Ultra-high speed AO-OCT clinical system to image ganglion cells and microglia
超高速 AO-OCT 临床系统对神经节细胞和小胶质细胞进行成像
基本信息
- 批准号:10547181
- 负责人:
- 金额:$ 87.56万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-30 至 2024-08-31
- 项目状态:已结题
- 来源:
- 关键词:AreaBiological MarkersBlindnessBuffersCellsClinicalCollaborationsCommunitiesDataDegenerative DisorderDetectionDevelopmentDiabetes MellitusDiabetic RetinopathyDiagnosisDiseaseDisease MarkerDisease ProgressionEarElementsEvaluationEyeGangliaGlaucomaGoalsGovernmentHumanImageImaging TechniquesInvestigationLabelLateralLeadLegal patentMarket ResearchMassachusettsMicrogliaMonitorMorphologic artifactsMotionNerve FibersNeurosciencesNoiseOphthalmologyOphthalmoscopesOpticsPathogenesisPatientsPerformancePersonsPhagocytosisPharmacotherapyPhasePlayRecording of previous eventsResearchResolutionRetinaRetinal DegenerationRetinal DiseasesRetinal Ganglion CellsRoleScanningSeverity of illnessSignal TransductionSourceSpatial DistributionSpeedStructureSystemTechnologyTestingTimeVisionadaptive opticsaxon injurybaseclinical diagnosticsclinical imagingcostdensitydesigndiagnostic platformexperienceganglion cellhealthy volunteerhuman subjectimagerimaging approachimaging platformimaging systemimprovedimproved functioninginnovationinstrumentinterestlensmacrophagenext generationnovelnovel therapeuticsoptical imagingphysical scienceprogramsprototyperetinal imagingroutine imagingspecific biomarkerstool
项目摘要
Project Summary/Abstract
There is currently a significant need for new imaging techniques that may enable accurate
quantification of biomarkers for detection, diagnosis, and monitoring of retinal diseases progression.
Physical Sciences Inc. (PSI), Massachusetts Eye and Ear (MEE), and Joslin Diabetes Center (JDC)
propose to develop a clinical tool able to routinely image retinal ganglion cells (RGCs) and to characterize
microglia spatial distribution and temporal dynamics in live human eyes using a label-free adaptive optics
(AO) imaging approach for improved diagnosis and treatment of glaucoma and diabetic retinopathy (DR).
An ultra-high speed AO-OCT system will be designed and built based on a number of recently
demonstrated innovations: lens-based design, ultra-high speed to eliminate motion artifacts, buffered swept
source (SS) and dual beam approach to increase A-line rate to the MHz range, adaptive lens, dual-axis
MEMS for raster scanning, and the use of polarization optics to eliminate specular reflections on optical
elements. The retinal imager will be tested in a clinical setting at MEE and JDC on a large group of
glaucoma and DR subjects experiencing a wide range of disease severity. Specific biomarkers for glaucoma
and DR will be defined based on patient data acquired by our collaborators from MEE and JDC.
PSI has a long, successful history of developing and commercializing high-resolution retinal imagers for
the ophthalmic research market which gives us a competitive advantage in developing and maturing this
platform that enables routine clinical imaging of human subjects and motivates a Direct to Phase II
approach. A successful program and subsequent Phase III commercial development will provide clinicians
with high performance retinal imaging for glaucoma and DR investigations at a lower cost and improved
functionality superior to other non-AO retinal imagers. Early adaptors of this technology within the research
community will grow our understanding of vision and its disruption by glaucoma and DR and will investigate
the effects of new drugs and therapies. The ability to visualize ganglion and macrophage cells without
fluorescent labeling in the human eye represents an important advance for both ophthalmology and
neuroscience, which will lead to identification of novel disease biomarkers and new avenues of exploration
in disease progression.
