2023
Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging
Pieszko K, Shanbhag A, Singh A, Hauser M, Miller R, Liang J, Motwani M, Kwieciński J, Sharir T, Einstein A, Fish M, Ruddy T, Kaufmann P, Sinusas A, Miller E, Bateman T, Dorbala S, Di Carli M, Berman D, Dey D, Slomka P. Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging. Npj Digital Medicine 2023, 6: 78. PMID: 37127660, PMCID: PMC10151323, DOI: 10.1038/s41746-023-00806-x.Peer-Reviewed Original ResearchAcute coronary syndromeMajor adverse cardiovascular eventsMyocardial perfusion imagingCause deathAdverse cardiovascular eventsModifiable risk factorsPrediction of deathPersonalized risk assessmentCardiovascular eventsCoronary syndromeClinical featuresPrognostic valueRisk factorsExternal cohortStandard clinical interpretationPerfusion imagingAbnormality measuresCardiac perfusionTime pointsPatients' explanationsClinical interpretationExternal validationDeathPatientsRisk assessment
2022
Integration of coronary artery calcium scoring from CT attenuation scans by machine learning improves prediction of adverse cardiovascular events in patients undergoing SPECT/CT myocardial perfusion imaging
Feher A, Pieszko K, Miller R, Lemley M, Shanbhag A, Huang C, Miras L, Liu YH, Sinusas AJ, Miller EJ, Slomka PJ. Integration of coronary artery calcium scoring from CT attenuation scans by machine learning improves prediction of adverse cardiovascular events in patients undergoing SPECT/CT myocardial perfusion imaging. Journal Of Nuclear Cardiology 2022, 30: 590-603. PMID: 36195826, DOI: 10.1007/s12350-022-03099-x.Peer-Reviewed Original ResearchConceptsMajor adverse cardiovascular eventsMyocardial perfusion imagingAdverse cardiovascular eventsSPECT myocardial perfusion imagingCAC scoringCardiovascular eventsPrediction of MACECoronary artery calcification (CAC) scoringMACE-free survivalClinical risk factorsCoronary artery calciumCT myocardial perfusion imagingReceiver operator characteristic curveSPECT/CT myocardial perfusion imagingSPECT/CTOperator characteristic curveCT myocardial perfusionArtery calciumCAC scoreAnalysis patientsMACE predictionSingle centerHigher event ratesRisk factorsRisk scorePrevalence and predictors of automatically quantified myocardial ischemia within a multicenter international registry
Han D, Rozanski A, 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, Dey D, Berman DS, Slomka PJ. Prevalence and predictors of automatically quantified myocardial ischemia within a multicenter international registry. Journal Of Nuclear Cardiology 2022, 29: 3221-3232. PMID: 35174442, PMCID: PMC9378748, DOI: 10.1007/s12350-021-02829-x.Peer-Reviewed Original ResearchConceptsTotal perfusion deficitMyocardial ischemiaStress testingCAD risk factorsMulticenter international registryPredictor of ischemiaCardiac stress testingNuclear stress testingChi-square testConclusionThe prevalenceMulticenter registryOverall cohortTypical anginaCAD statusPerfusion deficitsInternational registryMale genderRisk factorsLVEFIschemiaPatientsImaging characteristicsPotent predictorPrevalenceRegistry
2020
Survival Following Implantable Cardioverter‐Defibrillator Implantation in Patients With Amyloid Cardiomyopathy
Higgins AY, Annapureddy AR, Wang Y, Minges KE, Lampert R, Rosenfeld LE, Jacoby DL, Curtis JP, Miller EJ, Freeman JV. Survival Following Implantable Cardioverter‐Defibrillator Implantation in Patients With Amyloid Cardiomyopathy. Journal Of The American Heart Association 2020, 9: e016038. PMID: 32867553, PMCID: PMC7726970, DOI: 10.1161/jaha.120.016038.Peer-Reviewed Original ResearchConceptsImplantable cardioverter defibrillator implantationCardioverter-defibrillator implantationNonischemic cardiomyopathyCardiac amyloidosisDiabetes mellitusCerebrovascular diseaseVentricular tachycardiaMultivariable Cox proportional hazards regression modelsCox proportional hazards regression modelProportional hazards regression modelsKaplan-Meier survival curvesCox proportional hazards modelPropensity-matched cohortOutcomes of patientsHazards regression modelsProportional hazards modelCause mortalityICD implantationRenal functionMultivariable analysisConclusions MortalityRisk factorsRegistry dataAmyloid cardiomyopathyHigh risk
2019
Myocardial Ischemic Burden and Differences in Prognosis Among Patients With and Without Diabetes: Results From the Multicenter International REFINE SPECT Registry
Han D, Rozanski A, Gransar H, 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, Germano G, Dey D, Berman DS, Slomka PJ. Myocardial Ischemic Burden and Differences in Prognosis Among Patients With and Without Diabetes: Results From the Multicenter International REFINE SPECT Registry. Diabetes Care 2019, 43: 453-459. PMID: 31776140, PMCID: PMC6971784, DOI: 10.2337/dc19-1360.Peer-Reviewed Original ResearchMeSH KeywordsAgedAngina, UnstableCohort StudiesCoronary Artery DiseaseDiabetes MellitusDiabetic AngiopathiesFemaleHumansMaleMiddle AgedMyocardial InfarctionMyocardial IschemiaMyocardial Perfusion ImagingPrevalencePrognosisPropensity ScoreRegistriesRisk FactorsTomography, Emission-Computed, Single-PhotonConceptsMajor adverse cardiovascular eventsTotal perfusion deficitMACE riskMyocardial ischemic burdenAdverse cardiovascular eventsTomography myocardial perfusionREFINE SPECT registrySingle photon emissionIschemic burdenMinimal ischemiaCardiovascular eventsCause mortalityLate revascularizationPrognostic impactUnstable anginaSignificant ischemiaPerfusion deficitsMyocardial infarctionMyocardial ischemiaRisk factorsCardiovascular diseaseHigh riskMyocardial perfusionPatientsDiabetes