2023
Radiomic markers of intracerebral hemorrhage expansion on non-contrast CT: independent validation and comparison with visual markers
Haider S, Qureshi A, Jain A, Tharmaseelan H, Berson E, Zeevi T, Werring D, Gross M, Mak A, Malhotra A, Sansing L, Falcone G, Sheth K, Payabvash S. Radiomic markers of intracerebral hemorrhage expansion on non-contrast CT: independent validation and comparison with visual markers. Frontiers In Neuroscience 2023, 17: 1225342. PMID: 37655013, PMCID: PMC10467422, DOI: 10.3389/fnins.2023.1225342.Peer-Reviewed Original ResearchIndependent validation cohortIntracerebral hemorrhageRadiomic featuresValidation cohortClinical variablesHematoma expansionSpontaneous supratentorial intracerebral hemorrhageNon-contrast head CTSupratentorial intracerebral hemorrhageTomography (CT) of patientsNon-contrast headFuture clinical trialsNon-contrast CTIntracerebral Hemorrhage ExpansionHigh predictive valueBAT scoreHypertensive patientsClinical predictorsPrognostic relevanceFunctional outcomeClinical trialsHead CTHemorrhage expansionClinical trial datasetDiscovery cohort
2012
Location-weighted CTP analysis predicts early motor improvement in stroke
Payabvash S, Souza LC, Kamalian S, Wang Y, Passanese J, Kamalian S, Fung SH, Halpern EF, Schaefer PW, Gonzalez RG, Furie KL, Lev MH. Location-weighted CTP analysis predicts early motor improvement in stroke. Neurology 2012, 78: 1853-1859. PMID: 22573641, PMCID: PMC3369521, DOI: 10.1212/wnl.0b013e318258f799.Peer-Reviewed Original ResearchConceptsAcute stroke patientsAdmission NIHSSMotor improvementStroke patientsCT perfusionPredictive valueOnly independent clinical predictorMultivariate binary logistic regressionFrontal lobe white matterMultivariate modelIndependent clinical predictorsMotor functional improvementMotor function improvementNegative predictive valuePositive predictive valueSuperior temporal gyrusBinary logistic regressionExtremity paresisAcute strokeSymptom onsetClinical predictorsConsecutive patientsIndependent predictorsClinical outcomesImaging predictors
2010
Predicting Language Improvement in Acute Stroke Patients Presenting with Aphasia: A Multivariate Logistic Model Using Location-Weighted Atlas-Based Analysis of Admission CT Perfusion Scans
Payabvash S, Kamalian S, Fung S, Wang Y, Passanese J, Kamalian S, Souza LC, Kemmling A, Harris GJ, Halpern EF, González RG, Furie KL, Lev MH. Predicting Language Improvement in Acute Stroke Patients Presenting with Aphasia: A Multivariate Logistic Model Using Location-Weighted Atlas-Based Analysis of Admission CT Perfusion Scans. American Journal Of Neuroradiology 2010, 31: 1661-1668. PMID: 20488905, PMCID: PMC3640318, DOI: 10.3174/ajnr.a2125.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAphasiaBrainComputer SimulationFemaleHumansLogistic ModelsMaleModels, NeurologicalMultivariate AnalysisPattern Recognition, AutomatedPerfusion ImagingPrognosisRadiographic Image Interpretation, Computer-AssistedReproducibility of ResultsSensitivity and SpecificityStrokeSubtraction TechniqueTomography, X-Ray ComputedConceptsBrain CTPNIHSS scoreStroke onsetFunctional outcomeFirst-time ischemic strokeProximal cerebral artery occlusionMultiple logistic regression analysisMultivariate logistic regression modelMultivariate modelDischarge NIHSS scoreTotal NIHSS scoreAcute stroke patientsCerebral artery occlusionTime of dischargeCT perfusion imagingLogistic regression analysisMultivariate logistic modelCT perfusion scansLogistic regression modelsAdmission CTAArtery occlusionInfarct volumeIschemic strokeClinical predictorsConsecutive patients