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. Children with TR on central radiology review (CRR) at diagnosis and/or indication of preoperative TR on surgical forms were included. Correlation between radiology/surgery/pathology findings was made. RESULTS: Total 141 patients had TR identified (69 on CRR, 43 on surgical form and 29 on both), and 124/141 had images available for CRR, and 98/124 had features suggestive of TR on diagnostic CRR (63 magnetic resonance imaging/35 computed tomography). TR was limited to the renal fossa in 47/98 (48%) and intraperitoneal in 51/98 (52%). Three of 98(3%) had upfront surgery, and 87/95 (92%) had TR confirmed on post-chemotherapy preoperative scans. Among 80/98 (82%) cases with TR on CRR and available surgical forms, TR was not confirmed on surgery or pathology in 38/80, giving a false-positive rate of 48%. Preoperative TR was indicated on 72 surgical forms, with images available for CRR in 55. Twenty-six of 55 (47%) were false-negative for TR on CRR and of those 10/26 (38%) had TR confirmed on pathology. CONCLUSIONS: Radiology alone should not be used to define TR, as it does not accurately correlate with surgical or pathology findings, and therefore cannot be relied upon for definitive staging and treatment. A multidisciplinary team should take the decision regarding the final abdominal stage and treatment using a multimodality approach considering clinical, radiological, surgical and pathological findings.

The incidence of fractures in children under two years of age: a systematic review.

BACKGROUND: Epidemiological research on fractures in children under the age of two is of great importance to help understand differences between accidental and abusive trauma. OBJECTIVE: This systematic review aimed to evaluate studies reporting on the incidence of fractures in children under two years of age, excluding birth injuries. Secondary outcome measures included fracture location, mechanisms of injury and fracture characteristics. METHODS: A systematic literature review (1946 to February 7th 2024), including prospective and retrospective cohort studies and cross-sectional cohort studies, was performed. Studies including children from other age groups were included if the actual measures for those aged 0-2 years could be extracted. We also included studies restricted to infants. Annual incidence rates of fractures were extracted and reported as the main result. Critical appraisal of was performed using the Appraisal tool for Cross-Sectional Studies. RESULTS: Twelve moderate to good quality studies met eligibility criteria, of which seven were based on data from medical records and five were registry studies. Studies investigated different aspects of fractures, making comprehensive synthesis challenging. There was an overall annual fracture incidence rate of 5.3 to 9.5 per 1,000 children from 0-2 years of age; with commonest sites being the radius/ulna (25.2-40.0%), followed by tibia/fibula (17.3-27.6%) and the clavicle (14.6-14.8%) (location based on 3 studies with a total of 407 patients). In infants, the reported incidence ranged between 0.7 to 4.6 per 1,000 (based on 3 studies), with involvement of the clavicle in 22.2% and the distal humerus in 22.2% of cases (based on 1 study). Only a single metaphyseal lesion was reported (proximal humerus of an 11-month-old infant). Fracture mechanisms were detailed in four studies, with fall from chair, bed, table, own height or fall following indoor activities causing 50-60% of fractures. CONCLUSIONS: There is a paucity of good quality data on fracture incidence in children under the age of two. Larger, prospective and unbiased studies would be helpful in determining normal pattern of injuries, so that differences from abusive trauma may be better understood.

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. In this article, we present a pragmatic standardised reporting framework, developed over a decade of PMCT reporting in children in our institution, with examples of positive and negative findings, so that it may aid in the interpretation of PMCT images with those less experienced in paediatric findings and postmortem imaging. CRITICAL RELEVANCE STATEMENT: Standardised reporting using a common framework with a sound understanding of normal postmortem changes that occur in children are crucial in avoiding common reporting errors at postmortem CT. KEY POINTS: Familiarity with postmortem imaging is required for useful image reporting, and reporting standards vary. Understanding normal postmortem change from significant abnormalities requires training and experience. Following a template may remind reporters what to include and help improve performance.

