1. Duke University Receives NIH Grant for Robotic Point-of-Care OCT

    Duke University Receives NIH Grant for Robotic Point-of-Care OCT

    Duke University Received a 2022 NIH Grant for $97,825 for Robotic Point-of-Care OCT. The principal investigator is Mark Draelos. Below is a summary of the proposed study.

    The PI was previously funded by the F30 mechanism while completing the Duke Medical Scientist Training Program. He has since completed medical school and internship and now returns for a full-time research career. This career development proposal is an effective continuation of the PI’s prior mentored training and research experience and seeks to develop him into an independent investigator. The proposed project concerns the role of optical coherence tomography (OCT) in retinal disease screening. Preventable retinal blindness affects tens of millions of Americans and hundreds of millions worldwide. Its top three causes are chronic, progressive conditions that yield irreversible vision loss after an initial asymptomatic period. Annual screening is therefore essential to detect and treat these diseases before sight deteriorates. Rates of screening are suboptimal, however, because the proper eye examination is difficult for and inaccurate when performed by primary care providers (PCPs). OCT is an essential imaging modality for management of retinal diseases. Currently, clinical OCT is deployed as bulky tabletop instruments that require trained ophthalmic photographers, dedicated imaging suites, and mechanical head stabilization with chinrests for operation, which has prevented OCT-based eye screening by PCPs. We recently introduced robotic point-of-care OCT (RAOCT) as a fundamentally new paradigm for OCT-based eye examination that overcomes the barriers that restrict OCT to ophthalmology offices. RAOCT offers semi- or fully-automated non-contact OCT imaging by bringing a robot-mounted OCT scanner to the patient, tracking them throughout a large imaging workspace, and optically correcting for motion artifact. Our laboratory prototypes using this approach have demonstrated sufficient OCT quality in freestanding and seated subjects for anatomic measurement and clinical correlation, respectively, with only minimal operator training. These prototypes function reliably only under controlled laboratory conditions, however, and significant technology development for portability, tracking robustness, and motion correction is necessary to yield a clinic- ready instrument. This project therefore seeks to advance our bench-mounted prototypes into fully-fledged mobile systems for imaging in non-specialist clinics and to test them against the OCT standard-of-care. First, we will transition our prototype into a wheeled cart that can be brought into clinics, upgrade our robot arm for extended reach, and redesign our robot-mounted scanner for improved tracking under realistic imaging conditions. Next, we will enhance motion attenuation by transitioning image processing algorithms to dedicated hardware, by adding digital correction for residual motion, and by incorporating a novel adaptive scanning technique to reduce imaging time. Finally, we will perform RAOCT imaging in ophthalmology clinics to compare against the standard of care and in primary care offices to evaluate screening workflows. Completion of this project will develop robotic point-of-care OCT into a turnkey imaging platform that promises to enhance eye screening in primary care settings.

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