3D OCT Angiography for quantitative characterization of diabetic retinopathy
3D OCT 血管造影定量表征糖尿病视网膜病变
基本信息
- 批准号:9299870
- 负责人:
- 金额:$ 20.63万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-04-01 至 2019-03-31
- 项目状态:已结题
- 来源:
- 关键词:African AmericanAmericanAngiographyArchitectureAreaBlood VesselsBlood capillariesBrain MappingBrain imagingClinicClinicalClinical ResearchCommunitiesComputational algorithmComputer softwareDataData AnalysesDatabasesDetectionDevelopmentDiabetic RetinopathyDimensionsDiseaseDisease stratificationEarly DiagnosisEarly treatmentEdemaEyeEye diseasesFDA approvedFluorescein AngiographyFunctional disorderFundingGeometryImageImage AnalysisImpairmentIschemiaLaboratoriesMagnetic Resonance ImagingMeasuresMethodsMicroaneurysmModelingMonitorMorphologyOptical Coherence TomographyPathologyPerfusionPlayPopulationPopulation StudyPublic HealthPublishingResearchResolutionRetinaRetinalRetinal DiseasesRetinal EdemasRetinal Vein OcclusionRiskRoleScientistSeveritiesSeverity of illnessShunt DeviceSkeletonSoftware ToolsSource CodeSurfaceSymptomsTechniquesTestingThree-Dimensional ImagingThree-dimensional analysisTimeTranslatingVisualWorkbasecapillaryclinical Diagnosisclinically relevantcohortcomputerized toolscotton wool spotsdensitydiabetichistological studiesmaculaneovascularizationneuroimagingneurosensorynon-invasive imagingnovelretinal ischemiashape analysistoolweb site
项目摘要
Abstract
In the clinical diagnosis of diabetic retinopathy (DR), fluorescein angiography (FA) is currently the only method
used routinely for the detection and treatment of ischemia, but it is an invasive method and not sensitive to
early microvascular changes before the onset of visual symptoms. For the early detection and management of
ischemia in DR, Optical Coherence Tomography Angiography (OCTA) is a novel method that has obtained
FDA approval in 2015. Compared with FA, OCTA allows non-invasive imaging of both the neurosensory retina
as well as the retinal vasculature at ~10m resolution. Some recent studies have successfully used OCTA to
extract quantitative 2D metrics that are well correlated with DR severity. Dr. Kashani’s group has pioneered
several of the 2D OCTA metrics for the quantitative assessment of capillary morphology and density. While
highly valuable, these 2D OCTA metrics were derived from the en face projection of the 3D OCTA data, and
therefore inevitably obscure the geometric and topological information in the original 3D vasculature networks.
To overcome this fundamental limitation, Drs. Shi and Kashani will collaborate in this R21 project to develop
truly 3D metrics for the automated analysis of OCTA data and apply them for the early diagnosis of DR in large
scale eye studies. For brain mapping research, Dr. Shi’s group at Laboratory of Neuro Imaging (LONI) of USC
has developed various advanced computational tools for 3D shape analysis based on generally applicable
principles from intrinsic geometry. In this project, we will translate and adapt these tools for 3D retinal
vasculature modeling and analysis using OCTA data. There are three specific aims in this project: (1) Apply
cutting-edge computational algorithms developed in brain imaging to develop novel 3D OCTA metrics for
volume- and surface-based quantitation of retinal capillary density and morphology. (2) Define the relationship
and reliability of 2D- and 3D-OCTA metrics with clinical severity of DR using our previously published cohorts
of healthy and diabetic subjects. (3) Validate the relationship of 2D- and 3D-OCTA metrics with DR severity
among a well-characterized population from the NEI funded African American Eye Diseases Study (AFEDS)
and identify OCTA metrics associated with currently undetectable (sub-clinical) retinopathy. Given the rich
computational tools developed by Dr. Shi’s group at LONI and the already collected, large-scale OCTA data
(n=396) from the AFEDS study and Dr. Kashani’s published studies, the risk of this project is low, but the
resulting 3D OCTA metrics and associated software tools will be highly valuable to the research and potentially
clinical community. We will make all the software tools and source codes developed in this project freely
available through the NITRC (http://www.nitrc.org) and LONI website (http://www.loni.usc.edu/Software).
摘要
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Amir H Kashani其他文献
Amir H Kashani的其他文献
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{{ truncateString('Amir H Kashani', 18)}}的其他基金
Functional Imaging in Hypoxic-Ischemic Retinal Disease
缺氧缺血性视网膜疾病的功能成像
- 批准号:
10456440 - 财政年份:2021
- 资助金额:
$ 20.63万 - 项目类别:
Validation of Imaging and Blood-based Small Vessel VCID Biomarkers in Multiethnic Population
多种族人群中影像学和基于血液的小血管 VCID 生物标志物的验证
- 批准号:
10611821 - 财政年份:2021
- 资助金额:
$ 20.63万 - 项目类别:
Multidimensional Assessment of Brain Health as A Marker of Dementia Risk and Resilience
大脑健康的多维评估作为痴呆症风险和复原力的标志
- 批准号:
10670132 - 财政年份:2020
- 资助金额:
$ 20.63万 - 项目类别:
Multidimensional Assessment of Brain Health as A Marker of Dementia Risk and Resilience
大脑健康的多维评估作为痴呆症风险和复原力的标志
- 批准号:
10451624 - 财政年份:2020
- 资助金额:
$ 20.63万 - 项目类别:
Multidimensional Assessment of Brain Health as A Marker of Dementia Risk and Resilience
大脑健康的多维评估作为痴呆症风险和复原力的标志
- 批准号:
10261497 - 财政年份:2020
- 资助金额:
$ 20.63万 - 项目类别:
Assessment of Retinal Capillary Density, Morphology and Function in Retinal Vascular Disease Using Novel OCT Angiography Based Metrics
使用基于 OCT 血管造影的新型指标评估视网膜血管疾病中的视网膜毛细血管密度、形态和功能
- 批准号:
10004661 - 财政年份:2019
- 资助金额:
$ 20.63万 - 项目类别:
Assessment of Retinal Capillary Density, Morphology and Function in Retinal Vascular Disease Using Novel OCT Angiography Based Metrics
使用基于 OCT 血管造影的新型指标评估视网膜血管疾病中的视网膜毛细血管密度、形态和功能
- 批准号:
10460809 - 财政年份:2019
- 资助金额:
$ 20.63万 - 项目类别:
Assessment of Retinal Capillary Density, Morphology and Function in Retinal Vascular Disease Using Novel OCT Angiography Based Metrics
使用基于 OCT 血管造影的新型指标评估视网膜血管疾病中的视网膜毛细血管密度、形态和功能
- 批准号:
10245006 - 财政年份:2019
- 资助金额:
$ 20.63万 - 项目类别:
Imaging Cerebral and Retinal Microvasculature in Cerebral Small Vessel Disease
脑小血管疾病的脑和视网膜微血管成像
- 批准号:
9356350 - 财政年份:2016
- 资助金额:
$ 20.63万 - 项目类别:
Validation of Imaging and Blood-based Small Vessel VCID Biomarkers in Multiethnic Population
多种族人群中影像学和基于血液的小血管 VCID 生物标志物的验证
- 批准号:
10369505 - 财政年份:2016
- 资助金额:
$ 20.63万 - 项目类别:
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