2022
PET Myocardial Blood Flow for Post-transplant Surveillance and Cardiac Allograft Vasculopathy in Heart Transplant Recipients
Feher A, Miller EJ. PET Myocardial Blood Flow for Post-transplant Surveillance and Cardiac Allograft Vasculopathy in Heart Transplant Recipients. Current Cardiology Reports 2022, 24: 1865-1871. PMID: 36279035, DOI: 10.1007/s11886-022-01804-3.Peer-Reviewed Original ResearchMeSH KeywordsAllograftsCoronary AngiographyCoronary Artery DiseaseHeart TransplantationHumansMyocardial Perfusion ImagingPositron-Emission TomographyConceptsHeart transplant recipientsAllograft vasculopathyTransplant recipientsPositron emission tomography myocardial perfusionOverall graft survivalPost-transplant surveillanceCardiac allograft vasculopathyHeart transplant patientsTomography myocardial perfusionRecent FindingsMultiple studiesMyocardial perfusion imagingMyocardial blood flowMBF quantificationGraft survivalHeart transplantationTransplant patientsTransplant rejectionSerial monitoringPrognostic performancePET myocardial blood flowBlood flowMyocardial perfusionPerfusion imagingMBF assessmentBlood flow quantificationDeep Learning Coronary Artery Calcium Scores from SPECT/CT Attenuation Maps Improve Prediction of Major Adverse Cardiac Events
Miller R, Pieszko K, Shanbhag A, Feher A, Lemley M, Killekar A, Kavanagh PB, Van Kriekinge SD, Liang JX, Huang C, Miller EJ, Bateman T, Berman DS, Dey D, Slomka PJ. Deep Learning Coronary Artery Calcium Scores from SPECT/CT Attenuation Maps Improve Prediction of Major Adverse Cardiac Events. Journal Of Nuclear Medicine 2022, 64: 652-658. PMID: 36207138, PMCID: PMC10071789, DOI: 10.2967/jnumed.122.264423.Peer-Reviewed Original ResearchMitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images
Miller RJH, Singh A, Otaki Y, Tamarappoo BK, Kavanagh P, Parekh T, Hu LH, Gransar H, Sharir T, Einstein AJ, Fish MB, Ruddy TD, Kaufmann PA, Sinusas AJ, Miller EJ, Bateman TM, Dorbala S, Di Carli MF, Liang JX, Dey D, Berman DS, Slomka PJ. Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images. European Journal Of Nuclear Medicine And Molecular Imaging 2022, 50: 387-397. PMID: 36194270, PMCID: PMC10042590, DOI: 10.1007/s00259-022-05972-w.Peer-Reviewed Original ResearchConceptsCoronary artery diseaseMyocardial perfusion imagingArtery diseaseInvasive angiographyObstructive coronary artery diseaseDisease probabilityLow-risk patientsLow-risk populationHigh-risk populationTotal perfusion deficitHigh diagnostic accuracyS-TPDPerfusion deficitsPatient managementPatientsPerfusion imagingDiagnostic accuracyPerfusion SPECT imagesLower likelihoodGood calibrationCharacteristic curveAngiographySPECT imagesSelection biasDiseaseThe Prognostic Value of CAC Zero Among Individuals Presenting With Chest Pain A Meta-Analysis
Agha AM, Pacor J, Grandhi GR, Mszar R, Khan SU, Parikh R, Agrawal T, Burt J, Blankstein R, Blaha MJ, Shaw LJ, Al-Mallah MH, Brackett A, Cainzos-Achirica M, Miller EJ, Nasir K. The Prognostic Value of CAC Zero Among Individuals Presenting With Chest Pain A Meta-Analysis. JACC Cardiovascular Imaging 2022, 15: 1745-1757. PMID: 36202453, DOI: 10.1016/j.jcmg.2022.03.031.Peer-Reviewed Original ResearchMeSH KeywordsCalciumChest PainCoronary AngiographyCoronary Artery DiseaseHumansPredictive Value of TestsPrognosisRisk AssessmentRisk FactorsConceptsObstructive coronary artery diseaseAcute chest painCoronary artery calciumCoronary artery diseaseStable chest painNonobstructive coronary artery diseaseMajor adverse cardiac eventsAdverse cardiac eventsChest painCardiac eventsLow prevalenceAbsence of CACHealth care delivery modelsCare delivery modelsA Meta-AnalysisNegative predictive valueCAC assessmentArtery calciumCAC scoreIntermediate riskArtery diseaseCoronary CTACTA assessmentPrognostic valueTomography angiographyExplainable Deep Learning Improves Physician Interpretation of Myocardial Perfusion Imaging.
