2024
Impact of cardiac size on diagnostic performance of single-photon emission computed tomography myocardial perfusion imaging: insights from the REgistry of Fast Myocardial Perfusion Imaging with NExt generation single-photon emission computed tomography
Randazzo M, Elias P, Poterucha T, Sharir T, Fish M, Ruddy T, Kaufmann P, Sinusas A, Miller E, Bateman T, Dorbala S, Di Carli M, Castillo M, Liang J, Miller R, Dey D, Berman D, Slomka P, Einstein A. Impact of cardiac size on diagnostic performance of single-photon emission computed tomography myocardial perfusion imaging: insights from the REgistry of Fast Myocardial Perfusion Imaging with NExt generation single-photon emission computed tomography. European Heart Journal - Cardiovascular Imaging 2024, 25: 996-1006. PMID: 38445511, PMCID: PMC11210974, DOI: 10.1093/ehjci/jeae055.Peer-Reviewed Original ResearchSPECT myocardial perfusion imagingMyocardial perfusion imagingCoronary artery diseaseCardiac sizeDetect obstructive coronary artery diseasePerfusion imagingObstructive coronary artery diseaseDetection of coronary artery diseaseNegative predictive valueLeft ventricular volumeSolid-state scannersSmall cardiac sizeCoronary angiographyMale patientsYounger patientsElderly patientsMale sexDiagnostic performanceVentricular volumeArtery diseaseVisual assessmentPatientsPredictive valueElderly ageSPECT
2022
Explainable 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 curve
2019
Machine 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
Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT A Multicenter Study
Betancur J, Commandeur F, Motlagh M, Sharir T, Einstein AJ, Bokhari S, Fish MB, Ruddy TD, Kaufmann P, Sinusas AJ, Miller EJ, Bateman TM, Dorbala S, Di Carli M, Germano G, Otaki Y, Tamarappoo BK, Dey D, Berman DS, Slomka PJ. Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT A Multicenter Study. JACC Cardiovascular Imaging 2018, 11: 1654-1663. PMID: 29550305, PMCID: PMC6135711, DOI: 10.1016/j.jcmg.2018.01.020.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overCoronary CirculationCoronary StenosisDeep LearningFemaleHumansImage Interpretation, Computer-AssistedMaleMiddle AgedMyocardial Perfusion ImagingOrganophosphorus CompoundsOrganotechnetium CompoundsPredictive Value of TestsRadiopharmaceuticalsRegistriesTechnetium Tc 99m SestamibiTomography, Emission-Computed, Single-PhotonConceptsTotal perfusion deficitMyocardial perfusion imagingCoronary artery diseaseObstructive diseaseArtery diseaseVessel coronary artery diseaseTomography myocardial perfusion imagingTetrofosmin myocardial perfusion imagingLarge multicenter populationStress total perfusion deficitReceiver-operating characteristic curveInvasive coronary angiographyLeft ventricular myocardiumSingle photon emissionMyocardial perfusion SPECTMonths of MPIMulticenter populationObstructive stenosisCoronary angiographyMulticenter studyCoronary arteryPerfusion deficitsNormal limitsVessel sensitivityCurrent clinical methods
2016
Visual identification of coronary calcifications on attenuation correction CT improves diagnostic accuracy of SPECT/CT myocardial perfusion imaging
Patchett ND, Pawar S, Miller EJ. Visual identification of coronary calcifications on attenuation correction CT improves diagnostic accuracy of SPECT/CT myocardial perfusion imaging. Journal Of Nuclear Cardiology 2016, 24: 711-720. PMID: 26850031, DOI: 10.1007/s12350-016-0395-5.Peer-Reviewed Original ResearchMeSH KeywordsArtifactsComputed Tomography AngiographyCoronary Artery DiseaseFemaleHumansImage EnhancementMaleMiddle AgedMyocardial Perfusion ImagingObserver VariationReproducibility of ResultsSensitivity and SpecificitySingle Photon Emission Computed Tomography Computed TomographyUser-Computer InterfaceVascular CalcificationConceptsCoronary artery calciumMyocardial perfusion imagingCT myocardial perfusion imagingSPECT/CT myocardial perfusion imagingInvasive coronary angiographyAttenuation correction CTCause mortalityLate revascularizationAbsence of CACAccuracy of MPIRetrospective chart reviewFalse-positive studiesCT myocardial perfusionArtery calciumChart reviewHazard ratioConsecutive patientsCoronary angiographyCoronary calcificationRisk stratificationRisk markersMore MIsCT scanMyocardial perfusionPatients