Shear wave elastography (SWE) is a non-invasive imaging technique used to quantify the elasticity/stiffness of any tissue. There are normative SWE studies on tonsils in healthy children in the literature. The purpose of this study is to analyze the palatine tonsils in children with acute tonsillitis using ultrasound and SWE. In this prospective study, pediatric patients aged 4–18 years diagnosed with acute tonsillitis and healthy children were included. Those with antibiotic use, chronic tonsillitis, adenoid hypertrophy, and having chronic disease, immunodeficiency, and autoimmune disease, or any rheumatological disease were excluded. The volume and elasticity of palatine tonsil were measured via ultrasound and SWE. The study included 81 (46 female, 35 male) acute tonsillitis patients, and 63 (38 female, 25 male) healthy children between the ages of 4 and 18. Elasticity (kPa) values of tonsils were found significantly higher in the tonsillitis group (SWE-R: 25.39 ± 4.64, SWE-L: 25.01 ± 4.17) compared to the normal group (SWE-R: 9.71 ± 2.37, SWE-L: 9.39 ± 2.19) (p < 0.001). In the tonsillitis group, a significant positive correlation was found between tonsil volume and elasticity (r: 0.774, p: 0.002). In conclusion, in pediatric patients with acute tonsillitis, higher kPa values were obtained with SWE in the palatine tonsils. Full article

Pediatric neck infections and their complications, such as abscesses extending to deep neck compartments, are potentially life-threatening acute conditions. Medical imaging aims to verify abscesses and their extensions and exclude other complications. Magnetic resonance imaging (MRI) has proven to be a useful and highly accurate imaging method in acute neck infections in children. Children and adults differ in terms of the types of acute infections and the anatomy and function of the neck. This pictorial review summarizes typical findings in pediatric patients with neck infections and discusses some difficulties related to image interpretation. Full article

This study aimed to systematically review the literature to synthesise and summarise the evidence surrounding the efficacy of artificial intelligence (AI) in classifying paediatric pneumonia on chest radiographs (CXRs). Following the initial search of studies that matched the pre-set criteria, their data were extracted using a data extraction tool, and the included studies were assessed via critical appraisal tools and risk of bias. Results were accumulated, and outcome measures analysed included sensitivity, specificity, accuracy, and area under the curve (AUC). Five studies met the inclusion criteria. The highest sensitivity was by an ensemble AI algorithm (96.3%). DenseNet201 obtained the highest level of specificity and accuracy (94%, 95%). The most outstanding AUC value was achieved by the VGG16 algorithm (96.2%). Some of the AI models achieved close to 100% diagnostic accuracy. To assess the efficacy of AI in a clinical setting, these AI models should be compared to that of radiologists. The included and evaluated AI algorithms showed promising results. These algorithms can potentially ease and speed up diagnosis once the studies are replicated and their performances are assessed in clinical settings, potentially saving millions of lives. Full article

Artificial intelligence (AI)-based computer-aided detection and diagnosis (CAD) is an important research area in radiology. However, only two narrative reviews about general uses of AI in pediatric radiology and AI-based CAD in pediatric chest imaging have been published yet. The purpose of this systematic review is to investigate the AI-based CAD applications in pediatric radiology, their diagnostic performances and methods for their performance evaluation. A literature search with the use of electronic databases was conducted on 11 January 2023. Twenty-three articles that met the selection criteria were included. This review shows that the AI-based CAD could be applied in pediatric brain, respiratory, musculoskeletal, urologic and cardiac imaging, and especially for pneumonia detection. Most of the studies (93.3%, 14/15; 77.8%, 14/18; 73.3%, 11/15; 80.0%, 8/10; 66.6%, 2/3; 84.2%, 16/19; 80.0%, 8/10) reported model performances of at least 0.83 (area under receiver operating characteristic curve), 0.84 (sensitivity), 0.80 (specificity), 0.89 (positive predictive value), 0.63 (negative predictive value), 0.87 (accuracy), and 0.82 (F1 score), respectively. However, a range of methodological weaknesses (especially a lack of model external validation) are found in the included studies. In the future, more AI-based CAD studies in pediatric radiology with robust methodology should be conducted for convincing clinical centers to adopt CAD and realizing its benefits in a wider context. Full article

