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.

Comparison of chest radiograph findings in ambulatory and hospitalized children with pulmonary tuberculosis.

BACKGROUND: The diagnosis of childhood tuberculosis (TB) is, in many instances, solely reliant on chest radiographs (CXRs), as they are often the only diagnostic tool available, especially in TB-endemic areas. Accuracy and reliability of CXRs for detecting TB lymphadenopathy may vary between groups depending on severity of presentation and presence of parenchymal disease, which may obscure visualization. OBJECTIVE: To compare CXR findings in ambulatory versus hospitalized children with laboratory confirmed pulmonary TB versus other lower respiratory tract infections (LRTI) and test inter-rater agreement for these findings. MATERIALS AND METHODS: Retrospective review, by two pediatric radiologists, of CXRs performed on children < 12 years old referred for evaluation of LRTI with clinical suspicion of pulmonary TB in inpatient and outpatient settings. Each radiologist commented on imaging findings of parenchymal changes, lymphadenopathy, airway compression and pleural effusion. Frequency of imaging findings was compared between patients based on location and diagnosis and inter-rater agreement was determined. Accuracy of radiographic diagnosis was compared to laboratory testing which served as the gold standard. RESULTS: The number of enrolled patients was 181 (54% males); 69 (38%) were ambulatory and 112 (62%) were hospitalized. Of those enrolled, 87 (48%) were confirmed to have pulmonary TB, while 94 (52%) were other LRTI controls. Lymphadenopathy and airway compression were more common in TB patients than other LRTI controls, regardless of patient location. Parenchymal changes and pleural effusion were more common in hospitalized than ambulatory patients, regardless of patient diagnosis. Agreement for parenchymal changes was higher in the hospitalized group (kappa [κ] = 0.75), while agreement for lymphadenopathy (κ = 0.65) and airway compression (κ = 0.68) was higher in the ambulatory group. The specificity of CXRs for TB diagnosis (> 75%) was higher than the sensitivity (< 50%) for both ambulatory and hospitalized groups. CONCLUSION: Higher frequency of parenchymal changes among hospitalized children may conceal specific imaging findings of TB such as lymphadenopathy, contributing to the poor reliability of CXRs. Despite this, the high specificity of CXRs shown in our results is encouraging for continued use of radiographs for TB diagnosis in both settings.

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.

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.

Quality assurance of paediatric lateral chest radiographs.

INTRODUCTION: Lateral chest radiographs aid in paediatric clinical practice in countries where the diagnosis of primary pulmonary tuberculosis (PTB) still relies heavily on the chest radiograph. This study aimed to create a validated quality assurance (QA) tool investigating the diagnostic performance of this projection by applying this to a database of lateral chest radiographs in children with suspected PTB. METHOD: The QA tool was built to include a compilation of criteria from the different sources, accompanied by graphic representations and objective measurements where appropriate. Each defined criterion (radiographic error) was evaluated by implementing the QA tool on 300 radiographs, scored by three readers. The sample was subjected to two separate sets of data analysis, based on averages, and on majority decision methodology. RESULTS: The QA tool was based on existing published criteria, as well as under-collimation and under-inspiration, two de novo criteria. For the total 900 reads, errors were categorized as patient-related in 681 (75.7%) and radiographer-related in 421 (46.8%) and 122 (13.6%) had no errors. The average number of errors per radiograph ranged from 0.9 to 4.7 errors out of the 11 quality factors reviewed. When considering the majority decision, the median errors per radiograph was 1 (IQR 1-2) (range 0-5). Inter-rater agreement varied for different criteria. CONCLUSION: A novel QA tool for evaluating lateral chest radiographs was developed which requires further efforts of refinement regarding criteria such as exposure, field of view: under-collimation, and motion artifact, which remain subjective. The designed QA tool will allow comparison of radiograph quality before and after interventions. Furthermore, the tool can be used in tackling childhood PTB in low- and middle-income countries (LMICs) since the hallmark of the disease is lymphadenopathy, which is often depicted best on lateral chest radiographs.

Pediatric Lower Respiratory Tract Infections: Imaging Guidelines and Recommendations.