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. Six fetuses underwent 9.4 T MRI, four underwent micro-CT and six underwent PMUS. All operators were blinded to clinical history. All imaging was reported according to a prespecified template assessing 36 anatomical structures, later grouped into five regions: brain, thorax, heart, abdomen and genito-urinary. RESULTS: More anatomical structures were seen on 9.4 T MRI and micro-CT than with PMUS, with a combined frequency of identified structures of 91.9% and 69.7% versus 54.5% and 59.6 (p < 0.001; p < 0.05) respectively according to comparison groups. In comparison with 9.4 T MRI, more structures were seen on micro-CT (90.2% vs. 83.3%, p < 0.05). Anatomical structures were described as abnormal on PMUS in 2.7%, 9.4 T MRI in 6.1% and micro-CT 7.7% of all structures observed. However, the accuracy test could not be calculated because conventional autopsy was performed on 6 fetuses of that only one structure was abnormal. CONCLUSION: Micro-CT appears to offer the greatest potential as an imaging adjunct or non-invasive alternative for conventional autopsies in early gestation fetuses.

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. However, information regarding their development, evidence for performance and validation as well as the intended target population is not always clear, but vital when evaluating a potential AI solution for implementation. In this article, we review the range of available products utilizing AI for fracture detection (in both adults and children) and summarize the evidence, or lack thereof, behind their performance. This will allow others to make better informed decisions when deciding which product to procure for their specific clinical requirements.

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. Results: Postmortem body weight (r2 = 0.6435) was better correlated with iodination time than gestational age (r2 = 0.1384), producing a line of best fit, y = [0.0304 × body weight (g)] - 2.2103. This can be simplified for clinical use whereby immersion time (days) = [0.03 × body weight (g)] - 2.2. Using this formula, for example, a 100-g fetus would take 5.2 days to reach optimal contrast enhancement. Conclusions: The simplified equation can now be used to provide estimation times for fetal contrast preparation time prior to micro-CT imaging and can be used to manage service throughput and parental expectation for return of their fetus. Advances in knowledge: A simple equation from empirical data can now be used to estimate preparation time for human fetal postmortem micro-CT imaging.

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. In this article, we provide an overview of the latest opinions regarding AI ethics, bias, limitations, challenges and considerations that we should all contemplate in this exciting and expanding field, with a special attention to how this applies to the unique aspects of a paediatric population. By embracing AI technology and fostering a multidisciplinary approach, it is hoped that we can harness the power AI brings whilst minimising harm and ensuring a beneficial impact on radiology practice.

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. Techniques such as ultra-high-field MRI (>3T) and micro-focus computed tomography have been shown to have higher diagnostic accuracy whilst still being acceptable to parents. By further developing and increasing the availability of these more innovative imaging techniques, parents will be provided with a greater choice of acceptable options to investigate their loss, which may in turn increase their uptake. We provide a narrative review focussing on the development of high-resolution, non-invasive imaging techniques to evaluate early gestational pregnancy loss.

Artificial intelligence applied to fetal MRI: A scoping review of current research.

Artificial intelligence (AI) is defined as the development of computer systems to perform tasks normally requiring human intelligence. A subset of AI, known as machine learning (ML), takes this further by drawing inferences from patterns in data to 'learn' and 'adapt' without explicit instructions meaning that computer systems can 'evolve' and hopefully improve without necessarily requiring external human influences. The potential for this novel technology has resulted in great interest from the medical community regarding how it can be applied in healthcare. Within radiology, the focus has mostly been for applications in oncological imaging, although new roles in other subspecialty fields are slowly emerging.In this scoping review, we performed a literature search of the current state-of-the-art and emerging trends for the use of artificial intelligence as applied to fetal magnetic resonance imaging (MRI). Our search yielded several publications covering AI tools for anatomical organ segmentation, improved imaging sequences and aiding in diagnostic applications such as automated biometric fetal measurements and the detection of congenital and acquired abnormalities. We highlight our own perceived gaps in this literature and suggest future avenues for further research. It is our hope that the information presented highlights the varied ways and potential that novel digital technology could make an impact to future clinical practice with regards to fetal MRI.

