RSIP Vision Presents New Technology for Noninvasive Planning of PCI

December 8, 2021—RSIP Vision, an Israel-based developer of medical imaging through advanced artificial intelligence (AI) and computer vision solutions, announced a coronary artery modeling technology intended to enable quick and accurate reconstruction of the coronary vasculature during angiography into a three-dimensional (3D) model for planning of percutaneous coronary intervention (PCI) procedures.

According to the company, the technology can be used for precise measurements of arterial length and diameter at any point, quantitative coronary angiography (QCA; including delineation of potential luminal obstructions), virtual stent positioning, and vessel modification for intervention planning. The vendor-neutral technology will be available to third-party C-arm manufacturers and medical device vendors.

The company noted that developing capabilities for additional interventions during PCI planning requires utilization of state-of-the-art deep learning (DL) algorithms combined with classic computer vision methods to create a 3D model of the coronary arteries accurately, rapidly, and automatically.

RSIP Vision’s model can be used to better visualize artery structure and measure vessel dimensions in points-of-interest. More advanced capabilities that are enabled using DL algorithms include stenosis detection, 3D QCA, and use as the baseline for computerized fractional flow reserve measurement. Additional modules can show anticipated postprocedural arterial modification/outcome because of stent placement or place a virtual stent in the desired position within the coronary artery.

“Preprocedural PCI planning and intraprocedural analysis, appraisal, and proper execution form the pillars of an uneventful invasive coronary intervention,” commented cardiac surgeon David Yakobi, MD, in the company’s press release. “Automated technologies that would allow better anatomical and pathological visualization and appreciation, as well as AI-based algorithms for coronary lesion characterization, will augment the procedural success, decrease the complication rate, and—based on a very broad scientific literature—have the potential of increasing stent patency rate and patients’ long-term survival.”

Dr. Yakobi added, “This module from RSIP Vision has the potential of becoming an automated, human error- and bias-free tool for classifying coronary artery disease based on the SYNTAX score and basically behaving as an independent ‘Heart Team’ for decision-making purposes between PCI and coronary artery bypass graft surgery.”