To the Editor:
We have been flattered by Bowness et al.’s  very supportive and positive feedback about our online published article very recently and we do congratulate their recent publication which seems to be quite similar to ours in many aspects. Clinical validation of the accuracy of a real-time sonoanatomy identification via artificial intelligence (AI)-supported ultrasound-guided peripheral nerve block practice has been also presented and evaluated recently via ScanNav Anatomy Peripheral Nerve Block (Intelligent Ultrasound, Cardiff). They evaluated the performance of an assisted AI to identify anatomical structure on ultrasound in seven body regions. Although we preferred to evaluate peripheral blocks that are commonly used in our regional anesthesia practice, Bowness et al.  investigated most of the peripheral and plane blocks (upper and lower extremity plus abdomen/trunk). Coincidentally, our study design/methodology is almost alike; particularly in terms of independent expert assessment for validation and scoring concept except adding an expert (or validator) other than an anesthesiologist that was criticized. The reason why we chose a radiologist for assessment was; we do respect the proficiency in the recognition of anatomic structures on ultrasound by a radiologist could be better than that of an anatomist. We thank you for asking a reply letter and sharing a very well-written preliminary evaluation paper on assistive AI system for recognition of anatomical structures on ultrasound-guided regional anesthesia with us.
Bowness J, Varsou O, Turbitt L, Burkett-St LD. Identifying anatomical structures on ultrasound: assistive artificial intelligence in ultrasound-guided regional anesthesia. Clin Anat. 2021;34(5):802–9. https://doi.org/10.1002/ca.23742 (Epub 2021 May 11. PMID: 33904628. Online ahead of print).
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Gunaydin, B., Gungor, I. & Inan, G. Accuracy study design: assistive AI, ultrasound-guided block. J Anesth 35, 603 (2021). https://doi.org/10.1007/s00540-021-02966-0