2021
Comparison of diabetes to other prognostic predictors among patients referred for cardiac stress testing: A contemporary analysis from the REFINE SPECT Registry
Han D, Rozanski A, Gransar H, Tzolos E, Miller RJH, Sharir T, Einstein AJ, Fish MB, Ruddy TD, Kaufmann PA, Sinusas AJ, Miller EJ, Bateman TM, Dorbala S, Di Carli M, Liang JX, Hu LH, Dey D, Berman DS, Slomka PJ. Comparison of diabetes to other prognostic predictors among patients referred for cardiac stress testing: A contemporary analysis from the REFINE SPECT Registry. Journal Of Nuclear Cardiology 2021, 29: 3003-3014. PMID: 34757571, PMCID: PMC9085969, DOI: 10.1007/s12350-021-02810-8.Peer-Reviewed Original ResearchConceptsMajor adverse cardiovascular eventsCoronary artery diseaseTotal perfusion deficitCardiac stress testingStress testingComparison of diabetesAdverse cardiovascular eventsStress test patientsCardiac stress test patientsREFINE SPECT registryDM statusMACE riskBackgroundDiabetes mellitusCardiovascular eventsArtery diseaseVentricular functionPrognostic predictorClinical variablesPerfusion deficitsChi-square analysisSPECT-MPIPatientsTest patientsPropensity scorePotent predictorDetermining a minimum set of variables for machine learning cardiovascular event prediction: results from REFINE SPECT registry
Rios R, Miller RJH, Hu LH, Otaki Y, Singh A, Diniz M, Sharir T, Einstein AJ, Fish MB, Ruddy TD, Kaufmann PA, Sinusas AJ, Miller EJ, Bateman TM, Dorbala S, DiCarli M, Van Kriekinge S, Kavanagh P, Parekh T, Liang JX, Dey D, Berman DS, Slomka P. Determining a minimum set of variables for machine learning cardiovascular event prediction: results from REFINE SPECT registry. Cardiovascular Research 2021, 118: 2152-2164. PMID: 34259870, PMCID: PMC9302886, DOI: 10.1093/cvr/cvab236.Peer-Reviewed Original ResearchConceptsMajor adverse cardiac eventsMyocardial perfusion imagingTotal perfusion deficitPrognostic accuracyREFINE SPECT registryImaging variablesTraditional multivariable modelsMultivariable modelStress total perfusion deficitAdverse cardiac eventsReceiver-operating characteristic curveOptimal risk stratificationTomography (SPECT) MPIComparable prognostic accuracyComparable prognostic performanceHigher prognostic accuracySingle photon emissionCardiovascular event predictionCardiac eventsRisk stratificationClinical variablesPerfusion deficitsPrognostic performancePerfusion imagingCollected variablesDiagnostic safety of a machine learning-based automatic patient selection algorithm for stress-only myocardial perfusion SPECT
Eisenberg E, Miller RJH, Hu LH, Rios R, Betancur J, Azadani P, Han D, Sharir T, Einstein AJ, Bokhari S, Fish MB, Ruddy TD, Kaufmann PA, Sinusas AJ, Miller EJ, Bateman TM, Dorbala S, Di Carli M, Liang JX, Otaki Y, Tamarappoo BK, Dey D, Berman DS, Slomka PJ. Diagnostic safety of a machine learning-based automatic patient selection algorithm for stress-only myocardial perfusion SPECT. Journal Of Nuclear Cardiology 2021, 29: 2295-2307. PMID: 34228341, PMCID: PMC9020793, DOI: 10.1007/s12350-021-02698-4.Peer-Reviewed Original ResearchConceptsObstructive coronary artery diseaseCoronary artery diseaseHigh-risk coronary artery diseaseMyocardial perfusion imagingPatient selection algorithmTriple-vessel coronary artery diseasePrediction of CADML thresholdsStress-first protocolInvasive coronary angiographyReceiver operator characteristic curveOperator characteristic curveMyocardial perfusion SPECTArtery diseaseCoronary angiographyAnterior descendingClinical variablesClinical algorithmReader diagnosisRest imagingPerfusion SPECTPerfusion imagingDiagnostic safetyRadiation doseCharacteristic curve
2018
Rationale and design of the REgistry of Fast Myocardial Perfusion Imaging with NExt generation SPECT (REFINE SPECT)
Slomka PJ, Betancur J, Liang JX, Otaki Y, Hu LH, Sharir T, Dorbala S, Di Carli M, Fish MB, Ruddy TD, Bateman TM, Einstein AJ, Kaufmann PA, Miller EJ, Sinusas AJ, Azadani PN, Gransar H, Tamarappoo BK, Dey D, Berman DS, Germano G. Rationale and design of the REgistry of Fast Myocardial Perfusion Imaging with NExt generation SPECT (REFINE SPECT). Journal Of Nuclear Cardiology 2018, 27: 1010-1021. PMID: 29923104, PMCID: PMC6301135, DOI: 10.1007/s12350-018-1326-4.Peer-Reviewed Original ResearchMeSH KeywordsAgedArtificial IntelligenceAutomationCoronary AngiographyCoronary Artery DiseaseData CollectionDatabases, FactualFemaleFollow-Up StudiesHumansImage Processing, Computer-AssistedMachine LearningMaleMiddle AgedMyocardial Perfusion ImagingPrognosisRegistriesReproducibility of ResultsSoftwareTomography, Emission-Computed, Single-PhotonConceptsMyocardial perfusion imagingPharmacologic stressMajor adverse cardiac eventsAdverse cardiac eventsRevascularization resultsMulticenter registryCardiac eventsClinical variablesPrognostic outcomesResultsTo dateClinical dataPrognostic dataDiagnostic cohortSPECT-MPIImaging variablesMyocardial perfusionPrognostic cohortPerfusion imagingPatientsRegistryArtificial intelligence toolsNew artificial intelligence toolsQuantitative softwareCohortClinical image database