Wrist trauma is common in children and generally requires radiography for diagnosis. Many children who receive radiographs do not have fractures and are thus subjected to unnecessary radiation exposure along with increased wait times in the emergency department (ED). Ultrasound (US) is safe, cost-effective, portable and sensitive in visualizing cortical disruption, potentially making it a valuable tool for bedside assessment of fractures. This study aims to determine the feasibility of using US to detect distal radius fractures (DRF) in children and to contrast the accuracy of hand-held device compatible 2D transducers to 3D transducers that can only be used with traditional US machines. In order to address difficulties in US image interpretation by inexperienced users, we investigated the utility of an artificial intelligence (AI) network. Read More

Meeting name: SPR 2023 Annual Meeting & Postgraduate Course , 2023

Authors: Knight Jessica, Jaremko Jacob, Zhou Yuyue, Keen Christopher, Rakkundedeth Abhilash, Ghasseminia Siyavash, Wichuk Stephanie, Brilz Alan, Alves Pereira Fatima, Kirschner David

Keywords: Artificial Intelligence, Ultrasound, Musculoskeletal