Three-dimensional (3D) printing technology has become increasingly used in the medical field, with reports demonstrating its superior advantages in both educational and clinical value when compared with standard image visualizations or current diagnostic approaches. Patient-specific or personalized 3D printed models serve as a valuable tool in cardiovascular disease because of the difficulty associated with comprehending cardiovascular anatomy and pathology on 2D flat screens. Additionally, the added value of using 3D-printed models is especially apparent in congenital heart disease (CHD), due to its wide spectrum of anomalies and its complexity. This review provides an overview of 3D-printed models in pediatric CHD, with a focus on educational value for medical students or graduates, clinical applications such as pre-operative planning and simulation of congenital heart surgical procedures, and communication between physicians and patients/parents of patients and between colleagues in the diagnosis and treatment of CHD. Limitations and perspectives on future research directions for the application of 3D printing technology into pediatric cardiology practice are highlighted. Full article

Radiation dose optimization is particularly important in pediatric radiology, as children are more susceptible to potential harmful effects of ionizing radiation. However, only one narrative review about artificial intelligence (AI) for dose optimization in pediatric computed tomography (CT) has been published yet. The purpose of this systematic review is to answer the question “What are the AI techniques and architectures introduced in pediatric radiology for dose optimization, their specific application areas, and performances?” Literature search with use of electronic databases was conducted on 3 June 2022. Sixteen articles that met selection criteria were included. The included studies showed deep convolutional neural network (CNN) was the most common AI technique and architecture used for dose optimization in pediatric radiology. All but three included studies evaluated AI performance in dose optimization of abdomen, chest, head, neck, and pelvis CT; CT angiography; and dual-energy CT through deep learning image reconstruction. Most studies demonstrated that AI could reduce radiation dose by 36–70% without losing diagnostic information. Despite the dominance of commercially available AI models based on deep CNN with promising outcomes, homegrown models could provide comparable performances. Future exploration of AI value for dose optimization in pediatric radiology is necessary due to small sample sizes and narrow scopes (only three modalities, CT, positron emission tomography/magnetic resonance imaging and mobile radiography, and not all examination types covered) of existing studies. Full article

Children with congenital heart disease are exposed to repeated medical imaging throughout their lifetime. Although the imaging contributes to their care and treatment, exposure to ionising radiation is known to increase one’s lifetime attributable risk of malignancy. A systematic search of multiple databases was performed. Inclusion and exclusion criteria were applied to all relevant papers and seven were deemed acceptable for quality assessment and risk of bias assessment. The cumulative effective dose (CED) varied widely across the patient cohorts, ranging from 0.96 mSv to 53.5 mSv. However, it was evident across many of the included studies that a significant number of patients were exposed to a CED >20 mSv, the current annual occupational exposure limit. Many factors affected the dose which patients received, including age and clinical demographics. The imaging modality which contributed the most radiation dose to patients was cardiology interventional procedures. Paediatric patients with congenital heart disease are at an increased risk of receiving an elevated cumulative radiation dose across their lifetime. Further research should focus on identifying risk factors for receiving higher radiation doses, keeping track of doses, and dose optimisation where possible. Full article

