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.

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). METHODS: A 10-year retrospective review was performed at a children's hospital for patients having PMSS, PMCT and histopathological correlation (reference standard) for suspected CMLs. Twenty-four radiologists independently reported the presence or absence of CMLs in all cases in a blinded randomised cross-over design across two rounds. Logistic regression models were used to compare accuracy between modalities. RESULTS: Twenty CMLs were reviewed for each of the 10 subjects (200 metaphyses in all). Among them, 20 CMLs were confirmed by bone histopathology. Sensitivity for these CMLs was significantly higher for PMSS (69.6%, 95% CI 61.7 to 76.7) than PMCT (60.5%, 95% CI 51.9 to 68.6). Using PMSS for detection of CMLs would yield one extra correct diagnosis for every 11.1 (95% CI 6.6 to 37.0) fractured bones. In contrast, specificity was higher on PMCT (92.7%, 95% CI 90.3 to 94.5) than PMSS (90.5%, 95% CI 87.6 to 92.8) with an absolute difference of 2.2% (95% CI 1.0 to 3.4, p < 0.001). More fractures were reported collectively by readers on PMSS (785) than on PMCT (640). CONCLUSION: PMSS remains preferable to PMCT for CML evaluation. Any investigation of suspected abuse or unexplained deaths should include radiographs of the limbs to exclude CMLs. CLINICAL RELEVANCE STATEMENT: In order to avoid missing evidence that could indicate child abuse as a contributory cause for death in children, radiographs of the limbs should be performed to exclude CMLs, even if a PMCT is being acquired. KEY POINTS: • Corner metaphyseal lesions (CMLs) are indicative for abuse, but challenging to detect. Skeletal surveys (i.e. radiographs) are standard practice; however, accuracy of CT is unknown. • Sensitivity for CML detection on radiographs is significantly higher than CT. • Investigation of unexplained paediatric deaths should include radiographs to exclude CMLs even if CT is also being performed.

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.

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. MATERIALS AND METHODS: This prospectively registered, PRISMA-compliant systematic review searched the following databases: PubMed, MEDLINE, Web of Science, and Scopus from January 1, 2018, to May 29, 2023, with no restrictions on country of origin. Screening and data extraction occurred independently and in duplicate. Gender of first, last, and corresponding authors were determined using an artificial intelligence-powered, validated, multinational database ( www.genderize.io ). Two time periods were categorised according to the Johns Hopkins Center for Systems Science and Engineering: pre-COVID (prior to March 2020) and peak and post-COVID (March 2020 onwards). One-sample binomial testing was used to analyse proportion of authorship based on gender. Categorical variables were described as frequencies and percentages, and compared using testing chi-square or Fisher exact testing, with a threshold of P<0.05 representing statistical significance. RESULTS: In total, 922 articles were included with 39 countries represented. A statistically significant difference in authorship based on gender persisted during the peak and post-COVID time period (March 2020 onwards) where women represented a statistically significant lower proportion of last (35.5%) and corresponding (42.7%) authors (P<0.001, P=0.001, respectively). Statistically significant differences for first authors were not found in either period (P=0.08 and P=0.48). CONCLUSION: This study identifies differences in gender trends for authorship in paediatric radiology research worldwide. Future efforts to increase authorship by women are needed.

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.

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. Research participants interested in interventional radiology were selected for analysis. Analyses were performed by using either Fisher's exact or chi-square tests. Results: Of 892 respondents to the survey, 155 (17.4%) (112/155, 72.3% men and 43/155, 27.7% women) declared interest in interventional radiology. Active involvement in research and teaching was reported by 53.5% (83/155) and 30.3% (47/155) of the participants, respectively. The majority is willing to work in an academic setting in the future (66.8%, 103/155) and to perform a research fellowship abroad (83.9%, 130/155). Insufficient time was the greatest perceived barrier for both research and teaching activities (49.0% [76/155] and 48.4% [75/155], respectively), followed by lack of mentorship (49.0% [75/155] and 35.5% [55/155], respectively) and lack of support from faculty (40.3% [62/155] and 37.4% [58/155], respectively). Conclusion: Our international study shows that most trainees interested in interventional radiology subspecialty actively participate in research activities and plan to work in an academic setting. However, insufficient time for academia, mentorship, and support from seniors are considered challenges in 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. Nonetheless, real-world AI applications and clinical studies are limited in the niche area of paediatric imaging. This review article will focus on how AI, or more specifically deep learning, can be applied to TB diagnosis and management in children. We describe how deep learning can be utilised in chest imaging to provide computer-assisted diagnosis to augment workflow and screening efforts. We also review examples of recent AI applications for TB screening in resource constrained environments and we explore some of the challenges and the future directions of AI in paediatric TB.

