Artificial Intelligence in Regional Anesthesia and Pain Management - 01/08/25

Doi : 10.1016/j.anclin.2025.05.004

Heitor J.S. Medeiros, MD ^a,^⁎ , Ali Dabbagh, MD ^b, Kamen Vlassakov, MD ^c, A. Sassan Sabouri, MD ^a
^a Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, USA
^b Cardiac Anesthesiology Department, School of Medicine, Anesthesiology Research Center, Shahid Modarres Hospital, Shahid Beheshti University of Medical Sciences, Modarres Hospital Sa'adat Abad, Tehran 1998734383, Iran
^c Division of Regional and Orthopedic Anesthesiology, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women’s Hospital, Boston, USA

^∗Corresponding author. Massachusetts General Hospital, Department of Anesthesia, Critical Care and Pain Medicine, 55 Fruit Street, Boston, MA 02114.Massachusetts General HospitalDepartment of AnesthesiaCritical Care and Pain Medicine55 Fruit StreetBostonMA02114

Résumé

Artificial intelligence (AI) is improving regional anesthesia by bringing unparalleled precision and efficiency to ultrasound-guided procedures. Using advanced machine learning algorithms like convolutional neural networks, AI can instantly interpret ultrasound images, accurately identifying nerves, blood vessels, and other critical anatomic structures. This real-time analysis dramatically shortens the learning curve for anesthesiologists, enhancing needle placement accuracy and reducing procedural errors. In labor anesthesia, AI-powered systems such as the spinal level identification device have demonstrated superior accuracy in locating spinal interspaces, especially in patients with high body mass index.

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Keywords : Artificial intelligence, Regional anesthesia, Machine learning, Ultrasound, Pain management, Predictive analytics, Education, Automation