Laser Speckle Imaging Chip for Telehealth Applications

摘要

ABSTRACT The availability of improved diagnostic tools in the primary care environment capable of diagnosing diseases in their earliest stages could significantly improve disease management. Primary beneficiaries would be the elderly, who are at increased risk for a number of progressively debilitating diseases, but who may face practical cost and convenience hurdles in routinely presenting to specialists for examination. Retinal imaging is increasingly being recognized as a means to monitor not just ophthalmic health, but also as a surrogate indicator of neurological and cardiovascular health. And therefore, there is increasing support for its integration into primary care practice via telehealth approaches. However, current retinal imaging products that meet the cost, size, and use case requirements of the primary care environment have significant limitations in their abilities such as their inadequacy to measure blood flow or other dynamic changes in physiology. To address this shortcoming of current technology and make a clinical impact, Vasoptic has proposed to develop and commercialize a low-cost, portable, noninvasive retinal imaging instrument (the XyCAM) that can complement fundus photographs with retinal blood flow information obtained at high spatio-temporal resolution without the introduction of any dyes. During Phase I studies, we designed and developed a custom image sensing chip with high signal to noise ratio, as needed for the low-light retinal imaging application, and developed a handheld prototype with a robust software suite for image acquisition and analysis. Upon confirming safety against light toxicity, we characterized performance of the XyCAM prototype by conducting proof-of-concept experiments in animal models and proof-of-feasibility studies in human subjects. Our investigation has indicated that the XyCAM prototype can image retinal blood flow with a high spatio- temporal resolution and with high reproducibility. Based on this success and our learnings, we propose a Phase II effort which will include (a) development and validation of robust mechanisms to automatically and objectively assess the vascular status in the retina; and (b) demonstration of preliminary feasibility that the XyCAM can discriminate between normal and diseased retinas through point-of-care assessment of retinal blood flow and associated morphological and physiological metrics. Our Phase II application focuses on two disease conditions that affect the elderly and severely impact their quality of life – Alzheimer’s disease, which is also the sixth leading cause of death in the United States and diabetic retinopathy, which causes as many as 65,000 individuals to experience serious visual impairment every year. While the former could also benefit from research carried out in primary care environments leading to the development of retinal blood flow as a robust biomarker for diagnostics, the latter could benefit from increased patient compliance and early diagnostics as is possible through telehealth methods. If we are successful, this study will enable a 510(k) submission to the US FDA seeking approval to market the validated XyCAM as a general purpose retinal imager and provide us the necessary early feasibility data that justifies multi-center clinical trials to investigate the sensitivity and specificity for various disease diagnostics.