Artificial Intelligence Aided Ultrasound Detection of DDH: A Scoping Review Protocol

Abstract

Background: Ultrasound imaging plays a pivotal role in the diagnosis and monitoring of developmental dysplasia of the hip (DDH). However, this step requires a formal referral to the radiology department for an ultrasound by an expert radiologist or sonographer. This process can delay diagnosis and treatment initiation due to long wait times caused by the high demand on NHS services. In recent years, there has been a growing interest in leveraging artificial intelligence (AI) in ultrasound imaging. AI has potential to assist in image acquisition and interpretation, to inform clinical decision-making. Further benefits may include improved accuracy, efficiency, and consistency in diagnosis, ultimately leading to better patient outcomes. This scoping review aims to review the evidence for AI to support ultrasound detection of DDH, including reviewing the methodologies employed, the accuracy and utility of algorithms, challenges and opportunities for clinical translation, and requirements for future research. Methods: We will conduct a comprehensive search of the literature using multiple databases, including ACM Digital Library, EMBASE, OVID MEDLINE, PUBMED, COCHRANE Library, CINAHL, and IEEE Explore. These databases cover a wide range of academic disciplines, including computer science, and medical sciences, ensuring thorough coverage of relevant studies related to artificial intelligence (AI) in ultrasound for developmental dysplasia of the hip (DDH). In addition, we will explore the International Committee of Medical Journal Editors (ICMJE) approved clinical trial registries and the World Health Organization (WHO) clinical trials registry to identify ongoing or completed studies in this field. This will capture relevant research that may not yet be published in peer-reviewed journals. To supplement the research databases, we will search the websites of international societies in relevant fields, such as the British Society of Children's Orthopaedic Surgery (BSCOS) and Paediatric Orthopaedic Society of North America (POSNA). As AI has a strong commercial interest, we will review product information and publicly available evidence from EXO Imaging (https://www.exo.inc), a commercial company with a known interest in this field and an established AI aided US device. Discussion: This scoping review represents the first comprehensive attempt to gather the available evidence on the application of AI in ultrasound imaging for the diagnosis of DDH. By systematically reviewing and synthesizing a diverse range of studies, we aim to provide an overview of the current state of the art in this emerging field, identify gaps in the literature, and inform future research.