The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop a novel, intraoperative imaging technology to addresse the problem of inadvertent cuts to vasculature during minimally invasive surgeries. Patients who suffer vascular injury face increased risks of developing nosocomial infections and, in up to 32% of cases, mortality. These patients are burdened with longer hospital stays and corrective procedures that add tens of thousands of dollars to their healthcare expenses. This is compounded by obesity, a risk factor that is associated with higher rates of conversion from minimally invasive to open surgery due to limitations in the surgeon?s ability to visualize and navigate vasculature. Hence, there is a critical need to identify and assess hidden vasculature in real time. The proposed technology provides users with blood vessel visualization and size metrics 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 aims to 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, and will be based on science similar to that found in pulse oximetry technology. 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.
