansLiver NeoplasmsMagnetic Resonance ImagingMaleMiddle AgedNeoplasm Recurrence, LocalRetrospective StudiesRisk FactorsConceptsEarly-stage hepatocellular carcinomaLiver transplantHepatocellular carcinomaImaging featuresPosttreatment recurrenceOrgan allocationMean AUCLiver transplant eligibilityPretreatment clinical characteristicsPretreatment MRI examinationsKaplan-Meier analysisKaplan-Meier curvesClinical characteristicsImaging surveillanceTherapy allocationTransplant eligibilityUnderwent treatmentClinical parametersRetrospective studyUnpredictable complicationMRI dataConcept studyPoor survivalClinical impactPretreatment MRIMR Imaging Biomarkers for the Prediction of Outcome after Radiofrequency Ablation of Hepatocellular Carcinoma: Qualitative and Quantitative Assessments of the Liver Imaging Reporting and Data System and Radiomic Features
Petukhova-Greenstein A, Zeevi T, Yang J, Chai N, DiDomenico P, Deng Y, Ciarleglio M, Haider SP, Onyiuke I, Malpani R, Lin M, Kucukkaya AS, Gottwald LA, Gebauer B, Revzin M, Onofrey J, Staib L, Gunabushanam G, Taddei T, Chapiro J. MR Imaging Biomarkers for the Prediction of Outcome after Radiofrequency Ablation of Hepatocellular Carcinoma: Qualitative and Quantitative Assessments of the Liver Imaging Reporting and Data System and Radiomic Features. Journal Of Vascular And Interventional Radiology 2022, 33: 814-824.e3. PMID: 35460887, PMCID: PMC9335926, DOI: 10.1016/j.jvir.2022.04.006.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkersCarcinoma, HepatocellularCatheter AblationContrast MediaHumansLiver NeoplasmsMagnetic Resonance ImagingRetrospective StudiesConceptsProgression-free survivalPoor progression-free survivalLiver Imaging ReportingHepatocellular carcinomaMR imaging biomarkersRadiomics signatureRadiofrequency ablationRadiomic featuresImaging biomarkersImaging ReportingFirst follow-up imagingMedian progression-free survivalRF ablationEarly-stage hepatocellular carcinomaPretreatment magnetic resonanceFirst-line treatmentMultifocal hepatocellular carcinomaSelection operator Cox regression modelTherapy-naïve patientsEarly-stage diseaseKaplan-Meier analysisCox regression modelLog-rank testFollow-up imagingPrediction of outcomeOptimization 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
Improved performance and consistency of deep learning 3D liver segmentation with heterogeneous cancer stages in magnetic resonance imaging
Gross M, Spektor M, Jaffe A, Kucukkaya AS, Iseke S, Haider SP, Strazzabosco M, Chapiro J, Onofrey JA. Improved performance and consistency of deep learning 3D liver segmentation with heterogeneous cancer stages in magnetic resonance imaging. PLOS ONE 2021, 16: e0260630. PMID: 34852007, PMCID: PMC8635384, DOI: 10.1371/journal.pone.0260630.Peer-Reviewed Original ResearchIdentifying enhancement-based staging markers on baseline MRI in patients with colorectal cancer liver metastases undergoing intra-arterial tumor therapy
Ghani MA, Fereydooni A, Chen E, Letzen B, Laage-Gaupp F, Nezami N, Deng Y, Gan G, Thakur V, Lin M, Papademetris X, Schernthaner RE, Huber S, Chapiro J, Hong K, Georgiades C. Identifying enhancement-based staging markers on baseline MRI in patients with colorectal cancer liver metastases undergoing intra-arterial tumor therapy. European Radiology 2021, 31: 8858-8867. PMID: 34061209, PMCID: PMC8848338, DOI: 10.1007/s00330-021-08058-7.Peer-Reviewed Original ResearchMeSH KeywordsBiomarkersCarcinoma, HepatocellularChemoembolization, TherapeuticColorectal NeoplasmsHumansLiver NeoplasmsMagnetic Resonance ImagingRetrospective StudiesTumor BurdenConceptsColorectal cancer liver metastasesCancer liver metastasesTotal tumor volumeIntra-arterial therapyTotal liver volumeLiver metastasesTumor volumeTumor burdenTumor diameterPatient survivalBaseline MRILiver volumeMultivariable Cox proportional hazards modelsKaplan-Meier survival curvesWhole liverCox proportional hazards modelKaplan-Meier methodPrognostic staging systemSurvival of patientsColorectal cancer metastasisMethodsThis retrospective studyPre-treatment MRIProportional hazards modelAppropriate cutoff valueHR 1.7Role 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 imagesHepatic Radiofrequency Ablation
