2023
Predicting 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 Research
2022
Machine 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 ResearchConceptsEarly-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 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
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 ResearchThermal 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
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 ResearchConceptsTumor 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 MRI