2024
In vivo neuropil density from anatomical MRI and machine learning
Akif A, Staib L, Herman P, Rothman D, Yu Y, Hyder F. In vivo neuropil density from anatomical MRI and machine learning. Cerebral Cortex 2024, 34: bhae200. PMID: 38771239, PMCID: PMC11107380, DOI: 10.1093/cercor/bhae200.Peer-Reviewed Original ResearchConceptsMagnetic resonance imagingSynaptic densityNeuropil densityCellular densityArtificial neural networkNeural networkPositron emission tomographyAnatomical magnetic resonance imagingHealthy subjectsSynaptic activityMRI scansMachine learning algorithmsBrain's energy budgetEmission tomographyIn vivo MRI scansResonance imagingTissue cellularityLearning algorithmsDiffusion magnetic resonance imagingMachine learningMicroscopic interpretationInterpretation of functional neuroimaging dataIndividual predictionsSubjects
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 ResearchMeSH KeywordsCarcinoma, HepatocellularHumansLiver NeoplasmsMachine LearningMagnetic Resonance ImagingNeoplasm Recurrence, LocalRetrospective Studies
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 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 outcomeMachine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment
Petersen G, Shatalov J, Verma T, Brim WR, Subramanian H, Brackett A, Bahar RC, Merkaj S, Zeevi T, Staib LH, Cui J, Omuro A, Bronen RA, Malhotra A, Aboian MS. Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment. American Journal Of Neuroradiology 2022, 43: 526-533. PMID: 35361577, PMCID: PMC8993193, DOI: 10.3174/ajnr.a7473.Peer-Reviewed Original ResearchMeSH KeywordsGliomaHumansLymphomaMachine LearningMagnetic Resonance ImagingReproducibility of ResultsConceptsMachine learning-based methodsLearning-based methodsBalanced data setData setsVector machine modelMachine learningClassification algorithmsMachine modelMachineAlgorithmData basesPrediction modelPromising resultsPrimary CNS lymphomaPrediction model study RiskRisk of biasRadiomic featuresClassifierSetCNS lymphomaWebLearningFeaturesQualitySystematic review
2021
BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis
Li X, Zhou Y, Dvornek N, Zhang M, Gao S, Zhuang J, Scheinost D, Staib LH, Ventola P, Duncan JS. BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis. Medical Image Analysis 2021, 74: 102233. PMID: 34655865, PMCID: PMC9916535, DOI: 10.1016/j.media.2021.102233.Peer-Reviewed Original ResearchMeSH KeywordsAutism Spectrum DisorderBrainConnectomeHumansMagnetic Resonance ImagingNeural Networks, ComputerConceptsFunctional magnetic resonance imagesGraph neural network frameworkMedical image analysisGraph neural networkGraph convolutional layersNeural network frameworkDifferent evaluation metricsSpecific task statesIndependent fMRI datasetsPooling layerConvolutional layersConsistency lossNetwork frameworkNeural networkFMRI datasetsImage analysis methodEvaluation metricsDetection resultsBrain graphsSubjects releaseROI selectionImage analysisCognitive stimuliTask statesFMRI analysis
2020
Multi-site fMRI analysis using privacy-preserving federated learning and domain adaptation: ABIDE results
Li X, Gu Y, Dvornek N, Staib LH, Ventola P, Duncan JS. Multi-site fMRI analysis using privacy-preserving federated learning and domain adaptation: ABIDE results. Medical Image Analysis 2020, 65: 101765. PMID: 32679533, PMCID: PMC7569477, DOI: 10.1016/j.media.2020.101765.Peer-Reviewed Original ResearchConceptsDeep learning modelsFederated LearningPrivacy-preserving federated learningLearning modelFederated learning approachPrivacy-preserving strategyDomain adaptation methodsData analysis problemsLocal model weightsIterative optimization algorithmEntity dataDomain adaptationLearning approachLearning formulationMulti-site dataRandomization mechanismAdaptation methodNeuroimage analysisDifferent tasksModel weightsModel optimizationOptimization algorithmPrivate informationTraining strategyAnalysis problemAutomated 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 MRIThresholdingImpact of Radiologist-Driven Change-Order Requests on Outpatient CT and MRI Examinations
Pourjabbar S, Cavallo JJ, Arango J, Tocino I, Staib LH, Imanzadeh A, Forman HP, Pahade JK. Impact of Radiologist-Driven Change-Order Requests on Outpatient CT and MRI Examinations. Journal Of The American College Of Radiology 2020, 17: 1014-1024. PMID: 31954708, DOI: 10.1016/j.jacr.2019.12.017.Peer-Reviewed Original ResearchMeSH KeywordsHumansMagnetic Resonance ImagingOutpatientsPhysical ExaminationRadiologistsTomography, X-Ray Computed
2018
Does MR enterography offer added value after a recent CT in the evaluation of abdominal pain in Crohn's disease patients?