项目总结/摘要
目前存在对新成像技术的显著需求,所述新成像技术可以实现准确的成像。
用于检测、诊断和监测视网膜疾病进展的生物标志物的定量。
物理科学公司(PSI)、马萨诸塞州眼耳中心和乔斯林糖尿病中心
我建议开发一种能够常规成像视网膜神经节细胞(RGC)并表征
使用无标记自适应光学在活体人眼中小胶质细胞的空间分布和时间动态
(AO)影像学方法,用于改善青光眼和糖尿病视网膜病变(DR)的诊断和治疗。
本论文将基于近年来的一些研究成果,设计并搭建超高速声光OCT系统,
展示创新:基于镜头的设计,超高速消除运动伪影,缓冲扫描
源(SS)和双光束方法,以增加A线速率到MHz范围,自适应透镜,双轴
MEMS用于光栅扫描,并使用偏振光学器件消除光学器件上的镜面反射。
元素视网膜成像仪将在临床环境中进行测试,在一个大的群体,
青光眼和DR受试者经历广泛的疾病严重程度。青光眼的特异性生物标志物
和DR将根据我们的合作者从CNAS和JDC获得的患者数据进行定义。
PSI在开发和商业化高分辨率视网膜成像仪方面有着悠久而成功的历史,
眼科研究市场,这使我们在开发和成熟这一领域具有竞争优势。
该平台能够对人类受试者进行常规临床成像,并促进直接进入II期
approach.一个成功的项目和随后的第三阶段商业开发将为临床医生提供
具有高性能的视网膜成像,用于青光眼和DR检查,成本更低,
功能上级于其他非AO视网膜成像器。这项技术在研究中的早期应用
社区将增加我们对视力的理解,以及青光眼和DR对视力的破坏,并将调查
新药物和疗法的效果。能够可视化神经节和巨噬细胞,
人眼中的荧光标记代表了眼科学和生物医学的重要进展。
神经科学,这将导致识别新的疾病生物标志物和新的探索途径
在疾病进展中。
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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Mircea Mujat其他文献
Mircea Mujat的其他文献
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{{ truncateString('Mircea Mujat', 18)}}的其他基金
Evaluation of photoreceptors health and function in diabetic retinopathy patients using a high-resolution retinal imaging device with controlled light stimulus
使用受控光刺激的高分辨率视网膜成像设备评估糖尿病视网膜病变患者的光感受器健康和功能
- 批准号:
10696696 - 财政年份:2023
- 资助金额:
$ 87.56万 - 项目类别:
Ultra-high speed AO-OCT clinical system to image ganglion cells and microglia
超高速 AO-OCT 临床系统对神经节细胞和小胶质细胞进行成像
- 批准号:
10705315 - 财政年份:2022
- 资助金额:
$ 87.56万 - 项目类别:
Versatile Eye Tracking for Improved High-resolution Retinal Imaging
多功能眼动追踪可改善高分辨率视网膜成像
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10154113 - 财政年份:2021
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Multispectral cellular-level retinal imaging for early detection of Alzheimer’s disease
用于早期检测阿尔茨海默病的多光谱细胞水平视网膜成像
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10323717 - 财政年份:2021
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Comprehensive imaging and quantification of blood flow for investigating ocular diseases without additional contrast agent
无需额外造影剂即可对血流进行全面成像和量化以研究眼部疾病
- 批准号:
10295545 - 财政年份:2019
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Comprehensive imaging and quantification of blood flow for investigating ocular diseases without additional contrast agent
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Measurement of Retinal Nerves and Blood Vessels as Markers for Type 1 Diabetes
测量视网膜神经和血管作为 1 型糖尿病的标志物
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9754819 - 财政年份:2017
- 资助金额:
$ 87.56万 - 项目类别:
Multi-modal AO-LSO Phase Gradient Imaging of the Inner Retina
内视网膜多模态 AO-LSO 相位梯度成像
- 批准号:
9788095 - 财政年份:2014
- 资助金额:
$ 87.56万 - 项目类别:
Combined RCM and PSOCT for skin cancer imaging
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8534059 - 财政年份:2012
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$ 87.56万 - 项目类别:
Combined RCM and PSOCT for skin cancer imaging
结合 RCM 和 PSOCT 进行皮肤癌成像
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8251261 - 财政年份:2012
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$ 87.56万 - 项目类别:
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