Miller RJH, Kuronuma K, Singh A, Otaki Y, Hayes S, Chareonthaitawee P, Kavanagh P, Parekh T, Tamarappoo BK, Sharir T, Einstein AJ, Fish MB, Ruddy TD, Kaufmann PA, Sinusas AJ, Miller EJ, Bateman TM, Dorbala S, Carli MD, Cadet S, Liang JX, Dey D, Berman DS, Slomka PJ. Explainable Deep Learning Improves Physician Interpretation of Myocardial Perfusion Imaging. Journal Of Nuclear Medicine 2022, 63: 1768-1774. PMID: 35512997, PMCID: PMC9635672, DOI: 10.2967/jnumed.121.263686.Peer-Reviewed Original ResearchConceptsMyocardial perfusion imagingCoronary artery diseaseObstructive coronary artery diseasePhysician interpretationDiagnostic accuracyPerfusion imagingLeft main arteryOverall net reclassification improvementInvasive coronary angiographyNet reclassification improvementTotal perfusion deficitArtery diseaseCoronary angiographyMedian agePhysician diagnosisReclassification improvementPerfusion deficitsClinical historyCoronary segmentsRepresentative cohortMeaningful improvementsMain arteryPatientsDL resultsQuantitative perfusion
2021
Clinical Deployment of Explainable Artificial Intelligence of SPECT for Diagnosis of Coronary Artery Disease
Otaki Y, Singh A, Kavanagh P, Miller RJH, Parekh T, Tamarappoo BK, Sharir T, Einstein AJ, Fish MB, Ruddy TD, Kaufmann PA, Sinusas AJ, Miller EJ, Bateman TM, Dorbala S, Di Carli M, Cadet S, Liang JX, Dey D, Berman DS, Slomka PJ. Clinical Deployment of Explainable Artificial Intelligence of SPECT for Diagnosis of Coronary Artery Disease. JACC Cardiovascular Imaging 2021, 15: 1091-1102. PMID: 34274267, PMCID: PMC9020794, DOI: 10.1016/j.jcmg.2021.04.030.Peer-Reviewed Original ResearchConceptsTotal perfusion deficitMyocardial perfusion imagingStandard clinical softwareStress total perfusion deficitObstructive CADTomography myocardial perfusion imagingSPECT myocardial perfusion imagingStress myocardial perfusionCoronary artery diseaseReceiver-operating characteristic curveInvasive coronary angiographyClinical softwareReader diagnosisSingle photon emissionTypical clinical workflowArtery diseaseCoronary angiographyPerfusion deficitsDiagnostic findingsMyocardial perfusionPerfusion imagingVentricular volumeStandard clinical workstationPatientsDiagnostic accuracyDiagnostic 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 curveA phenomapping-derived tool to personalize the selection of anatomical vs. functional testing in evaluating chest pain (ASSIST)
Oikonomou EK, Van Dijk D, Parise H, Suchard MA, de Lemos J, Antoniades C, Velazquez EJ, Miller EJ, Khera R. A phenomapping-derived tool to personalize the selection of anatomical vs. functional testing in evaluating chest pain (ASSIST). European Heart Journal 2021, 42: 2536-2548. PMID: 33881513, PMCID: PMC8488385, DOI: 10.1093/eurheartj/ehab223.Peer-Reviewed Original ResearchMeSH KeywordsChest PainComputed Tomography AngiographyCoronary AngiographyCoronary Artery DiseaseHumansProspective StudiesConceptsStable chest painChest painPrimary endpointMajor adverse cardiovascular eventsNon-fatal myocardial infarctionAdverse cardiovascular eventsStudy's primary endpointCoronary artery diseaseClinical trial populationsCox regression modelParticipant-level dataSCOT-HEARTCardiovascular eventsCause mortalityHazard ratioPatients 5Artery diseaseFunctional testingPROMISE trialTrial populationMyocardial infarctionLower incidenceStudy populationPainCollected variables
2019
New approach for quantification of left ventricular function from low-dose gated bloodpool SPECT: Validation and comparison with conventional methods in patients
Liu YH, Fazzone-Chettiar R, Sandoval V, Tsatkin V, Miller EJ, Sinusas AJ. New approach for quantification of left ventricular function from low-dose gated bloodpool SPECT: Validation and comparison with conventional methods in patients. Journal Of Nuclear Cardiology 2019, 28: 939-950. PMID: 31338796, DOI: 10.1007/s12350-019-01823-8.Peer-Reviewed Original ResearchConceptsLV functionEquilibrium radionuclide angiocardiographyInter-observer reproducibilityRed blood cellsVentricular functionLeft ventricular functionExcellent inter-observer reproducibilityHigh-dose injectionLow-dose injectionsUnderwent standardRadionuclide angiocardiographyRadioactive doseShort-axis slicesRegional functionBlood cellsRadiation exposureGold standardImaging modalitiesAxis slicesPatientsDedicated cardiac SPECT cameraDoseSPECTInjectionDifferent quantification methodsMachine learning predicts per-vessel early coronary revascularization after fast myocardial perfusion SPECT: results from multicentre REFINE SPECT registry.
Hu LH, Betancur J, Sharir T, Einstein AJ, Bokhari S, Fish MB, Ruddy TD, Kaufmann PA, Sinusas AJ, Miller EJ, Bateman TM, Dorbala S, Di Carli M, Germano G, Commandeur F, Liang JX, Otaki Y, Tamarappoo BK, Dey D, Berman DS, Slomka PJ. Machine learning predicts per-vessel early coronary revascularization after fast myocardial perfusion SPECT: results from multicentre REFINE SPECT registry. European Heart Journal - Cardiovascular Imaging 2019, 21: 549-559. PMID: 31317178, PMCID: PMC7167744, DOI: 10.1093/ehjci/jez177.Peer-Reviewed Original ResearchConceptsEarly coronary revascularizationMyocardial perfusion imagingStress TPDCoronary revascularizationTomography myocardial perfusion imagingTetrofosmin myocardial perfusion imagingSPECT myocardial perfusion imagingInvasive coronary angiographyReceiver operator characteristic curveREFINE SPECT registryPatient-specific explanationsOperator characteristic curveSingle photon emissionMyocardial perfusion SPECTCoronary angiographyIndividual patientsImaging variablesPatientsPerfusion SPECTPerfusion imagingClinical settingCharacteristic curveRevascularizationExpert interpretationStress test
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