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. MATERIALS AND METHODS: A web-based 16-question survey was distributed to members of the European Society of Paediatric Radiology (ESPR) and ESPR postmortem imaging task force over a 6-month period (March-August 2021). Survey questions related to the radiologic and autopsy services being offered and how each was funded within the respondent's institute. RESULTS: Eighteen individual responses were received (13/18, 72.2% from Europe). Only one-third of the institutions (6/18, 33.3%) have fully funded postmortem imaging services, with the remainder receiving partial (6/18, 33.3%) or no funding (5/18, 27.8%). Funding (full or partial) was more commonly available for forensic work (13/18, 72%), particularly where this was nationally provided. Where funding was not provided, the imaging and reporting costs were absorbed by the institute. CONCLUSION: Increased access is required for the expansion of postmortem imaging into routine clinical use. This can only be achieved with formal funding on a national level, potentially through health care commissioning and acknowledgement by health care policy makers and pathology services of the value the service provides following the death of a fetus or child. Funding should include the costs involved in training, equipment, reporting and image acquisition.

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. MATERIALS AND METHODS: Hip MRIs from 60 consecutive children, adolescents and young adults with JIA were scored independently by two sets of radiologists. One set scored the same MRIs twice. Features of active and chronic changes, growth abnormalities and secondary post-inflammatory changes were scored. We used kappa statistics to analyze inter- and intraobserver agreement for categorical variables and a Bland-Altman approach to test the precision of continuous variables. RESULTS: Among active changes, there was good intra- and interobserver agreement for grading overall inflammation (kappa 0.6-0.7). Synovial enhancement showed a good intraobserver agreement (kappa 0.7-0.8), while the interobserver agreement was moderate (kappa 0.4-0.5). Regarding acetabular erosions on a 0-3 scale, the intraobserver agreement was 0.6 for the right hip and 0.7 for the left hip, while the interobserver agreement was 0.6 for both hips. Measurements of joint space width, caput-collum-diaphyseal angle, femoral neck-head length, femoral width and trochanteric distance were imprecise. CONCLUSION: We identified a set of MRI markers for active and chronic changes in JIA and suggest that the more robust markers be included in future studies addressing clinical validity and long-term patient outcomes.

European Society of Paediatric Radiology Artificial Intelligence taskforce: a new taskforce for the digital age.

A new task force dedicated to artificial intelligence (AI) with respect to paediatric radiology was created in 2021 at the International Paediatric Radiology (IPR) meeting in Rome, Italy (a joint society meeting by the European Society of Pediatric Radiology [ESPR] and the Society for Pediatric Radiology [SPR]). The concept of a separate task force dedicated to AI was borne from an ESPR-led international survey of health care professionals' opinions, expectations and concerns regarding AI integration within children's imaging departments. In this survey, the majority (> 80%) of ESPR respondents supported the creation of a task force and helped define our key objectives. These include providing educational content about AI relevant for paediatric radiologists, brainstorming ideas for future projects and collaborating on AI-related studies with respect to collating data sets, de-identifying images and engaging in multi-case, multi-reader studies. This manuscript outlines the starting point of the ESPR AI task force and where we wish to go.

Post-mortem perinatal imaging: what is the evidence?

Post-mortem imaging for the investigation of perinatal deaths is an acceptable tool amongst parents and religious groups, enabling a less invasive autopsy examination. Nevertheless, availability is scarce nationwide, and there is some debate amongst radiologists regarding the best practice and optimal protocols for performing such studies. Much of the published literature to date focusses on single centre experiences or interesting case reports. Diagnostic accuracy studies are available for a variety of individual imaging modalities (e.g. post-mortem CT, MRI, ultrasound and micro-CT), however, assimilating this information is important when attempting to start a local service.In this article, we present a comprehensive review summarising the latest research, recently published international guidelines, and describe which imaging modalities are best suited for specific indications. When the antenatal clinical findings are not supported by the post-mortem imaging, we also suggest how and when an invasive autopsy may be considered. In general, a collaborative working relationship within a multidisciplinary team (consisting of radiologists, radiographers, the local pathology department, mortuary staff, foetal medicine specialists, obstetricians and bereavement midwives) is vital for a successful service.

