Agreement Between Artificial Intelligence and Anesthesiologists in Ultrasound-Guided Axillary Brachial Plexus Block

This prospective observational study aims to evaluate the agreement between artificial intelligence (AI)-assisted target point identification and experienced anesthesiologists during ultrasound-guided axillary brachial plexus block. Ultrasound guidance is widely used in regional anesthesia to improve block success and safety. However, accurate identification of anatomical structures and optimal injection points remains operator-dependent. Artificial intelligence-based systems have the potential to assist clinicians by identifying anatomical landmarks in real time. In this study, AI-generated target points will be compared with those determined by experienced anesthesiologists. The level of agreement between the two methods will be analyzed. Secondary outcomes will include block performance parameters and image quality. The findings of this study may contribute to understanding the clinical utility of AI in ultrasound-guided regional anesthesia.

NCT Number	NCT07532278
Lead Sponsor	Gaziantep City Hospital
Conditions	Ultrasound-Guided Nerve Block and Artificial Intelligence
Enrollment	100 participants
Start Date	2026-04-15
Primary Completion	2026-07-15 (estimated)
Study Completion	2026-07-15 (estimated)
Updated on ClinicalTrials.gov	2026-04-15