Project Summary. Dyad Medical, Inc. will create intravascular Optical Coherence Tomography (IVOCT) software for clinical, live time determination of stent apposition and for offline analysis of stent implantation. Every year, 100s of thousands of patients in the US are treated with intravascular stents creating an opportunity for both solutions. Although advancements such as drug eluting metal stents hinder restenosis, there remains significant room for improvement. Stent design parameters include drug, material (bioresorbable vs metal), polymer composition, coatings to stimulate cell coverage, etc. To optimize designs, sensitive, in vivo assessments are needed for preclinical and clinical evaluations. IVOCT is the lone imaging modality with the resolution and contrast to meet this challenge. Dyad's automated software solution promises to drastically cut stent image analysis from 6-16 hrs of manual analysis to less than 2 minutes per single stent, as demonstrated in our Phase I feasibility results. We also demonstrated stent strut detection accuracy >88%, classification accuracy >88%, and stent and vessel areas with accuracy >90%. In addition to faster analysis, we will eliminate inter-analyst variability and errors, which in turn have the potential to significantly improve clinicians' ability to accurately assess and interpret stent position and integrity in real time. Cardiology analysts will be able to provide instant feedback to physicians, presenting the number and location of malapposed struts in 3D, empowering their decision making on the need for additional dilatation with a larger balloon or higher pressure, or whether patient needs to stay on anti-platelet regimen or be taken off in order to minimize bleeding risk. For purposes of research, clinical trials or stent design development, our software will improve reproducibility, increase accuracy, and harmonize analysis. In this follow on Phase II study, we will develop enhanced algorithms, optimize software usability, develop and test several user interfaces (UIs) in collaboration with the Core Lab at the University Hospitals. We will test and validate the functionality and performance of software using image data sets from multiple sources, increasing robustness of our approach. Phase II will enable us to develop a highly functional and usable software ready for commercial deployment. It will facilitate the use of our software in the clinic as part of an initial trial in the cath lab.
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