2024
A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information
Ramakrishnan D, Jekel L, Chadha S, Janas A, Moy H, Maleki N, Sala M, Kaur M, Petersen G, Merkaj S, von Reppert M, Baid U, Bakas S, Kirsch C, Davis M, Bousabarah K, Holler W, Lin M, Westerhoff M, Aneja S, Memon F, Aboian M. A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information. Scientific Data 2024, 11: 254. PMID: 38424079, PMCID: PMC10904366, DOI: 10.1038/s41597-024-03021-9.Peer-Reviewed Original ResearchConceptsWhole-brain radiotherapyStereotactic radiosurgeryT1 post-contrastBrain metastasesPost-contrastSide effectsImage informationArtificial intelligenceAssociated with cognitive side effectsContrast-enhancing lesionsQuality of datasetsCognitive side effectsFLAIR MR imagesValidation of AI modelsBrain radiotherapyLimitations of algorithmsStandard treatmentAI modelsMR imagingAI networksContrast enhancementClinical settingSegmentation workflowDatasetClinical adoption
2023
Application of novel PACS-based informatics platform to identify imaging based predictors of CDKN2A allelic status in glioblastomas
Tillmanns N, Lost J, Tabor J, Vasandani S, Vetsa S, Marianayagam N, Yalcin K, Erson-Omay E, von Reppert M, Jekel L, Merkaj S, Ramakrishnan D, Avesta A, de Oliveira Santo I, Jin L, Huttner A, Bousabarah K, Ikuta I, Lin M, Aneja S, Turowski B, Aboian M, Moliterno J. Application of novel PACS-based informatics platform to identify imaging based predictors of CDKN2A allelic status in glioblastomas. Scientific Reports 2023, 13: 22942. PMID: 38135704, PMCID: PMC10746716, DOI: 10.1038/s41598-023-48918-4.Peer-Reviewed Original ResearchConceptsInformatics platformDeep learning algorithmsImaging featuresCDKN2A alterationsLearning algorithmHeterozygous lossHomozygous deletionLarge datasetsDeep white matter invasionGBM molecular subtypesNew informaticsQualitative imaging biomarkersWhole-exome sequencingQualitative imaging featuresGBM resectionRadiographic evidenceWorse prognosisPACSMolecular subtypesPial invasionImaging biomarkersCDKN2A mutationsAllele statusNoninvasive identificationMagnetic resonance imagesSystematic Literature Review of Machine Learning Algorithms Using Pretherapy Radiologic Imaging for Glioma Molecular Subtype Prediction
Lost J, Verma T, Jekel L, von Reppert M, Tillmanns N, Merkaj S, Petersen G, Bahar R, Gordem A, Haider M, Subramanian H, Brim W, Ikuta I, Omuro A, Conte G, Marquez-Nostra B, Avesta A, Bousabarah K, Nabavizadeh A, Kazerooni A, Aneja S, Bakas S, Lin M, Sabel M, Aboian M. Systematic Literature Review of Machine Learning Algorithms Using Pretherapy Radiologic Imaging for Glioma Molecular Subtype Prediction. American Journal Of Neuroradiology 2023, 44: 1126-1134. PMID: 37770204, PMCID: PMC10549943, DOI: 10.3174/ajnr.a8000.Peer-Reviewed Original ResearchPACS-integrated machine learning breast density classifier: clinical validation
Lewin J, Schoenherr S, Seebass M, Lin M, Philpotts L, Etesami M, Butler R, Durand M, Heller S, Heacock L, Moy L, Tocino I, Westerhoff M. PACS-integrated machine learning breast density classifier: clinical validation. Clinical Imaging 2023, 101: 200-205. PMID: 37421715, DOI: 10.1016/j.clinimag.2023.06.023.Peer-Reviewed Original ResearchPredicting 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
DuDoSS: Deep‐learning‐based dual‐domain sinogram synthesis from sparsely sampled projections of cardiac SPECT
Chen X, Zhou B, Xie H, Miao T, Liu H, Holler W, Lin M, Miller EJ, Carson RE, Sinusas AJ, Liu C. DuDoSS: Deep‐learning‐based dual‐domain sinogram synthesis from sparsely sampled projections of cardiac SPECT. Medical Physics 2022, 50: 89-103. PMID: 36048541, PMCID: PMC9868054, DOI: 10.1002/mp.15958.Peer-Reviewed Original ResearchConceptsLow reconstruction accuracySynthetic projectionsAbsolute percent errorImage predictionSPECT image reconstructionImage domainSinogram synthesisGround truthReconstruction accuracyImage reconstructionSinogram domainProjection angleData acquisitionMean square errorFast data acquisitionImagesReconstruction artifactsSPECT imagesSquare errorMachine 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 MRIAnalysis of Tumor Burden as a Biomarker for Patient Survival with Neuroendocrine Tumor Liver Metastases Undergoing Intra-Arterial Therapies: A Single-Center Retrospective Analysis
