Title : The utility of AI in ultrasound guided regional anesthesia
Abstract:
Regional anesthesia (RA) is increasingly used in anesthesia practice. Ultrasound has been used to facilitate the performance of the regional blocks. The use of ultrasound for nerve localization increases success and reduces complication rate.
Ultrasound technology has increasingly gained popularity among practitioners due to its portability, and the ability to track the performance of the procedure in real-time. Other benefits of Ultrasound use in regional anesthesia include direct visualization of nerves, blood vessels, muscles, bones, tendons and the local anesthetic spread during injection and as such minimizes the rate of possible complications like inadvertent intravascular injections and unintended intraneuronal injection of local anesthetics.
The use of ultrasound technology in regional Anesthesia like other image guided procedures is challenging. It is associated with several technical difficulties, which are especially prevalent in trainees and less experienced proceduralists. The performance of a block can then be complicated with loss of coordination between hand, needle and probe. Performance also requires intense mental work in terms of real time image interpretation and to guide the needle under ultrasound guidance towards the intended target.
Artificial intelligence (AI) is a field of computer science which uses techniques that enable computers to undertake tasks associated with human intelligence. AI solutions might be useful for practitioners in anatomical landmark identification and, reducing or avoiding possible complications such as injury to the nerve, artery, vein, and other vital structures, as well as local anesthetic systemic toxicity. AI-guided solutions can improve the optimization and interpretation of the sonographic image, visualization of needle advancement and injection of local anesthetic. The big question is what is the evidence supporting the use of artificial intelligence for ultrasound scanning in regional anesthesia? and whether it improves performance and subsequently translate into favorable patient’s outcomes. Training skills pertinent to ultrasound guided regional anesthesia is another area that AI may prove helpful however its utility and limitation should be carefully evaluated before a conclusion could ever be drawn.
