Artificial intelligence (AI) for paediatric fracture detection: a multireader multicase (MRMC) study protocol.

Introduction: Paediatric fractures are common but can be easily missed on radiography leading to potentially serious implications including long-term pain, disability and missed opportunities for safeguarding in cases of inflicted injury. Artificial intelligence (AI) tools to assist fracture detection in adult patients exist, although their efficacy in children is less well known. This study aims to evaluate whether a commercially available AI tool (certified for paediatric use) improves healthcare professionals (HCPs) detection of fractures, and how this may impact patient care in a retrospective simulated study design.

Evaluating the impact of artificial intelligence-assisted image analysis on the diagnostic accuracy of front-line clinicians in detecting fractures on plain X-rays (FRACT-AI): protocol for a prospective observational study.

Introduction: Missed fractures are the most frequent diagnostic error attributed to clinicians in UK emergency departments and a significant cause of patient morbidity. Recently, advances in computer vision have led to artificial intelligence (AI)-enhanced model developments, which can support clinicians in the detection of fractures. Previous research has shown these models to have promising effects on diagnostic performance, but their impact on the diagnostic accuracy of clinicians in the National Health Service (NHS) setting has not yet been fully evaluated.

Multimodality detection of tumour rupture in children with Wilms tumour.

Background And Aims: Tumour rupture (TR) signifies stage III disease and requires treatment intensification, which includes radiotherapy. We studied the associations between radiological, surgical and pathology TR in children with Wilms tumour (WT) in a United Kingdom multicentre clinical study.

Patients And Methods: The IMPORT (Improving Population Outcomes for Renal Tumours of Childhood) study registered 712 patients between 2012 and 2021.

Fetal and neonatal post-mortem imaging referral template: recommendations from the European Society of Paediatric Radiology Post-mortem Task Force.

Background: In post-mortem (PM) fetal and neonatal imaging, relevant clinical information is crucial for accurate interpretation and diagnosis; however, it is usually incomplete.

Objective: To propose a standardized template for PM fetal and neonatal imaging referrals to enhance communication between referring clinicians and reporting radiologists.

Materials And Methods: A modified Delphi approach was conducted amongst members of the European Society of Paediatric Radiology (ESPR) PM Task Force and other recommended PM imaging specialists worldwide to determine consensus on necessary information.

"How I would like AI used for my imaging": children and young persons' perspectives.

Objectives: Artificial intelligence (AI) tools are becoming more available in modern healthcare, particularly in radiology, although less attention has been paid to applications for children and young people. In the development of these, it is critical their views are heard.

Materials And Methods: A national, online survey was publicised to UK schools, universities and charity partners encouraging any child or young adult to participate.

How to report perinatal and paediatric postmortem CT.

Postmortem CT (PMCT) has become increasingly accepted alongside skeletal surveys as a critical part of investigation in childhood deaths, either as part of a suite of non-invasive investigations through parental choice, or comprehensive evaluation in a forensic setting. Whilst CT image acquisition and protocols have been published and are relatively standardised, CT imaging reporting remains highly variable, largely dependent upon reporter experience and expertise. The main "risk" in PMCT is the over-interpretation of normal physiological changes on imaging as pathological, potentially leading to misdiagnosis or overdiagnosis of the disease.

Post-mortem skeletal survey (PMSS) versus post-mortem computed tomography (PMCT) for the detection of corner metaphyseal lesions (CML) in children.

Objectives: Corner metaphyseal lesions (CMLs) are specific for child abuse but challenging to detect on radiographs. The accuracy of CT for CML detection is unknown. Our aim was to compare diagnostic accuracy for CML detection on post-mortem skeletal surveys (PMSS, plain radiography) versus post-mortem CT (PMCT).

Postmortem imaging of fetuses at early gestations: A comparison of microfocus computed tomography with postmortem magnetic resonance at 9.4 T and postmortem ultrasound.

Objective: To compare the diagnostic performance of postmortem ultrasound (PMUS), 9.4 T magnetic resonance imaging (MRI) and microfocus computed tomography (micro-CT) for the examination of early gestation fetuses.

Method: Eight unselected fetuses (10-15 weeks gestational age) underwent at least 2 of the 3 listed imaging examinations.

Body weight-based iodinated contrast immersion timing for human fetal postmortem microfocus computed tomography.

Objectives: The aim of this study was to evaluate the length of time required to achieve full iodination using potassium tri-iodide as a contrast agent, prior to human fetal postmortem microfocus computed tomography (micro-CT) imaging.