Presentation to publication: Changes in paediatric radiology research trends 2010-2016.

BACKGROUND: More than half of paediatric radiology research presented at annual conference meetings between 2010-2012 remains unpublished. It is unclear if there are any improvements in this statistic despite some initiatives to improve awareness of the importance of evidence-based medicine. OBJECTIVES: To determine the abstract to publication rates (APRs) originating from recent paediatric radiology meetings, trends in research topics and factors associated with publication success. MATERIALS AND METHODS: All PubMed cited articles originating from oral presentations at European Society of Paediatric Radiology, Society for Paediatric Radiology or International Paediatric Radiology conferences between 2013-2016 were evaluated, and compared to those from previously published data from the same conferences dated 2010-2012. Publication rates, study design and topic as well as characteristics of the research group (e.g., author affiliations and number) were evaluated and compared between published and unpublished groups. RESULTS: The APR increased to 433/937 (46%) for abstracts presented between 2013-2016, compared to 300/715 (42%) in 2010-2012 (P=0.094). The largest proportion of publications comes from academic and tertiary centres (324/433 [75%]). International collaboration increased to 49/433 (11%) from 18/300 (6%) in 2010-2012 (P=0.018). A greater proportion of work was published within 12 months of conference: 41% in 2013-2016, compared to 29% in 2010-2012 (P=0.02). Paediatric Radiology remained the most popular destination journal, publishing 167/433 (39%) articles. CONCLUSION: There was a slight increase over time in the proportion of abstracts that resulted in publication, yet more than half of abstracts still do not reach publication status. Further work should identify how radiologists (particularly those outside tertiary and academic centres) can be supported to share their research.

Artificial intelligence for radiological paediatric fracture assessment: a systematic review.

BACKGROUND: Majority of research and commercial efforts have focussed on use of artificial intelligence (AI) for fracture detection in adults, despite the greater long-term clinical and medicolegal implications of missed fractures in children. The objective of this study was to assess the available literature regarding diagnostic performance of AI tools for paediatric fracture assessment on imaging, and where available, how this compares with the performance of human readers. MATERIALS AND METHODS: MEDLINE, Embase and Cochrane Library databases were queried for studies published between 1 January 2011 and 2021 using terms related to 'fracture', 'artificial intelligence', 'imaging' and 'children'. Risk of bias was assessed using a modified QUADAS-2 tool. Descriptive statistics for diagnostic accuracies were collated. RESULTS: Nine eligible articles from 362 publications were included, with most (8/9) evaluating fracture detection on radiographs, with the elbow being the most common body part. Nearly all articles used data derived from a single institution, and used deep learning methodology with only a few (2/9) performing external validation. Accuracy rates generated by AI ranged from 88.8 to 97.9%. In two of the three articles where AI performance was compared to human readers, sensitivity rates for AI were marginally higher, but this was not statistically significant. CONCLUSIONS: Wide heterogeneity in the literature with limited information on algorithm performance on external datasets makes it difficult to understand how such tools may generalise to a wider paediatric population. Further research using a multicentric dataset with real-world evaluation would help to better understand the impact of these tools.

Abdominal US in Pediatric Inflammatory Multisystem Syndrome Associated with SARS-CoV-2 (PIMS-TS).

