The Updated Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT 2.0).
Miller R, Lemley M, Shanbhag A, Ramirez G, Liang J, Builoff V, Kavanagh P, Sharir T, Hauser M, Ruddy T, Fish M, Bateman T, Acampa W, Einstein A, Dorbala S, Di Carli M, Feher A, Miller E, Sinusas A, Halcox J, Martins M, Kaufmann P, Dey D, Berman D, Slomka P. The Updated Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT 2.0). Journal Of Nuclear Medicine 2024, 65: 1795-1801. PMID: 39362762, PMCID: PMC11533915, DOI: 10.2967/jnumed.124.268292.Peer-Reviewed Original ResearchCoronary artery calciumCT attenuation correction imagesStress total perfusion deficitMyocardial perfusion imagingTotal perfusion deficitAttenuation correction imagesPerfusion imagingREFINE SPECTImprove prediction of adverse outcomesPerfusion deficitsSPECT myocardial perfusion imagingIncreased risk of MACEPredictive of adverse outcomesMedian follow-upInvasive coronary angiographyRisk of MACEAdverse cardiovascular eventsCAC scoreExperience MACECoronary angiographyArtery calciumInternational registryCardiovascular eventsFollow-upClinical dataDeep learning-based epicardial adipose tissue measurement, maximizing prognostic information from attenuation correction imaging
Shanbhag A, Miller R, Killekar A, Lemley M, Bednarski B, Van Kriekinge S, Kavanagh P, Feher A, Miller E, Bateman T, Liang J, Builoff V, Berman D, Dey D, Slomka P. Deep learning-based epicardial adipose tissue measurement, maximizing prognostic information from attenuation correction imaging. Progress In Biomedical Optics And Imaging 2024, 12930: 129300b-129300b-6. DOI: 10.1117/12.3007914.Peer-Reviewed Original ResearchEpicardial adipose tissueUngated CTMyocardial infarctionEAT volumeRisk stratificationComputed tomographyEAT volume measurementEpicardial adipose tissue measurementsEpicardial adipose tissue volumeAssociated with risk of cardiovascular eventsRisk of cardiovascular eventsMedian follow-upIncreased risk of deathGated computed tomographyImprove risk stratificationAdipose tissue measurementsAssociated with riskRisk of deathAttenuation correction imagesGated CTChest CTNo significant differencePrognostic informationCardiovascular eventsFollow-upArtificial Intelligence Predicts Hospitalization for Acute Heart Failure Exacerbation in Patients Undergoing Myocardial Perfusion Imaging
Feher A, Bednarski B, Miller R, Shanbhag A, Lemley M, Miras L, Sinusas A, Miller E, Slomka P. Artificial Intelligence Predicts Hospitalization for Acute Heart Failure Exacerbation in Patients Undergoing Myocardial Perfusion Imaging. Journal Of Nuclear Medicine 2024, 65: jnumed.123.266761. PMID: 38548351, PMCID: PMC11064832, DOI: 10.2967/jnumed.123.266761.Peer-Reviewed Original ResearchConceptsMyocardial perfusion imagingHF hospitalizationHeart failureStress left ventricular ejection fractionPerfusion imagingHF exacerbationPredictive of HF hospitalizationsSPECT/CT myocardial perfusion imagingMyocardial perfusionInternational cohortAcute heart failure exacerbationMedian follow-upVentricular ejection fractionReceiver-operating-characteristic curveClinical risk factorsHeart failure exacerbationExternal validation cohortAcute HF exacerbationPrevent HF hospitalizationsImaging parametersCalcium scoreEjection fractionClinical parametersCT scanValidation cohortAI-Defined Cardiac Anatomy Improves Risk Stratification of Hybrid Perfusion Imaging
Miller R, Shanbhag A, Killekar A, Lemley M, Bednarski B, Kavanagh P, Feher A, Miller E, Bateman T, Builoff V, Liang J, Newby D, Dey D, Berman D, Slomka P. AI-Defined Cardiac Anatomy Improves Risk Stratification of Hybrid Perfusion Imaging. JACC Cardiovascular Imaging 2024, 17: 780-791. PMID: 38456877, PMCID: PMC11222053, DOI: 10.1016/j.jcmg.2024.01.006.Peer-Reviewed Original ResearchComputed tomography attenuation correctionMajor adverse cardiovascular eventsCoronary artery calciumLV massMyocardial perfusion imagingPerfusion imagingSingle-photon emission computed tomography/computed tomographyIncreased risk of MACEAssociated with major adverse cardiovascular eventsRisk of Major Adverse Cardiovascular EventsCardiac chamber volumesMedian follow-upCT-based volumesRight ventricular volumesImprove cardiovascular risk assessmentAdverse cardiovascular eventsQuartile of LV massContinuous net reclassification indexCoronary artery diseaseNet reclassification indexCardiovascular risk assessmentTomography/computed tomographyConsecutive patientsImprove risk predictionPrognostic utilityAI-derived epicardial fat measurements improve cardiovascular risk prediction from myocardial perfusion imaging
Miller R, Shanbhag A, Killekar A, Lemley M, Bednarski B, Van Kriekinge S, Kavanagh P, Feher A, Miller E, Einstein A, Ruddy T, Liang J, Builoff V, Berman D, Dey D, Slomka P. AI-derived epicardial fat measurements improve cardiovascular risk prediction from myocardial perfusion imaging. Npj Digital Medicine 2024, 7: 24. PMID: 38310123, PMCID: PMC10838293, DOI: 10.1038/s41746-024-01020-z.Peer-Reviewed Original ResearchEpicardial adipose tissueMyocardial infarctionPerfusion imagingEpicardial adipose tissue measurementsEpicardial adipose tissue volumeEAT attenuationMedian follow-upIncreased risk of deathEpicardial fat measurementMyocardial perfusion imagingAssociated with cardiovascular riskCoronary artery diseaseAssociated with deathEating measuresRisk of deathEAT volumeLow-dosePrognostic insightsFollow-upCardiovascular riskCardiovascular risk predictionUngated CTArtery diseaseIncreased riskCardiac silhouette