Miszczuk M, Chapiro J, Do Minh D, van Breugel JMM, Smolka S, Rexha I, Tegel B, Lin M, Savic LJ, Hong K, Georgiades C, Nezami N. Analysis of Tumor Burden as a Biomarker for Patient Survival with Neuroendocrine Tumor Liver Metastases Undergoing Intra-Arterial Therapies: A Single-Center Retrospective Analysis. CardioVascular And Interventional Radiology 2022, 45: 1494-1502. PMID: 35941241, PMCID: PMC9587516, DOI: 10.1007/s00270-022-03209-9.Peer-Reviewed Original ResearchConceptsNeuroendocrine tumor liver metastasesMedian overall survivalIntra-arterial therapyLow tumor burdenTumor burdenOverall survivalLiver metastasesPrognostic factorsTumor diameterTB groupLonger median overall survivalRetrospective single-center analysisSingle-center retrospective analysisHigh TB groupLow TB groupRespective hazard ratiosHigh tumor burdenSingle-center analysisIndependent prognostic factorStrong prognostic factorDrug-eluting beadsLargest liver lesionPrediction of survivalHazard ratioPatient survivalResponse assessment methods for patients with hepatic metastasis from rare tumor primaries undergoing transarterial chemoembolization
Adam LC, Savic LJ, Chapiro J, Letzen B, Lin M, Georgiades C, Hong KK, Nezami N. Response assessment methods for patients with hepatic metastasis from rare tumor primaries undergoing transarterial chemoembolization. Clinical Imaging 2022, 89: 112-119. PMID: 35777239, PMCID: PMC9470015, DOI: 10.1016/j.clinimag.2022.06.013.Peer-Reviewed Original ResearchConceptsConventional transarterial chemoembolizationLipiodol depositionHepatic metastasesResponse assessment methodsPartial responseTransarterial chemoembolizationResponse assessmentTumor primaryStratification of responseRare primary tumorResponse Evaluation CriteriaRetrospective bicentric studyAssessment of responseQuantitative European AssociationLiver metastasesMajor complicationsBicentric studyPrimary tumorRare tumorEarly surrogateTreatment responseCT scanPatientsRECISTSolid tumorsMR 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 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 patientsMonthsChemoembolizationDirect and indirect strategies of deep-learning-based attenuation correction for general purpose and dedicated cardiac SPECT
Chen X, Zhou B, Xie H, Shi L, Liu H, Holler W, Lin M, Liu YH, Miller EJ, Sinusas AJ, Liu C. Direct and indirect strategies of deep-learning-based attenuation correction for general purpose and dedicated cardiac SPECT. European Journal Of Nuclear Medicine And Molecular Imaging 2022, 49: 3046-3060. PMID: 35169887, PMCID: PMC9253078, DOI: 10.1007/s00259-022-05718-8.Peer-Reviewed Original Research
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 ResearchWhat's Needed to Bridge the Gap Between US FDA Clearance and Real-world Use of AI Algorithms
Lin M. What's Needed to Bridge the Gap Between US FDA Clearance and Real-world Use of AI Algorithms. Academic Radiology 2021, 29: 567-568. PMID: 34794879, PMCID: PMC8903084, DOI: 10.1016/j.acra.2021.10.007.Peer-Reviewed Original ResearchLipiodol Deposition and Washout in Primary and Metastatic Liver Tumors After Chemoembolization
Nezami N, VAN Breugel JMM, Konstantinidis M, Chapiro J, Savic LJ, Miszczuk MA, Rexha I, Lin M, Hong K, Georgiades C. Lipiodol Deposition and Washout in Primary and Metastatic Liver Tumors After Chemoembolization. In Vivo 2021, 35: 3261-3270. PMID: 34697157, PMCID: PMC8627740, DOI: 10.21873/invivo.12621.Peer-Reviewed Original ResearchConceptsConventional trans-arterial chemoembolizationTrans-arterial chemoembolizationNeuroendocrine tumorsColorectal carcinomaIntrahepatic cholangiocarcinomaLipiodol depositionWashout rateContrast-enhanced magnetic resonanceMetastatic liver tumorsColorectal carcinoma tumorsLiver metastasesHepatic metastasesTumor responseTarget lesionsRetrospective analysisLiver tumorsSmall tumorsChemoembolizationCarcinoma tumorsTumorsExponential washoutCarcinomaTomography imagingWashoutCholangiocarcinomaIdentifying 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 ResearchConceptsColorectal 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 1.7Lipiodol 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 carcinomaRole 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 imagesThermal 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 groupDeep 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 ResearchConceptsNon-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