Spektor M, Mathur M, Santacana G, Asch D, Huber S, Staib L, Israel G. Does MR enterography offer added value after a recent CT in the evaluation of abdominal pain in Crohn's disease patients? Clinical Imaging 2018, 54: 78-83. PMID: 30562678, DOI: 10.1016/j.clinimag.2018.12.002.Peer-Reviewed Original ResearchConceptsAbdominal painCrohn's diseaseDisease patientsHigher health care costsAcute abdominal painBowel wall thickeningCrohn's disease patientsContrast-enhanced CTStrict inclusion criteriaHealth care costsModerate interobserver agreementRecent CTBowel obstructionConsecutive patientsMR enterographyPatient riskInclusion criteriaBlinded reviewAbdominal radiologistsMRE examinationsCare costsWall thickeningFree fluidRoutine useDiagnostic CT
2017
Disparities in Care Among Patients With Cardiac Implantable Electronic Devices Undergoing MRI
Cavallo JJ, Zhang Y, Staib LH, Lampert R, Weinreb JC. Disparities in Care Among Patients With Cardiac Implantable Electronic Devices Undergoing MRI. Journal Of The American College Of Radiology 2017, 14: 1566-1571. PMID: 28899705, DOI: 10.1016/j.jacr.2017.07.014.Peer-Reviewed Original ResearchLearning Non-rigid Deformations for Robust, Constrained Point-based Registration in Image-Guided MR-TRUS Prostate Intervention
Onofrey JA, Staib LH, Sarkar S, Venkataraman R, Nawaf CB, Sprenkle PC, Papademetris X. Learning Non-rigid Deformations for Robust, Constrained Point-based Registration in Image-Guided MR-TRUS Prostate Intervention. Medical Image Analysis 2017, 39: 29-43. PMID: 28431275, PMCID: PMC5514316, DOI: 10.1016/j.media.2017.04.001.Peer-Reviewed Original Research
2016
Brain responses to biological motion predict treatment outcome in young children with autism
Yang D, Pelphrey KA, Sukhodolsky DG, Crowley MJ, Dayan E, Dvornek NC, Venkataraman A, Duncan J, Staib L, Ventola P. Brain responses to biological motion predict treatment outcome in young children with autism. Translational Psychiatry 2016, 6: e948-e948. PMID: 27845779, PMCID: PMC5314125, DOI: 10.1038/tp.2016.213.Peer-Reviewed Original ResearchConceptsAutism spectrum disorderYoung childrenSocial information processingMultivariate pattern analysisMotivation/rewardBiological motionCore deficitComplex neurodevelopmental disorderBrain responsesResponse treatmentSpectrum disorderNeurobiological markersNeural predictorsInformation processingBehavioral interventionsIndividual childrenNeurodevelopmental disordersCurrent findingsNeural circuitsBehavioral deficitsEarly childhoodChildrenUnsuccessful interventionsNeurobiomarkersPattern analysisPivotal response treatment prompts a functional rewiring of the brain among individuals with autism spectrum disorder
Venkataraman A, Yang D, Dvornek N, Staib LH, Duncan JS, Pelphrey KA, Ventola P. Pivotal response treatment prompts a functional rewiring of the brain among individuals with autism spectrum disorder. Neuroreport 2016, 27: 1081-1085. PMID: 27532879, PMCID: PMC5007196, DOI: 10.1097/wnr.0000000000000662.Peer-Reviewed Original ResearchMeSH KeywordsAutism Spectrum DisorderBayes TheoremBehavior TherapyBrainChildChild, PreschoolFemaleHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleNeural PathwaysOxygenConceptsPivotal Response TreatmentAutism spectrum disorderOccipital-temporal cortexAttentional systemResponse treatmentSpectrum disorderOrbitofrontal cortexPosterior cingulateHigh-level objectsBehavioral interventionsLearning mechanismPerception shiftProcessing areasNeural circuitsFunctional rewiringCortexTreatment regimenAutismInterventionNovel Bayesian frameworkCingulateFunctional changesIndividualsDisordersObjectsMagnetic Resonance Imaging and Sonography in the Diagnosis of Placental Invasion
Balcacer P, Pahade J, Spektor M, Staib L, Copel JA, McCarthy S. Magnetic Resonance Imaging and Sonography in the Diagnosis of Placental Invasion. Journal Of Ultrasound In Medicine 2016, 35: 1445-1456. PMID: 27229131, DOI: 10.7863/ultra.15.07040.Peer-Reviewed Original ResearchIs there an added value of a hepatobiliary phase with gadoxetate disodium following conventional MRI with an extracellular gadolinium agent in a single imaging session for detection of primary hepatic malignancies?