Background Children with pediatric inflammatory syndrome temporally associated with SARS-CoV-2 (PIMS-TS), also known as multisystem inflammatory syndrome in children, present with abdominal pain among other nonspecific symptoms. Although initial imaging features of PIMS-TS have been reported, the duration of sonographic features remains unknown. Purpose To describe the abdominal US features of PIMS-TS at initial presentation and follow-up. Materials and Methods A retrospective review of children and young adults presenting with clinical features suspicious for PIMS-TS between April 2020 and June 2021 was carried out. US features were documented and reviewed at initial presentation and follow-up. Descriptive statistics were used and interobserver variability was calculated. Results Of 140 children and young adults presenting with suspected PIMS-TS, 120 had confirmed PIMS-TS (median age, 9 years; interquartile range, 7-12 years; 65 male patients) and 102 underwent abdominal US at presentation. PIMS-TS was present as a single abnormality in 109 of the 120 patients (91%) and abdominal symptoms were present in 104 of the 109 (95%). US examinations were abnormal in 86 of 102 patients (84%), with ascites being the most common abnormality in 65 (64%; 95% CI: 54, 73). Bowel wall thickening was present at US in 14 of the 102 patients (14%; 95% CI: 7, 20) and mesenteric inflammation was present in 16 (16%; 95% CI: 9, 23); all of these patients presented with abdominal symptoms. Among the patients with bowel wall thickening, the distal and terminal ileum were most involved (eight of 14 patients, 57%). Abdominal symptoms decreased to seven of 56 patients (13%) in those followed up at 6 months. Thirty-eight patients underwent follow-up US, and the presence of bowel inflammation had decreased to three of 27 patients (11%; 95% CI: -1, 23) in those followed up for less than 2 months and 0 of 17 (0%) in those followed up for more than 2 months. Conclusion Of 102 patients with pediatric inflammatory multisystem syndrome temporally associated with SARS-CoV-2 who underwent US at presentation, 14 (14%) had abdominal US findings of bowel inflammation and 16 (16%) had mesenteric edema. All US abnormalities resolved after 2 months. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by van Rijn and Pajkrt in this issue.

Artificial intelligence in paediatric radiology: international survey of health care professionals' opinions.

BACKGROUND: The nature of paediatric radiology work poses several challenges for developing and implementing artificial intelligence (AI) tools, but opinions of those working in the field are currently unknown. OBJECTIVE: To evaluate the attitudes and perceptions toward AI amongst health care professionals working within children's imaging services. MATERIALS AND METHODS: A web-based questionnaire was distributed to the membership of several paediatric and general radiological societies over a 4-month period (1 Feb - 31 May 2020). Survey questions covered attitudes toward AI in general, future impacts and suggested areas for development specifically within paediatric imaging. RESULTS: Two hundred and forty responses were collected with the majority being from radiologists (159/240, 66.3%; 95% confidence interval [CI] 59.8-72.2%) or allied health care professionals (72/240, 31.3%; 95% CI 25.4-37.5%). Respondents agreed that AI could potentially alert radiologists to imaging abnormalities (148/240, 61.7%; 95% CI 55.2-67.9%) but preferred that results were checked by a human (200/240, 83.3%; 95% CI 78.0-87.8%). The majority did not believe jobs in paediatric radiology would be replaced by AI (205/240, 85.4%; 95% CI 80.3-89.6%) and that the development of AI tools should focus on improved diagnostic accuracy (77/240, 32.1%; 95% CI 26.2-38.4%), workflow efficiencies (60/240, 25.0%; 95% CI 19.7-30.9%) and patient safety (54/240, 22.5%; 95% CI 17.4-28.3%). The majority of European Society of Paediatric Radiology (ESPR) members (67/81, 82.7%; 95% CI 72.7-90.2%) welcomed the idea of a dedicated paediatric radiology AI task force with emphasis on educational events and anonymised dataset curation. CONCLUSION: Imaging health care professionals working with children had a positive outlook regarding the use of AI in paediatric radiology, and did not feel their jobs were threatened. Future AI tools would be most beneficial for easily automated tasks and most practitioners welcomed the opportunity for further AI educational activities.