Diagnostic Innovations in Glaucoma: Clinical Electrophysiology
Diagnostic Innovations in Glaucoma: Clinical Electrophysiology
批准号:
7242398
负责人:
CHRISTOPHER BOWD
金额:
$21.81万
依托单位国家:
美国
项目类别:
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-07-01 至 2009-06-30
关键词:
AddressCaliforniaCaringClinicalCommunitiesDataDefectDetectionDevelopmentDiagnosisDiagnosticDiagnostic ProcedureDiseaseElectrophysiology (science)ElectroretinographyEnrollmentEvaluationEyeFrequenciesFundingFutureGlaucomaImageImaging TechniquesIndividualInvestigationLasersLongitudinal StudiesMachine LearningMeasurementMeasuresMethodsMonitorNamesNational Eye InstituteNerve DegenerationOnset of illnessOphthalmoscopyOptic DiskOptic NerveOptical Coherence TomographyParticipantPatientsPatternPerimetryPeripheralPersonal SatisfactionPhotographyPsychophysiologyRangeReference StandardsRelative (related person)ResearchRetinalScanningScotomaSensitivity and SpecificitySeveritiesStandards of Weights and MeasuresStructureSuspect GlaucomasTechniquesTechnologyTestingThickTimeUnited States National Institutes of HealthUniversitiesVisionVision researchVisualVisual PathwaysVisual evoked cortical potentialbasedesigndiagnostic accuracyganglion cellimprovedindependent component analysisinnovationnovelnovel diagnosticsoptic nerve disorderoptical imagingpolarimetryprogramsresponseretinal nerve fiber layerstereoscopicvector
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): This application proposes to investigate the diagnostic precision for detecting glaucoma of clinical electrophysiological measurement (pattern electroretinogram, PERG; and multifocal visual evoked potentials, mfVEP), a technique identified as an important recent glaucoma- related development in eye research by the 2004 National Eye Institute (NEI) National Plan. Aim 1: Electrophysiological responses will be characterized in glaucoma, suspect and healthy eyes and the diagnostic accuracy of these commercially available techniques will be compared to current reference standards (evaluation of stereoscopic photographs of the optic disc and standard automated perimetry) and to recently developed diagnostic techniques including optical imaging of the optic disc and retinal nerve fiber layer (RNFL) (confocal scanning laser ophthalmoscopy, optical coherence tomography, and scanning laser polarimetry) and visual function-specific perimetry (short-wavelength automated perimetry and frequency doubling technology perimetry). Aim 2: Novel use of machine learning classifier techniques (e.g. relevance vector machines, support vector machines, mixture of Gaussian techniques, independent components analysis) will be applied to electrophysiological data to improve its diagnostic accuracy and data from different diagnostic techniques (named above) will be combined to improve overall diagnostic accuracy. Aim 3: Electrophysiological measurements will be validated as functional indicators of optic nerve damage by examining the relationship between electrophysiological abnormality and optic disc and RNFL damage in glaucoma and glaucoma suspect patients. 210 patients (105 glaucoma's, 105 glaucoma suspects) and 105 healthy participants will be enrolled and studied cross-sectionally. The specific aims of this proposal address the current NEI Glaucoma and Optic Neuropathies Program objectives of developing improved diagnostic measures to characterize and detect optic nerve disease onset, determining functional correlates of optic nerve damage, and characterizing glaucomatous neurodegeneration within the visual pathways at structural and functional levels. Information about the relative usefulness of electrophysiological measurement, optical imaging techniques, and ganglion cell-specific perimetry for glaucoma detection is important to the clinical community for determining future evidence-based changes in standard of care for glaucoma diagnosis and monitoring. These studies will demonstrate the relative usefulness of electrophysiological measurement (pattern electroretinogram, PERG; multi-focal visual evoked potential, mfVEP) compared to optical imaging techniques (confocal scanning ophthalmoscopy, optical coherence tomography, scanning laser polarimetry) and ganglion cell-specific perimetry (short wavelength and frequency doubling perimetry) for glaucoma detection. The proposal addresses the current NEI Glaucoma and Optic Neuropathies Program objectives of developing improved diagnostic measures to characterize and detect optic nerve disease onset, determining functional correlates of optic nerve damage, and characterizing glaucomatous neurodegeneration within the visual pathways at structural and functional levels. Findings will be important to the clinical community for determining future evidence-based changes in standard of care for glaucoma diagnosis and monitoring.
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会议论文
Machine Learning Methods for Detecting Disease-related Functional and Structural Change in Glaucoma
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批准号:9517942
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项目类别:
-
资助金额:$19.38万
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财政年份:2017
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负责人:CHRISTOPHER BOWD
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依托单位:
Predicting and Detecting Glaucomatous Progression Using Pattern Recognition
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批准号:8410578
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项目类别:
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资助金额:$36.81万
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财政年份:2012
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负责人:CHRISTOPHER BOWD
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依托单位:
Predicting and Detecting Glaucomatous Progression Using Pattern Recognition
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批准号:8216617
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项目类别:
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资助金额:$38.68万
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财政年份:2012
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负责人:CHRISTOPHER BOWD
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依托单位:
Predicting and Detecting Glaucomatous Progression Using Pattern Recognition
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批准号:8601076
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项目类别:
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资助金额:$37.98万
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财政年份:2012
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负责人:CHRISTOPHER BOWD
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依托单位:
Diagnostic Innovations in Glaucoma: Clinical Electrophysiology
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批准号:7452327
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项目类别:
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资助金额:$18.93万
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财政年份:2007
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负责人:CHRISTOPHER BOWD
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依托单位:
海外基金