Collettini F, Brangsch J, Reimann C, Chapiro J, Savic LJ, Buchholz R, Keller S, Hamm B, Goldberg SN, Makowski MR. Hepatic Radiofrequency Ablation. Investigative Radiology 2021, 56: 591-598. PMID: 33787536, DOI: 10.1097/rli.0000000000000777.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsCatheter AblationDisease Models, AnimalMacrophagesMagnetic Resonance ImagingRabbitsRadiofrequency AblationElastin-specific MRI of extracellular matrix-remodelling following hepatic radiofrequency-ablation in a VX2 liver tumor model
Collettini F, Reimann C, Brangsch J, Chapiro J, Savic LJ, Onthank DC, Robinson SP, Karst U, Buchholz R, Keller S, Hamm B, Goldberg SN, Makowski MR. Elastin-specific MRI of extracellular matrix-remodelling following hepatic radiofrequency-ablation in a VX2 liver tumor model. Scientific Reports 2021, 11: 6814. PMID: 33767303, PMCID: PMC7994448, DOI: 10.1038/s41598-021-86417-6.Peer-Reviewed Original ResearchDeep learning–assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver
Oestmann PM, Wang CJ, Savic LJ, Hamm CA, Stark S, Schobert I, Gebauer B, Schlachter T, Lin M, Weinreb JC, Batra R, Mulligan D, Zhang X, Duncan JS, Chapiro J. Deep learning–assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver. European Radiology 2021, 31: 4981-4990. PMID: 33409782, PMCID: PMC8222094, DOI: 10.1007/s00330-020-07559-1.Peer-Reviewed Original ResearchMeSH KeywordsCarcinoma, HepatocellularContrast MediaDeep LearningHumansLiver NeoplasmsMagnetic Resonance ImagingRetrospective StudiesConceptsNon-HCC lesionsHepatocellular carcinomaHCC lesionsAtypical imagingGrading systemLI-RADS criteriaAtypical imaging featuresPrimary liver cancerTypical hepatocellular carcinomaAtypical hepatocellular carcinomaContrast-enhanced MRISensitivity/specificityLiver transplantMethodsThis IRBRetrospective studyLiver malignanciesImaging featuresLiver cancerAtypical featuresConclusionThis studyLesionsMRIClinical applicationCarcinomaImage-based diagnosis
2020
Reliable prediction of survival in advanced-stage hepatocellular carcinoma treated with sorafenib: comparing 1D and 3D quantitative tumor response criteria on MRI
Doemel LA, Chapiro J, Laage Gaupp F, Savic LJ, Kucukkaya AS, Petukhova A, Tefera J, Zeevi T, Lin M, Schlachter T, Jaffe A, Strazzabosco M, Patel T, Stein SM. Reliable prediction of survival in advanced-stage hepatocellular carcinoma treated with sorafenib: comparing 1D and 3D quantitative tumor response criteria on MRI. European Radiology 2020, 31: 2737-2746. PMID: 33123796, PMCID: PMC8043967, DOI: 10.1007/s00330-020-07381-9.Peer-Reviewed Original ResearchMeSH KeywordsAntineoplastic AgentsCarcinoma, HepatocellularHumansLiver NeoplasmsMagnetic Resonance ImagingPhenylurea CompoundsRetrospective StudiesSorafenibTreatment OutcomeConceptsTumor response criteriaOverall survivalAdvanced-stage HCCDisease progressionSorafenib therapyDisease controlResponse criteriaCox proportional hazards regression modelAdvanced-stage hepatocellular carcinomaProportional hazards regression modelsDCE-MRIInitiation of sorafenibTumor response analysisMultivariable Cox regressionIndependent risk factorMethodsThis retrospective analysisIndependent prognostic factorInitiation of treatmentKaplan-Meier analysisKaplan-Meier curvesHazards regression modelsLog-rank testStratification of patientsTotal tumor volumeArterial phase MRIQuantitative volumetric assessment of baseline enhancing tumor volume as an imaging biomarker predicts overall survival in patients with glioblastoma
Auer TA, Della Seta M, Collettini F, Chapiro J, Zschaeck S, Ghadjar P, Badakhshi H, Florange J, Hamm B, Budach V, Kaul D. Quantitative volumetric assessment of baseline enhancing tumor volume as an imaging biomarker predicts overall survival in patients with glioblastoma. Acta Radiologica 2020, 62: 1200-1207. PMID: 32938221, DOI: 10.1177/0284185120953796.Peer-Reviewed Original ResearchConceptsProgression-free survivalOverall survivalTumor volumeGlioblastoma multiformeMagnetic resonance imagingMultivariable analysisCommon malignant primary brain tumorIntracranial progression-free survivalKarnofsky performance status scoreCranial magnetic resonance imagingMalignant primary brain tumorMedian overall survivalPerformance status scoreOS of patientsCox regression modelSignificant prognostic rolePrimary brain tumorsContrast-enhanced MRI sequencesQuantitative volumetric assessmentResection statusPrognostic roleMethyltransferase statusWorse prognosisEntire cohortNon-invasive methodMolecular MRI of the Immuno-Metabolic Interplay in a Rabbit Liver Tumor Model: A Biomarker for Resistance Mechanisms in Tumor-targeted Therapy?
