SBIR Phase II: Non-Invasive Retinal Oximetry for Detecting Diabetic Retinopathy prior to Structural Damage

这个SBIR第二阶段项目演示并临床验证了一种新的非侵入性成像技术，可以在结构损伤发生之前检测到糖尿病视网膜病变。糖尿病视网膜病变是世界上导致视力丧失的主要原因之一。这种I型和II型糖尿病的破坏性并发症会对视网膜敏感的血管系统造成结构性损害。一旦造成结构性破坏，要改善它即使不是不可能，也是困难的。视网膜血管血氧饱和度的微小变化已被证明是糖尿病视网膜病变在结构损伤发生之前的可靠指标。由于没有临床非侵入性技术能够检测到这些微小的功能变化，因此存在对新的视网膜血氧仪技术的主要需求。糖尿病视网膜病变影响着全球2亿人。美国糖尿病协会报告称，2012年美国糖尿病造成的损失为2450亿美元，其中包括690亿美元的生产力下降和1760亿美元的医疗费用。由于40%的糖尿病患者预计会发展为糖尿病视网膜病变，估计每年糖尿病视网膜病变的经济成本为980亿美元。通过减轻糖尿病视网膜病变的发生，这项技术将有助于降低糖尿病视网膜病变的治疗成本及其整体经济负担，并有助于挽救全球数百万人的视力。拟议技术背后的主要技术创新是使用一种基于物理的新模型来克服高分辨率视网膜成像的挑战。这些挑战包括视网膜的多层结构、吸光度动力学，以及需要在一张快照中生成图像以减少运动伪影。与现有的基于结构成像的方法相比，该项目的成功成果将成为世界各地眼科医生的商业选择技术，使早期糖尿病视网膜病变或视网膜病变前期的检测具有成本效益。该技术的开发通过实验室和实际使用环境之间的迭代优化来生成可靠的、经过验证的数据。具体地说，在第二阶段，该项目的研究目标在两个平行的轨道上进行：1)改进核心成像系统，以及2)在临床环境中使用模型和人类受试者进行验证。该项目的成果将是一种易于使用、可靠的诊断成像和监测技术，具有经过验证的临床实用价值，可以在患者发生结构性损害之前，根据功能特性检测糖尿病视网膜病变的发病。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This SBIR Phase II project demonstrates and clinically validates a novel, non-invasive imaging technology to detect diabetic retinopathy before structural damage occurs. Diabetic retinopathy is among the leading causes of vision loss in the world. This devastating complication of both type I and II diabetes results in structural damage to the sensitive vasculature of the retina. Once structural damage is inflicted, it is difficult, if not impossible, to ameliorate it. Small changes in the retinal vasculature's oxygen saturation have been shown to be a reliable indicator of diabetic retinopathy before structural damage occurs. Since there is no clinical non-invasive technology capable of detecting these small functional changes, a major need exists for new retinal oximetry technologies. Diabetic retinopathy affects 200 million people worldwide. The American Diabetes Association reports that the cost of diabetes in the US in 2012 was $245 billion, including $69 billion in reduced productivity and $176 billion in medical costs. Since 40% of diabetics are anticipated to develop diabetic retinopathy, the estimated economic cost of diabetic retinopathy is $98 billion annually. By mitigating the occurrence of diabetic retinopathy, this technology will help reduce the cost of diabetic retinopathy treatment, its overall economic burden, and help save the vision of millions of people around the world.The primary technical innovation behind the proposed technology is its use of a novel physics-based model to overcome the challenges of high-resolution retinal imaging. These challenges include the multi-layered structure of the retina, absorbance dynamics, and the need to produce an image in one snapshot to reduce motion artifacts. Compared with existing methods based on structural imaging, the successful outcome of this project will become a commercial technology-of-choice for ophthalmologists around the world, enabling cost-effective detection of early stage diabetic retinopathy or pre-retinopathy. The development of the technology proceeds through iterative optimization between laboratory and real-use environments to generate robust, validated data. Specifically, in Phase II, the research objectives of the project are pursued in two parallel tracks: 1) refinement of the core imaging system, and 2) validation using model and human subjects in a clinical environment. The outcome of this project will be an easy-to-use, reliable diagnostic imaging and monitoring technology with proven clinical utility in detecting the onset of diabetic retinopathy based on functional properties, before structural damage has occurred in the patient.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.