Cydar EV

Cydar EV is a cloud-based Software-as-a-Service solution that provides image guidance for endovascular procedures by overlaying pre-operative 3D CT-derived vascular anatomy onto live 2D fluoroscopic images. The system's science relies on automated 2D-3D registration via machine vision tracking of vertebral anatomy to enhance surgical navigation and device positioning.

Cydar EV is a Software-as-a-Service (SaaS) product designed to enhance X-ray guided surgical procedures by providing augmented reality images. The system's methodology involves running specialized software on Cydar’s cloud servers, which processes data from client machines equipped with a video framegrabber to capture live fluoroscopy video. Its core function is to overlay preoperative 3D vessel anatomy, derived from previously acquired contrast-enhanced CT scans, onto the live 2D fluoroscopic images. This image fusion is achieved through a 2D-3D registration process that utilizes machine vision for automated tracking of vertebral anatomy, allowing for dynamic updates in response to C-arm, table, and patient movements. The intended purpose of Cydar EV is to assist clinicians in accurately positioning guidewires, catheters, and other endovascular devices during fluoroscopy-guided procedures in the lower thorax, abdomen, and pelvis. Suitable applications include endovascular aortic aneurysm repair (AAA and mid-distal TAA), angioplasty, stenting, and embolization in specified iliac arteries and veins, though it is not intended for procedures involving the liver, kidneys, or pelvic organs. Non-clinical performance testing validated the system's compliance with software and usability standards, focusing on registration accuracy and overlay alignment. A multi-centre observational clinical study assessed endpoints such as accuracy, robustness, usability, procedure time, radiation exposure, and iodinated contrast volume, concluding that Cydar EV provides safe, effective, and usable image guidance for its specified indications.

AI Regulatory Concerns

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Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

• Q1. How does the system's performance in 2D-3D registration accuracy, specifically using vertebral anatomy tracking, vary with patient anatomical variations (e.g., obesity, scoliosis) or challenging intraoperative imaging conditions?; What are the specific quantitative reductions in procedure time, radiation exposure, and iodinated contrast volume observed in the clinical study when using Cydar EV compared to procedures without this image guidance?; What are the documented failure rates or limitations of the machine vision tracking of vertebral anatomy, and what are the system's protocols or manual override options if automated registration is suboptimal or fails?; How is the latency associated with the cloud-based processing and data transfer managed to ensure real-time overlay accuracy and responsiveness critical for endovascular device manipulation?; Given its current exclusion, what specific technological advancements or validation studies would be necessary to potentially expand Cydar EV's indications for use to X-ray guided procedures in mobile organs like the liver, kidneys, or other pelvic organs?