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.

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.

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.

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.

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.

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. PARTICIPANTS: One artificial intelligence candidate (Smarturgences, Milvue) and 26 radiologists who had passed the FRCR examination in the preceding 12 months. MAIN OUTCOME MEASURES: Accuracy and pass rate of the artificial intelligence compared with radiologists across 10 mock FRCR rapid reporting examinations (each examination containing 30 radiographs, requiring 90% accuracy rate to pass). RESULTS: When non-interpretable images were excluded from the analysis, the artificial intelligence candidate achieved an average overall accuracy of 79.5% (95% confidence interval 74.1% to 84.3%) and passed two of 10 mock FRCR examinations. The average radiologist achieved an average accuracy of 84.8% (76.1-91.9%) and passed four of 10 mock examinations. The sensitivity for the artificial intelligence was 83.6% (95% confidence interval 76.2% to 89.4%) and the specificity was 75.2% (66.7% to 82.5%), compared with summary estimates across all radiologists of 84.1% (81.0% to 87.0%) and 87.3% (85.0% to 89.3%). Across 148/300 radiographs that were correctly interpreted by >90% of radiologists, the artificial intelligence candidate was incorrect in 14/148 (9%). In 20/300 radiographs that most (>50%) radiologists interpreted incorrectly, the artificial intelligence candidate was correct in 10/20 (50%). Most imaging pitfalls related to interpretation of musculoskeletal rather than chest radiographs. CONCLUSIONS: When special dispensation for the artificial intelligence candidate was provided (that is, exclusion of non-interpretable images), the artificial intelligence candidate was able to pass two of 10 mock examinations. Potential exists for the artificial intelligence candidate to improve its radiographic interpretation skills by focusing on musculoskeletal cases and learning to interpret radiographs of the axial skeleton and abdomen that are currently considered "non-interpretable."

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.

The clinical impact of observer variability in lung nodule classification in children with Wilms tumour.

OBJECTIVES: To investigate the extent to which observer variability of computed tomography (CT) lung nodule assessment may affect clinical treatment stratification in Wilms tumour (WT) patients, according to the recent Société Internationale d'Oncologie Pédiatrique Renal Tumour Study Group (SIOP-RTSG) UMBRELLA protocol. METHODS: I: CT thoraces of children with WT submitted for central review were used to estimate size distribution of lung metastases. II: Scans were selected for blinded review by five radiologists to determine intra- and inter-observer variability. They assessed identical scans on two occasions 6 months apart. III: Monte Carlo simulation (MCMC) was used to predict the clinical impact of observer variation when applying the UMBRELLA protocol size criteria. RESULTS: Lung nodules were found in 84 out of 360 (23%) children with WT. For 21 identified lung nodules, inter-observer limits of agreement (LOA) for the five readers were ±2.4 and ±1.4 mm (AP diameter), ±1.9 and ±1.8 mm (TS diameter) and ±2.0 and ±2.4 mm (LS diameter) at assessments 1 and 2. Intra-observer LOA across the three dimensions were ±1.5, ±2.2, ±3.5, ±3.1 and ±2.6 mm (readers 1-5). MCMC demonstrated that 17% of the patients with a 'true' nodule size of ≥3 mm will be scored as <3 mm, and 21% of the patients with a 'true' nodule size of <3 mm will be scored as being ≥3 mm. CONCLUSION: A significant intra-inter observer variation was found when measuring lung nodules on CT for patients with WT. This may have significant implications on treatment stratification, and thereby outcome, when applying a threshold of ≥3 mm for a lung nodule to dictate metastatic status.