Savic LJ, Doemel LA, Schobert IT, Montgomery RR, Joshi N, Walsh JJ, Santana J, Pekurovsky V, Zhang X, Lin M, Adam L, Boustani A, Duncan J, Leng L, Bucala RJ, Goldberg SN, Hyder F, Coman D, Chapiro J. Molecular MRI of the Immuno-Metabolic Interplay in a Rabbit Liver Tumor Model: A Biomarker for Resistance Mechanisms in Tumor-targeted Therapy? Radiology 2020, 296: 575-583. PMID: 32633675, PMCID: PMC7434651, DOI: 10.1148/radiol.2020200373.Peer-Reviewed Original ResearchConceptsImmuno-oncologic therapiesConventional transarterial chemoembolizationTransarterial chemoembolizationIntratumoral immune cell infiltrationMR spectroscopyRabbit liver tumor modelPrussian blue iron stainingAntigen-presenting immune cellsIntra-arterial infusionImmune cell infiltrationNew Zealand white rabbitsLiver tumor modelImmune cell exclusionLiver cancer modelContrast material administrationT2-weighted MRIZealand white rabbitsT2-weighted imagingResistance mechanismsImmunosuppressive tumorHLA-DRCell infiltrationImmune cellsImmunohistochemistry stainingRing enhancementAutomated detection and delineation of hepatocellular carcinoma on multiphasic contrast-enhanced MRI using deep learning
Bousabarah K, Letzen B, Tefera J, Savic L, Schobert I, Schlachter T, Staib LH, Kocher M, Chapiro J, Lin M. Automated detection and delineation of hepatocellular carcinoma on multiphasic contrast-enhanced MRI using deep learning. Abdominal Radiology 2020, 46: 216-225. PMID: 32500237, PMCID: PMC7714704, DOI: 10.1007/s00261-020-02604-5.Peer-Reviewed Original ResearchMeSH KeywordsCarcinoma, HepatocellularDeep LearningHumansLiver NeoplasmsMagnetic Resonance ImagingRetrospective StudiesConceptsDeep convolutional neural networkAverage false positive rateDice similarity coefficientU-NetDeep learning algorithmsConvolutional neural networkTest setMean Dice similarity coefficientRandom forest classifierDCNN methodDCNN approachDeep learningNet architectureLearning algorithmNeural networkLiver segmentationManual 3D segmentationForest classifierGround truthManual segmentationFalse positive rateCorresponding segmentationSegmentationMultiphasic contrast-enhanced MRIThresholdingNeutrophil-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
Comparing HCC arterial tumour vascularisation on baseline imaging and after lipiodol cTACE: how do estimations of enhancing tumour volumes differ on contrast-enhanced MR and CT?
Luedemann WM, Geisel D, Gebauer B, Schnapauff D, Chapiro J, Wieners G, Steffen I, Kahn J. Comparing HCC arterial tumour vascularisation on baseline imaging and after lipiodol cTACE: how do estimations of enhancing tumour volumes differ on contrast-enhanced MR and CT? European Radiology 2019, 30: 1601-1608. PMID: 31811428, DOI: 10.1007/s00330-019-06430-2.Peer-Reviewed Original ResearchMeSH KeywordsArteriesCarcinoma, HepatocellularContrast MediaEthiodized OilFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedRetrospective StudiesTomography, X-Ray ComputedTumor BurdenConceptsLipiodol depositionNative CT scansTumor volumeTumour vascularisationTechnical successHCC patientsCE-CTCT scanDifferent imaging modalitiesImaging modalitiesContrast-enhanced CTContrast-enhanced MRPearson correlation coefficientBaseline imagingSubgroup analysisRespective regression coefficientsCT groupLinear regression analysisCE-MRICE-MRVascularisationCTContrast phasesPatientsCTACE