2024
Deep-RPD-Net: A 3D Deep Network for Detection of Reticular Pseudodrusen on Optical Coherence Tomography Scans
Elsawy A, Keenan T, Thavikulwat A, Lu A, Bellur S, Mukherjee S, Agron E, Chen Q, Chew E, Lu Z. Deep-RPD-Net: A 3D Deep Network for Detection of Reticular Pseudodrusen on Optical Coherence Tomography Scans. Ophthalmology Science 2024, 100655. DOI: 10.1016/j.xops.2024.100655.Peer-Reviewed Original ResearchSemi-supervised learningReticular pseudodrusenOCT scansRetina specialistsOptical coherence tomographyArea under ROC curveSpectral-domain optical coherence tomographyBaseline modelOptical coherence tomography scansAge-Related Macular Degeneration StudyDetect reticular pseudodrusenFundus autofluorescence imagingDeep learning networkDeep networksBaseline methodsPretrained modelsModel decision-makingReading centerLearning networkHigh-performance metricsOCT studiesTomography scanAREDS2En faceCoherence tomographyAn Updated Simplified Severity Scale for Age-Related Macular Degeneration Incorporating Reticular Pseudodrusen Age-Related Eye Disease Study Report Number 42
Agrón E, Domalpally A, Chen Q, Lu Z, Chew E, Keenan T, Groups A. An Updated Simplified Severity Scale for Age-Related Macular Degeneration Incorporating Reticular Pseudodrusen Age-Related Eye Disease Study Report Number 42. Ophthalmology 2024, 131: 1164-1174. PMID: 38657840, PMCID: PMC11416341, DOI: 10.1016/j.ophtha.2024.04.011.Peer-Reviewed Original ResearchAge-Related Eye Disease StudyProgression to late AMDReticular pseudodrusenLate AMDFive-year ratesProgression rateAge-related macular degenerationSeverity ScaleEye Disease StudyClinical trial cohortIncrease prognostic accuracyPost hoc analysisMacular degenerationAREDS2Prognostic accuracyTrial cohortRisk featuresHoc analysisRisk categorizationPseudodrusenAge-relatedBaselineDisease StudyRiskExternal validationDetection of reticular pseudodrusen on optical coherence tomography images
Elsawy A, Keenan T, Agron E, Chen Q, Chew E, Lu Z. Detection of reticular pseudodrusen on optical coherence tomography images. Progress In Biomedical Optics And Imaging 2024, 12926: 1292632-1292632-5. DOI: 10.1117/12.3007014.Peer-Reviewed Original ResearchAge-related macular degenerationSD-OCT scansAge-Related Eye Disease Study 2Detect reticular pseudodrusenReticular pseudodrusenSD-OCTFundus autofluorescenceVolumetric spectral-domain optical coherence tomographySpectral-domain optical coherence tomographySubretinal drusenoid depositsOptical coherence tomography imagesPredictors of progressionOptical coherence tomographyReceiver characteristic operating curvesDrusenoid depositsMacular degenerationOCT studiesCoherence tomographyDisease featuresTomography imagesOperating curvePseudodrusenAge-relatedClassification networkMulti-tasking
2022
Reticular Pseudodrusen: The Third Macular Risk Feature for Progression to Late Age-Related Macular Degeneration Age-Related Eye Disease Study 2 Report 30
Agrón E, Domalpally A, Cukras C, Clemons T, Chen Q, Lu Z, Chew E, Keenan T, Groups A. Reticular Pseudodrusen: The Third Macular Risk Feature for Progression to Late Age-Related Macular Degeneration Age-Related Eye Disease Study 2 Report 30. Ophthalmology 2022, 129: 1107-1119. PMID: 35660417, PMCID: PMC9509418, DOI: 10.1016/j.ophtha.2022.05.021.Peer-Reviewed Original ResearchConceptsLate age-related macular degenerationAge-related macular degenerationAge-related eye disease studyNeovascular age-related macular degenerationColor fundus photographsHazard ratioReticular pseudodrusenGeographic atrophyHigh riskRisk factorsSeverity ScalePresence of RPDProportional hazards regression analysisMacular Degeneration AgeClinical trial cohortIndependent risk factorEye Disease StudyHazards regression analysisImportant risk factorFundus autofluorescence imagesAMD severity scaleTrial cohortRisk calculatorClinical trialsFundus photographs
2021
Multimodal, multitask, multiattention (M3) deep learning detection of reticular pseudodrusen: Toward automated and accessible classification of age-related macular degeneration
Chen Q, Keenan T, Allot A, Peng Y, Agrón E, Domalpally A, Klaver C, Luttikhuizen D, Colyer M, Cukras C, Wiley H, Magone M, Cousineau-Krieger C, Wong W, Zhu Y, Chew E, Lu Z, Group F. Multimodal, multitask, multiattention (M3) deep learning detection of reticular pseudodrusen: Toward automated and accessible classification of age-related macular degeneration. Journal Of The American Medical Informatics Association 2021, 28: 1135-1148. PMID: 33792724, PMCID: PMC8200273, DOI: 10.1093/jamia/ocaa302.Peer-Reviewed Original ResearchConceptsColor fundus photographyAge-related macular degenerationFundus autofluorescenceReticular pseudodrusenMacular degenerationStandard color fundus photographyReceiver-operating characteristic curveAdvanced imaging modalitiesExternal validationRetinal specialistsAMD featuresFundus photographyGeographic atrophyPigmentary abnormalitiesAMD diagnosisImaging modalitiesCharacteristic curvePseudodrusenDegeneration