Personalizing Glaucoma Diagnosis by Disease Specific Patterns and Individual Eye Anatomy
Personalizing Glaucoma Diagnosis by Disease Specific Patterns and Individual Eye Anatomy
批准号:
10245094
负责人:
Tobias Elze
金额:
$44.83万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-30 至 2024-07-31
关键词:
AnatomyAtrophicAxonBioinformaticsBlindnessClinicalCluster AnalysisComputer softwareConsensusCustomDataData SetDefectDetectionDevelopmentDiagnosisDiagnosticDiseaseEthnic OriginEventEvolutionEyeFutureGlaucomaGoalsHemorrhageImpairmentIndividualInvestigationLengthLocationMapsMeasurementMeasuresModelingMorphologic artifactsNerve FibersOptic DiskOptical Coherence TomographyPatientsPatternProbabilityProceduresPrognosisPublic HealthRefractive ErrorsRetinaRetinal DefectRetinal Ganglion CellsRetinal blind spotSamplingStructureStructure-Activity RelationshipSystemThickTimeVariantVisionVisual FieldsWorkbasecentral retinal arteryclinical applicationclinical centerclinical practicedisease diagnosisfollow-upfovea centralisimprovedindexingmultidisciplinaryneglectnovel diagnosticsopen sourceoptic nerve disorderretinal nerve fiber layersample fixationsexstatistical learning
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Project Summary/Abstract
Glaucoma is a disease of the optic nerve which is accompanied by visual field (VF) loss. While accurate VF loss
diagnosis and the detection of its progression over time is of high relevance to clinical practitioners as it indicates
the initiation of or change in ocular therapy, there is no consensus on objective measures for this purpose, and
VF measurements are known to be often unreliable. The main objective of this project is to develop clinically
applicable measures to improve the diagnosis of glaucomatous VF loss and of its progression by two approaches:
First, the identification of representative loss patterns and their progression, achieved by large-scale, customized
bioinformatical procedures applied to data from glaucoma patients from nine clinical centers and second, the
inclusion of eye and patient specific personalized parameters. In total, 480,486 VFs, are available for this project.
One major aim is to develop novel diagnostic indices based on computationally identified evolution patterns of
VF loss, particularly (1) an index that denotes the probability of glaucomatous vision loss and (2) an index that
assigns probabilities to a VF that follow-up measurements will be in a certain defect class. The indices will
be statistically evaluated on separate VF samples and compared to existing approaches. Routinely available
patient specific parameters which are candidates to impact glaucomatous vision loss are patient ethnicity, type of
glaucoma, spherical equivalent (SE) of refractive error and the location of the blind spot relative to fixation. The
effect of these parameters on the vision loss patterns will be systematically studied. The impact of their inclusion
in the novel diagnostic indices and their potential improvement on glaucoma diagnosis will be quantified on a
separate data set. A further aim is the calculation of a spatial map specific to a measured VF that represents the
preferred VF locations of future defects as well as their reliability as an aid to event-based progression diagnosis.
A second major objective is the investigation of the relationship of VF loss and individual parameters related
to retinal structure, based on retinal nerve fiber layer thickness (RNFLT) measurements around the optic disc.
The inter-relationship of representative patterns of RNFLT and its decrease over time with trajectories of major
retinal arteries, SE, and blind spot location is systematically studied, and the impact on patterns of VF loss
is quantitatively analyzed with the goal to improve the interpretation of existing VF loss and to predict future
glaucomatous vision loss. Main contributions of the project with relevance to clinical practice are publicly available
open-source software implementations of new diagnostic indices and maps, enhanced by individual functional
and structural parameters, and a detailed and personalized model for the relationship between retinal structure
and glaucomatous vision loss.
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Personalizing Glaucoma Diagnosis by Disease Specific Patterns and Individual Eye Anatomy
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批准号:10018038
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项目类别:
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资助金额:$47.34万
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财政年份:2019
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负责人:Tobias Elze
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依托单位:
Associating retinal nerve fiber layer thickness with glucose metabolism and diabetic retinopathy
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批准号:10002287
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项目类别:
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资助金额:$24.03万
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财政年份:2019
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负责人:Tobias Elze
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依托单位:
Personalizing Glaucoma Diagnosis by Disease Specific Patterns and Individual Eye Anatomy
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批准号:10669671
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项目类别:
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资助金额:$46.12万
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财政年份:2019
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负责人:Tobias Elze
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依托单位:
Associating retinal nerve fiber layer thickness with glucose metabolism and diabetic retinopathy
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批准号:9809589
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项目类别:
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资助金额:$31.38万
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财政年份:2019
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负责人:Tobias Elze
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依托单位:
Personalizing Glaucoma Diagnosis by Disease Specific Patterns and Individual Eye Anatomy
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批准号:10454416
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项目类别:
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资助金额:$44.56万
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财政年份:2019
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负责人:Tobias Elze
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依托单位:
A hybrid artificial intelligence framework for glaucoma monitoring
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批准号:9892013
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项目类别:
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资助金额:$22.08万
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财政年份:2019
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负责人:Tobias Elze
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依托单位:
Core Grant for Vision Research-LABORATORY COMPUTER APPLICATIONS MODULE (LCAM)
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批准号:10705719
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项目类别:
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资助金额:$20.36万
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财政年份:1997
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负责人:Tobias Elze
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依托单位:
海外基金