2024
AI-driven Patient-Selection For Preoperative Portal Vein Embolization For Patients With Colorectal Cancer Liver Metastases
Kuhn T, Engelhardt W, Kahl V, Alkukhun A, Gross M, Iseke S, Onofrey J, Covey A, Camacho Vasquez J, Kawaguchi Y, Hasegawa K, Odisio B, Vauthey J, Antoch G, Chapiro J, Madoff D. AI-driven Patient-Selection For Preoperative Portal Vein Embolization For Patients With Colorectal Cancer Liver Metastases. Journal Of Vascular And Interventional Radiology 2024 PMID: 39638087, DOI: 10.1016/j.jvir.2024.11.025.Peer-Reviewed Original ResearchTotal liver volumeMetastatic colorectal cancer patientsPreoperative portal vein embolizationColorectal cancer liver metastasesPortal vein embolizationCancer liver metastasesMulticenter retrospective studyColorectal cancer patientsStudent's t-testBoard-certified radiologistsVein embolizationConsecutive patientsLiver metastasesLiver volumePatient selectionRetrospective studyCancer patientsRadiomic featuresInclusion criteriaPatientsSemi-automatic segmentationLab valuesT-testSDAUCAutomated graded prognostic assessment for patients with hepatocellular carcinoma using machine learning
Gross M, Haider S, Ze’evi T, Huber S, Arora S, Kucukkaya A, Iseke S, Gebauer B, Fleckenstein F, Dewey M, Jaffe A, Strazzabosco M, Chapiro J, Onofrey J. Automated graded prognostic assessment for patients with hepatocellular carcinoma using machine learning. European Radiology 2024, 34: 6940-6952. PMID: 38536464, PMCID: PMC11399284, DOI: 10.1007/s00330-024-10624-8.Peer-Reviewed Original ResearchContrast-enhanced magnetic resonance imagingMagnetic resonance imagingClinical staging systemTime of diagnosisHepatocellular carcinomaClinical dataMortality risk predictionOverall survivalStaging systemRadiomic featuresManagement of hepatocellular carcinomaPersonalized follow-up strategiesAssociated with OSMethodsThis retrospective studyHepatocellular carcinoma patientsBaseline magnetic resonance imagingMRI radiomics featuresIndependent validation cohortHarrell's C-indexRisk predictionFollow-up strategiesHigh-risk groupPredictive risk scoreRadiomics feature extractionMedian timeAutomated MRI liver segmentation for anatomical segmentation, liver volumetry, and the extraction of radiomics
Gross M, Huber S, Arora S, Ze’evi T, Haider S, Kucukkaya A, Iseke S, Kuhn T, Gebauer B, Michallek F, Dewey M, Vilgrain V, Sartoris R, Ronot M, Jaffe A, Strazzabosco M, Chapiro J, Onofrey J. Automated MRI liver segmentation for anatomical segmentation, liver volumetry, and the extraction of radiomics. European Radiology 2024, 34: 5056-5065. PMID: 38217704, PMCID: PMC11245591, DOI: 10.1007/s00330-023-10495-5.Peer-Reviewed Original ResearchMagnetic resonance imagingRadiomics feature extractionLiver volumetryIntraclass correlation coefficientRadiomic featuresLiver segmentationAutomated liver volumetryHepatocellular carcinoma patientsMann-Whitney U testAutomated liver segmentationManual segmentationQuantitative imaging biomarkersCarcinoma patientsRetrospective studyInstitutional databaseAnatomical localizationClinical relevanceManual volumetryMann-WhitneyU testExternal validationInternal test setImaging biomarkersInclusion criteriaResultsIn total
2022
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
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 ResearchConceptsProgression-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 outcome
2020
Neutrophil-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 growth