2023
Clinical implications of Peri-hematomal edema microperfusion fraction in intracerebral hemorrhage intravoxel incoherent motion imaging – A pilot study
Abou Karam G, Tharmaseelan H, Aboian M, Malhotra A, Gilmore E, Falcone G, de Havenon A, Sheth K, Payabvash S. Clinical implications of Peri-hematomal edema microperfusion fraction in intracerebral hemorrhage intravoxel incoherent motion imaging – A pilot study. Journal Of Stroke And Cerebrovascular Diseases 2023, 32: 107375. PMID: 37738914, PMCID: PMC10591892, DOI: 10.1016/j.jstrokecerebrovasdis.2023.107375.Peer-Reviewed Original ResearchConceptsModified Rankin ScaleSecondary brain injuryIntracerebral hemorrhagePerihematomal edemaSubacute intracerebral hemorrhageIntravoxel incoherent motion imagingAdmission NIHSSBrain injuryMedian baseline National InstitutesPilot studyBaseline National InstitutesHealth Stroke ScalePerfusion fractionSupratentorial intracerebral hemorrhageIVIM metricsIncoherent motion imagingStroke ScaleNeuroprotective therapiesParenchymal injuryRankin ScaleRisk patientsConsecutive patientsUnivariable analysisPoor outcomeICH volume
2021
The coronal plane maximum diameter of deep intracerebral hemorrhage predicts functional outcome more accurately than hematoma volume
Haider SP, Qureshi AI, Jain A, Tharmaseelan H, Berson ER, Majidi S, Filippi CG, Mak A, Werring DJ, Acosta JN, Malhotra A, Kim JA, Sansing LH, Falcone G, Sheth K, Payabvash S. The coronal plane maximum diameter of deep intracerebral hemorrhage predicts functional outcome more accurately than hematoma volume. International Journal Of Stroke 2021, 17: 777-784. PMID: 34569877, PMCID: PMC9005571, DOI: 10.1177/17474930211050749.Peer-Reviewed Original ResearchAdmission computed tomography radiomic signatures outperform hematoma volume in predicting baseline clinical severity and functional outcome in the ATACH‐2 trial intracerebral hemorrhage population
Haider SP, Qureshi AI, Jain A, Tharmaseelan H, Berson ER, Zeevi T, Majidi S, Filippi CG, Iseke S, Gross M, Acosta JN, Malhotra A, Kim JA, Sansing LH, Falcone GJ, Sheth KN, Payabvash S. Admission computed tomography radiomic signatures outperform hematoma volume in predicting baseline clinical severity and functional outcome in the ATACH‐2 trial intracerebral hemorrhage population. European Journal Of Neurology 2021, 28: 2989-3000. PMID: 34189814, PMCID: PMC8818333, DOI: 10.1111/ene.15000.Peer-Reviewed Original ResearchConceptsAdmission Glasgow Coma ScaleGlasgow Coma ScaleRadiomics signatureMRS scoreHematoma volumeICH volumeClinical severityNoncontrast head CT scansAdmission National InstitutesHealth Stroke ScaleRankin Scale scoreStrong associationBaseline clinical severityMedium-term outcomesIndependent validation cohortHead CT scanATACH-2 trialStroke ScaleAdmission NIHSSIndependent predictorsClinical presentationComa ScaleBaseline CTICH patientsValidation cohortImaging of Spontaneous Intracerebral Hemorrhage
Jain A, Malhotra A, Payabvash S. Imaging of Spontaneous Intracerebral Hemorrhage. Neuroimaging Clinics Of North America 2021, 31: 193-203. PMID: 33902874, PMCID: PMC8820948, DOI: 10.1016/j.nic.2021.02.003.Peer-Reviewed Original ResearchConceptsIntracerebral hemorrhageSpontaneous intracerebral hemorrhageStroke incidenceLatest evidence-based guidelinesNontraumatic spontaneous intracerebral hemorrhageHemorrhagic stroke incidenceOverall stroke incidenceIdentification of patientsEvidence-based guidelinesClinical outcome predictionMorbidity rateHematoma expansionTreatment strategiesFirst monthOutcome predictionHemorrhageMortalityIncidenceFirst yearPatientsStrokeNeuroimagingMonths
2018
A user-guided tool for semi-automated cerebral microbleed detection and volume segmentation: Evaluating vascular injury and data labelling for machine learning
Morrison MA, Payabvash S, Chen Y, Avadiappan S, Shah M, Zou X, Hess CP, Lupo JM. A user-guided tool for semi-automated cerebral microbleed detection and volume segmentation: Evaluating vascular injury and data labelling for machine learning. NeuroImage Clinical 2018, 20: 498-505. PMID: 30140608, PMCID: PMC6104340, DOI: 10.1016/j.nicl.2018.08.002.Peer-Reviewed Original ResearchConceptsData labelingTraining dataHigh-level feature extractionVolume segmentationComputer-aided detection algorithmComputer-aided detection methodsGround truth labelingCerebral microbleed detectionFalse positivesMachine learningFeature extractionSegmentation resultsDetection algorithmSophisticated machineTime usersAlgorithm performanceCMB detectionComputer aidMicrobleed detectionSegmentationTest setDetection methodSuperior performanceExtensive research effortsMachine
2014
Differentiating intraparenchymal hemorrhage from contrast extravasation on post-procedural noncontrast CT scan in acute ischemic stroke patients undergoing endovascular treatment
Payabvash S, Qureshi MH, Khan SM, Khan M, Majidi S, Pawar S, Qureshi AI. Differentiating intraparenchymal hemorrhage from contrast extravasation on post-procedural noncontrast CT scan in acute ischemic stroke patients undergoing endovascular treatment. Neuroradiology 2014, 56: 737-744. PMID: 24925217, DOI: 10.1007/s00234-014-1381-8.Peer-Reviewed Original ResearchConceptsPost-procedural CT scanAcute ischemic stroke patientsIschemic stroke patientsContrast extravasationIntraparenchymal hemorrhageEndovascular treatmentStroke patientsCT scanNoncontrast CT scanHyperdense lesionHounsfield unitsParenchymal lesionsImaging recordsIntroductionThis studyHemorrhagePatientsExtravasationLesionsScansHyperdensityHyperdenseTreatmentAverage attenuationCharacteristic analysisResultsOf