Lower respiratory tract infection (LRTI) remains a major cause of morbidity and mortality in children. Various organisms cause LRTI, including viruses, bacteria, fungi, and parasites, among others. Infections caused by 2 or more organisms also occur, sometimes enhancing the severity of the infection. Medical imaging helps confirm a diagnosis but also plays a role in the evaluation of acute and chronic sequelae. Medical imaging tests help evaluate underlying pathology in pediatric patients with recurrent or long-standing symptoms as well as the immunocompromised.

Fronto-temporal cortical atrophy in 'nyaope' combination heroin and cannabis use disorder.

Sub-Saharan Africa is one of the top three regions with the highest rates of opioid-related premature mortality. Nyaope is the street name for what is believed to be a drug cocktail in South Africa although recent research suggests that it is predominantly heroin. Nyaope powder is most commonly smoked together with cannabis, a drug-use pattern unique to the region. Due to the increasing burden of this drug in low-income communities and the absence of human structural neuroimaging data of combination heroin and cannabis use disorder, we initiated an important cohort study in order to identify neuroanatomical sequelae. Twenty-eight male nyaope users and thirty healthy, matched controls were recruited from drug rehabilitation centers and the community, respectively. T1-weighted MRI images were obtained using a 3 T General Electric Discovery and cortical thickness was examined and compared. Nyaope users displayed extensive grey matter atrophy in the right hemispheric medial orbitofrontal, rostral middle frontal, superior temporal, superior frontal, and supramarginal gyri (two-sided t-test, p < 0.05, corrected for multiple comparisons). Our findings indicate cortical abnormality in nyaope users in regions involved in impulse control, decision making, social- and self-perception, and working memory. Importantly, affected brain regions show large overlap with the pattern of cortical abnormalities shown in heroin use disorder.

A systemic review of tuberculosis with HIV coinfection in children.

The epidemiology of tuberculosis is adversely impacted by the human immunodeficiency virus (HIV) coinfection. HIV-infected patients are more prone to opportunistic infections, most commonly tuberculosis, and the risk of death in coinfected patients is higher than in those without HIV. Due to the impaired cellular immunity and reduced immunological response in HIV-infected patients, the classic imaging features of tuberculosis usually seen in patients without HIV may present differently. The aim of this review article is to highlight the imaging features that may assist in the diagnosis of tuberculosis in patients with HIV coinfection.

Corpus callosum thickness in children: an MR pattern-recognition approach on the midsagittal image.

Thickening of the corpus callosum is an important feature of development, whereas thinning of the corpus callosum can be the result of a number of diseases that affect development or cause destruction of the corpus callosum. Corpus callosum thickness reflects the volume of the hemispheres and responds to changes through direct effects or through Wallerian degeneration. It is therefore not only important to evaluate the morphology of the corpus callosum for congenital anomalies but also to evaluate the thickness of specific components or the whole corpus callosum in association with other findings. The goal of this pictorial review is raise awareness that the thickness of the corpus callosum can be a useful feature of pathology in pediatric central nervous system disease and must be considered in the context of the stage of development of a child. Thinning of the corpus callosum can be primary or secondary, and generalized or focal. Primary thinning is caused by abnormal or failed myelination related to the hypomyelinating leukoencephalopathies, metabolic disorders affecting white matter, and microcephaly. Secondary thinning of the corpus callosum can be caused by diffuse injury such as hypoxic-ischemic encephalopathy, human immunodeficiency virus (HIV) encephalopathy, hydrocephalus, dysmyelinating conditions and demyelinating conditions. Focal disturbance of formation or focal injury also causes localized thinning, e.g., callosal dysgenesis, metabolic disorders with localized effects, hypoglycemia, white matter injury of prematurity, HIV-related atrophy, infarction and vasculitis, trauma and toxins. The corpus callosum might be too thick because of a primary disorder in which the corpus callosum finding is essential to diagnosis; abnormal thickening can also be secondary to inflammation, infection and trauma.

Combined oesophageal atresia with upper pouch fistula and meconium peritonitis.

Upper pouch tracheoesophageal fistula occurs is less than 1% of all oesophageal atresia variants. Meconium peritonitis is a rare neonatal condition with an incidence of 1:30 000 live births. In this case report, we describe the presentation, clinical findings and management of a patient diagnosed with an oesophageal atresia with upper pouch fistula as well as meconium peritonitis. To the best of our knowledge, this is the first case such as this described in published literature.