Pahade JK, Juice D, Staib L, Israel G, Cornfeld D, Mitchell K, Weinreb J. Is there an added value of a hepatobiliary phase with gadoxetate disodium following conventional MRI with an extracellular gadolinium agent in a single imaging session for detection of primary hepatic malignancies? Abdominal Radiology 2016, 41: 1270-1284. PMID: 26800701, DOI: 10.1007/s00261-016-0635-9.Peer-Reviewed Original Research
2015
Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patients
Onofrey JA, Staib LH, Papademetris X. Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patients. NeuroImage Clinical 2015, 10: 291-301. PMID: 26900569, PMCID: PMC4724039, DOI: 10.1016/j.nicl.2015.12.001.Peer-Reviewed Original ResearchSegmenting the Brain Surface from CT Images with Artifacts Using Dictionary Learning for Non-rigid MR-CT Registration
Onofrey JA, Staib LH, Papademetris X. Segmenting the Brain Surface from CT Images with Artifacts Using Dictionary Learning for Non-rigid MR-CT Registration. Lecture Notes In Computer Science 2015, 24: 662-674. PMID: 26221711, PMCID: PMC5266617, DOI: 10.1007/978-3-319-19992-4_52.Peer-Reviewed Original ResearchAnterior Cortical Development During Adolescence in Bipolar Disorder
Najt P, Wang F, Spencer L, Johnston JA, Lippard E, Pittman BP, Lacadie C, Staib LH, Papademetris X, Blumberg HP. Anterior Cortical Development During Adolescence in Bipolar Disorder. Biological Psychiatry 2015, 79: 303-310. PMID: 26033826, PMCID: PMC4595154, DOI: 10.1016/j.biopsych.2015.03.026.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentBipolar DisorderCase-Control StudiesEmotionsFemaleGray MatterHumansLongitudinal StudiesMagnetic Resonance ImagingMaleNeuroimagingPrefrontal CortexWhite MatterYoung AdultConceptsWhite matter expansionBipolar disorderWhite matterAnterior cortexHealthy adolescentsHigh-resolution magnetic resonance imaging (MRI) scansMagnetic resonance imaging (MRI) scansWhite matter increasesResonance imaging scansGray matter decreasesDorsolateral prefrontal cortexMatter expansionHealthy groupImaging scansCortical volumeFrontal cortexNeurodevelopmental abnormalitiesCortical developmentAnterior paralimbicNeurodevelopmental modelLongitudinal neuroimagingPrefrontal cortexCortexLongitudinal studyAdolescentsThe clinical impact of gynecologic MRI.
Ratner ES, Staib LH, Cross SN, Raji R, Schwartz PE, McCarthy SM. The clinical impact of gynecologic MRI. American Journal Of Roentgenology 2015, 204: 674-80. PMID: 25714302, DOI: 10.2214/ajr.14.12567.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedChildFemaleGenital Diseases, FemaleGenital Neoplasms, FemaleHumansMagnetic Resonance ImagingMiddle AgedTomography, X-Ray ComputedUltrasonographyYoung AdultConceptsPelvic MRIFirst modalityClinical managementClinical impactGynecologic massesIndeterminate pelvic massesGroup of patientsResults of MRIRadiologic recordsRadiologic findingsPelvic massClinical recordsUnnecessary surgeryMedical recordsCT examinationsFurther endpointsExact diagnosisPatientsSurgeryIndeterminate massesPatient treatmentMRIDiagnosisModalitiesResultant anxiety