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

这个SBIR二期项目展示并临床验证了一种新的、无创的成像技术，可以在结构损伤发生之前检测糖尿病视网膜病变。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1型和2型糖尿病的致命并发症会导致视网膜敏感血管的结构性损伤。一旦造成结构性损害，即使不是不可能，也很难改善它。视网膜血管氧饱和度的微小变化已被证明是糖尿病视网膜病变发生前的可靠指标。由于没有能够检测这些微小功能变化的临床非侵入性技术，因此主要需要新的视网膜氧饱和度测定技术。糖尿病视网膜病变影响全球2亿人。美国糖尿病协会报告称，2012年美国糖尿病的成本为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。由于预计40%的糖尿病患者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和总体经济负担，并帮助拯救全球数百万人的视力。提出的技术背后的主要技术创新是它使用了一种新的基于物理的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，以及需要在一次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技术选择，使早期糖尿病视网膜病变或视网膜病变前期的成本效益检测成为可能。该技术的发展通过实验室和实际使用环境之间的迭代优化来生成稳健的、经过验证的数据。具体而言，在II期，该项目的研究目标分为两个并行轨道：1)改进核心成像系统，2)在临床环境中使用模型和人体受试者进行验证。该项目的结果将是一种易于使用，可靠的诊断成像和监测技术，具有临床应用价值，可在患者发生结构损伤之前，根据功能特性检测糖尿病视网膜病变的发病。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.