Inadvertent puncture of an unintended object in a vascular access procedure is common and can lead to serious consequences. Inadvertent common carotid artery (CCA) puncture while targeting the internal jugular vein (IJV), for example, is reported to have an incidence of 2% - 8% and usually results in localized hematoma formation. The hematoma may enlarge rapidly if the patient is coagulopathic, or if a large puncture wound is produced by the introduction of the sheath itself into the CCA. Airway obstruction, pseudoaneurysm, arterio-venous fistula formation and retrograde aortic dissection have all been reported as a consequence of CCA puncture. In the presence of occlusive (atheromatous) carotid disease, inadvertent puncture may carry the risk of precipitating a cerebrovascular accident.

In this study, we aim to collect color Doppler and B-mode ultrasound videos from the most common ultrasound-guided vascular access sites - internal jugular vein, subclavian vein, femoral vein, basilic vein, and brachial vein. The videos will also include structures in close proximity to the intended veins. Using such database, we will run various vessel tracking and identification algorithms to evaluate their performance. Our ultimate goal is to develop an algorithm that will aid the ultrasound operator in identifying structures and differentiating between arteries and veins.