Key result
AI shows potential to transform ultrasound for regional anesthesia by improving imaging and automating needle guidance.
Why the study?
Ultrasound accuracy for regional anesthesia and pain management highly depends on operator skill, and AI incorporation has transformed image interpretation.
The incorporation of Artificial Intelligence (AI) into ultrasound modality has the potential to transform regional anesthesia and pain management by upgrading image explication and reducing operator dependence.
AI-enhanced ultrasound may aid image interpretation in regional anesthesia; leaves open need for outcome trials before adoption.
Ultrasound is a well-recognized tool for regional anesthesia and tailored pain management. It offers real-time imaging of patient’s anatomy and provides guideline for needle insertion with precision. Though, its accuracy highly relies on operator’s skill and experience. The incorporation of Artificial Intelligence (AI) into ultrasound modality has transformed the field by upgrading the explication of images including tumor detection, segmentation and classification by inculcating the Convolution Neural Networks (CNNs) which is a type of deep learning.
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Qurba Kiran (2025) conducted an editorial in Regional anesthesia and pain management. Artificial Intelligence (AI) in ultrasonography was evaluated. Artificial intelligence has the potential to transform ultrasonography for regional anesthesia and pain management by improving image interpretation, automating needle guidance, and increasing workflow efficiency.
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