Methods: Prospective assessment of optimal contrast iodination was conducted across 157 human fetuses (postmortem weight range 2-298 g; gestational age range 12-37 weeks), following micro-CT imaging. Simple linear regression was conducted to analyse which fetal demographic factors could produce the most accurate estimate for optimal iodination time.

Commercially available artificial intelligence tools for fracture detection: the evidence.

Missed fractures are a costly healthcare issue, not only negatively impacting patient lives, leading to potential long-term disability and time off work, but also responsible for high medicolegal disbursements that could otherwise be used to improve other healthcare services. When fractures are overlooked in children, they are particularly concerning as opportunities for safeguarding may be missed. Assistance from artificial intelligence (AI) in interpreting medical images may offer a possible solution for improving patient care, and several commercial AI tools are now available for radiology workflow implementation.

Pre- and post-COVID-19 gender trends in authorship for paediatric radiology articles worldwide: a systematic review.

Background: Gender inequalities in academic medicine persist despite progress over the past decade. Evidence-based targeted interventions are needed to reduce gender inequalities.

Objective: This systematic review aimed to investigate the impact of COVID-19 on gender trends in authorship of paediatric radiology research worldwide.

The unintended consequences of artificial intelligence in paediatric radiology.

Over the past decade, there has been a dramatic rise in the interest relating to the application of artificial intelligence (AI) in radiology. Originally only 'narrow' AI tasks were possible; however, with increasing availability of data, teamed with ease of access to powerful computer processing capabilities, we are becoming more able to generate complex and nuanced prediction models and elaborate solutions for healthcare. Nevertheless, these AI models are not without their failings, and sometimes the intended use for these solutions may not lead to predictable impacts for patients, society or those working within the healthcare profession.

Less-invasive autopsy for early pregnancy loss.

Autopsy investigations provide valuable information regarding fetal death that can assist in the parental bereavement process, and influence future pregnancies, but conventional autopsy is often declined by parents because of its invasive approach. This has led to the development of less-invasive autopsy investigations based on imaging technology to provide a more accessible and acceptable choice for parents when investigating their loss. Whilst the development and use of more conventional clinical imaging techniques (radiographs, CT, MRI, US) are well described in the literature for fetuses over 20 weeks of gestational age, these investigations have limited diagnostic accuracy in imaging smaller fetuses.

Academic Future of Interventional Radiology Subspecialty: Are We Giving Enough Space to Radiology Trainees?

Background: The aim of this study was to investigate willingness and barriers to academic activities of radiology trainees interested in interventional radiology subspecialty.

Materials And Methods: Radiology trainees and fellows were called to participate a 35-question survey via online platforms and radiological societies. The research survey investigated on involvement in academic activities, willingness of a future academic career, and challenges for pursuing an academic career.

Artificial Intelligence in Paediatric Tuberculosis.

Tuberculosis (TB) continues to be a leading cause of death in children despite global efforts focused on early diagnosis and interventions to limit the spread of the disease. This challenge has been made more complex in the context of the coronavirus pandemic, which has disrupted the "End TB Strategy" and framework set out by the World Health Organization (WHO). Since the inception of artificial intelligence (AI) more than 60 years ago, the interest in AI has risen and more recently we have seen the emergence of multiple real-world applications, many of which relate to medical imaging.

Can artificial intelligence pass the Fellowship of the Royal College of Radiologists examination? Multi-reader diagnostic accuracy study.

Objective: To determine whether an artificial intelligence candidate could pass the rapid (radiographic) reporting component of the Fellowship of the Royal College of Radiologists (FRCR) examination.

Design: Prospective multi-reader diagnostic accuracy study.

Setting: United Kingdom.

A novel magnetic resonance imaging scoring system for active and chronic changes in children and adolescents with juvenile idiopathic arthritis of the hip.

Background: Hip involvement predicts severe disease in juvenile idiopathic arthritis (JIA) and is accurately assessed by MRI. However, a child-specific hip MRI scoring system has not been validated.

Objective: To test the intra- and interobserver agreement of several MRI markers for active and chronic hip changes in children and young adults with JIA and to examine the precision of measurements commonly used for the assessment of growth abnormalities.

Current and future funding streams for paediatric postmortem imaging: European Society of Paediatric Radiology survey results.

Background: Perinatal and childhood postmortem imaging has been accepted as a noninvasive alternative or adjunct to autopsy. However, the variation in funding models from institution to institution is a major factor prohibiting uniform provision of this service.

Objective: To describe current funding models employed in European and non-European institutions offering paediatric postmortem imaging services and to discuss the perceived barriers to future postmortem imaging service provision.