SBIR Phase II: Label-free imaging for real-time, intraoperative blood vessel visualization

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The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop a novel, intraoperative imaging technology to address the problem of inadvertent cuts to vasculature during minimally invasive surgeries. More than 17% of patients who undergo these types of in-patient surgeries suffer from an intraoperative bleeding event. When a vessel is injured, there is a higher probability of hospital borne infection due to the loss of blood, and the added cost of care per patient increases by thousands of dollars due to corrective action and extended length of stay for the patient. The risk of vascular injury is compounded by risk factors, such as obesity, which limit the surgeon's ability to visualize and navigate vasculature. Therefore, there is a critical need to identify and assess hidden vasculature in real time. The proposed technology helps identify blood vessel before a cut is made. Importantly, this system will be designed for seamless integration into a suite of surgical instruments for multiple applications. Long term, the company will provide surgeons with the preeminent imaging platform to view, assess, and characterize a range of vessels (i.e. arteries/veins, ureters and bile ducts) in real-time for improved surgical guidance and outcomes. The proposed project will develop a novel blood vessel detection and visualization platform using low-cost optical imaging sensors and light-emitting diodes (LEDs). The proposed technology will provide visual and quantitative information about vessel presence and size in real-time that can supplement a surgeon's technique. This system will be simple, cost-effective, easy to employ, and highly accurate. Traditionally, the avoidance of blood vessels during minimally invasive surgery is accomplished by visualization or costly intraoperative imaging. The proposed technology will use pulsatile light absorption characteristics of blood vessels to provide quantitative information about vessel presence and size in real-time, supplementing a surgeon's technique. This project will also add significant value to the body of research conducted in the areas of signal processing and image analysis. In addition, the proposed technology will remove the risk of data loss due to artifacts in general and motion artifacts in particular. The proposed technology will be validated ex vivo and in vivo using a porcine animal model.