Guidance for reporting artificial intelligence technology evaluations for ultrasound scanning in regional anaesthesia (GRAITE-USRA): an international multidisciplinary consensus reporting framework
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Zhang,Xiaoxi;Ferry,Jenny;Hewson,David W.;Collins,Gary S.;Wiles,Matthew D.;Zhao,Yi;Martindale,Alexander P. L.;Tomaschek,Michael;Bowness,James S.;GRAITE†USRA Working Group
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2025
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INTRODUCTION: The application of artificial intelligence to enhance the clinical practice of ultrasound-guided regional anaesthesia is of increasing interest to clinicians, researchers and industry. The lack of standardised reporting for studies in this field hinders the comparability, reproducibility and integration of findings. We aimed to develop a consensus-based reporting guideline for research evaluating artificial intelligence applications for ultrasound scanning in regional anaesthesia. METHODS: We followed methodology recommended by the EQUATOR Network for the development of reporting guidelines. Review of published literature and expert consultation generated a preliminary list of candidate reporting items. An international, multidisciplinary, modified Delphi process was then undertaken, involving experts from clinical practice, academia and industry. Two rounds of expert consultation were conducted, in which participants evaluated each item for inclusion in a final reporting guideline, followed by an online discussion. RESULTS: A total of 67 experts participated in the first Delphi round, 63 in the second round and 25 in the roundtable consensus meeting. The GRAITE-USRA reporting guideline comprises 40 items addressing key aspects of reporting in artificial intelligence research for ultrasound scanning in regional anaesthesia. Specific items include ultrasound acquisition protocols and operator expertise, which are not covered in existing artificial intelligence reporting guidelines. DISCUSSION: The GRAITE-USRA reporting guideline provides a minimum set of recommendations for artificial intelligence-related research for ultrasound scanning in regional anaesthesia. Its adoption will promote consistent reporting standards, enhance transparency, improve study reproducibility and ultimately support the effective integration of evidence into clinical practice.; Doctors, scientists and companies are becoming more interested in using artificial intelligence (AI) to help with a type of pain†blocking treatment called ultrasound†guided regional anaesthesia. But it is hard to compare studies about this because they are not all written in the same way. Our goal was to create a clear list of rules for how to write these kinds of studies so that everyone can understand and trust the results. We followed expert advice on how to make good rules for research reporting. First, we looked at past research and talked to experts to come up with a list of things that should be included in these studies. Then, we asked a group of experts from different countries and jobs (like doctors, scientists and people from companies) what they thought. They shared their opinions in two rounds of surveys and one online group discussion. In the first round, 67 experts gave feedback. In the second round, 63 experts joined. Then, 25 experts came together for a group meeting. In the end, we created the GRAITE†USRA guideline. It has 40 important points that researchers should include when writing about AI for ultrasound in regional anaesthesia. Some of these points, like how the ultrasound images are taken and how skilled the person using the machine is, are not covered in other guidelines. The GRAITE†USRA guideline gives clear and simple rules to help people write better research about using AI in ultrasound for pain†blocking treatments. If everyone follows these rules, it will be easier to understand, trust and use the results in real medical care.
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Anaesthesia