The early diagnosis of biliary atresia (BA) in cholestatic infants is critical to the success of the treatment. Intraoperative cholangiography (IOC), an invasive imaging technique, is the current strategy for the diagnosis of BA. Ultrasonography has advanced over recent years and emerging techniques such as shear wave elastography (SWE) have the potential to improve BA diagnosis. This review sought to evaluate the diagnostic efficacy of advanced ultrasonography techniques in the diagnosis of BA. Six databases (CINAHL, Medline, PubMed, Google Scholar, Web of Science (core collection), and Embase) were searched for studies assessing the diagnostic performance of advanced ultrasonography techniques in differentiating BA from non-BA causes of infantile cholestasis. The meta-analysis was performed using Meta-DiSc 1.4 and Comprehensive Meta-analysis v3 software. Quality Assessment of Diagnostic Accuracy Studies tool version 2 (QUADAS-2) assessed the risk of bias. Fifteen studies consisting of 2185 patients (BA = 1105; non-BA = 1080) met the inclusion criteria. SWE was the only advanced ultrasonography technique reported and had a good pooled diagnostic performance (sensitivity = 83%; specificity = 77%; AUC = 0.896). Liver stiffness indicators were significantly higher in BA compared to non-BA patients (p < 0.000). SWE could be a useful tool in differentiating BA from non-BA causes of infantile cholestasis. Future studies to assess the utility of other advanced ultrasonography techniques are recommended. Full article

INTRODUCTION: The SARS-CoV-19 (COVID-19) pandemic has become a global problem but has affected the paediatric population less so than in adults. The clinical picture in paediatrics can be different to adults but nonetheless both groups have been subject to frequent imaging. The overall aim of this study was to comprehensively summarise the findings of the available literature describing the chest radiograph (CXR) findings of paediatric patients with confirmed COVID-19. The COVID-19 landscape is rapidly changing, new information is being constantly brought to light, it is therefore important to appraise clinicians and the wider scientific community on the radiographic features of COVID-19 in children. METHODS: Four databases, which included, PubMed; Medline; CINAHL; ScienceDirect were searched from the 30 November 2020 to the 5 March 2021. The review was conducted using the “Preferred Reporting Items for Systematic Reviews and Meta-Analysis, PRISMA” guidelines. Studies were included for (1) publications with full text available, (2) patients with confirmed COVID-19 diagnoses, (3) CXR imaging features of COVID-19 were reported, (4) the age of patients was 0–18 years, (5) studies were limited to human subjects and (6) a language restriction of English was placed on the search. Quality assessment of included articles used the National of Health Quality Assessment Tool for Case Series Studies. RESULTS: Eight studies met our criteria for inclusion in the review. All eight studies documented the number of CXRs obtained, along with the number of abnormal CXRs. Seven out of the eight studies noted greater than 50% of the CXRs taken were abnormal. Opacification was the number one feature that was recorded in all eight studies, followed by pleural effusion which was seen in six studies. Consolidation and peri-bronchial thickening features were both evident in four studies. Opacification was sub-divided into common types of opacities i.e., consolidation, ground glass opacities, interstitial, alveolar and hazy. Consolidation was reported in half of the studies followed by ground glass opacities and interstitial opacities which was seen in three out of the eight studies. CONCLUSION: This systematic review provides insight into the common COVID-19 features that are seen on CXRs in paediatric patients. Opacification was the most common feature reported, with consolidation, ground glass and interstitial opacities the top three opacifications seen. Peri-bronchial thickening is reported. in the paediatric population but this differs from the adult population and was not reported as a common radiographic finding typically seen in adults. ADVANCES IN KNOWLEDGE: This systematic review highlights the CXR appearances of paediatric patients with confirmed SARS-CoV-19, to gain insight into the disease pathophysiology and provide a comprehensive summary of the features for clinicians aiding optimal management. Full article

The practices for determining brain death are based on clinical criteria and vary immensely across countries. Cerebral angiography and perfusion scintigraphy are the most commonly used ancillary imaging tests for brain death confirmation in children; however, they both share similar shortcomings. Hence, contrast-enhanced ultrasound (CEUS) as a relatively inexpensive, easily accessible, and easy-to-perform technique has been proposed as an ancillary imaging test for brain death confirmation. CEUS has established itself as a favourable and widely used diagnostic imaging method in many different areas, but its application in delineating brain pathologies still necessities further validation. Herein, we present a case report of a 1-year-old polytraumatised patient in whom CEUS was applied as an ancillary imaging test for confirmation of brain death. As CEUS has not been validated as an ancillary test for brain death confirmation, the diagnosis was additionally confirmed with cerebral perfusion scintigraphy. Full article