University Children’s Hospital Basel

Functional gastrointestinal disorders (FGIDs) are common in childhood, but psychological correlates remain poorly understood. We compared emotional and behavioural functioning in children with FGIDs with somatic and healthy controls. Parents of children aged 2-12 years were recruited at the University Children's Hospital Basel (February 2024-February 2025). Children meeting Rome IV criteria formed the Functional Group; those with somatic gastrointestinal diseases and healthy peers served as Somatic and Healthy Controls. Parents completed the Strengths and Difficulties Questionnaire (SDQ) and Patient Health Questionnaire (PHQ-4). Group differences were tested using non-parametric models and adjusted negative binomial regression. Data from 218 children were analysed (Functional n = 66, Somatic n = 62, Healthy n = 90). SDQ total difficulties were markedly higher in FGIDs than in both control groups (p < 0.001). Differences were most pronounced for emotional and hyperactivity problems. Using age-adjusted SDQ total difficulties cut-offs, elevated scores occurred in 45.5% of children with FGIDs, compared with 8.1% in somatic and 10.0% in healthy peers. Parental psychological distress and separation predicted higher difficulties. Emotional and behavioural difficulties in FGIDs exceed those observed in somatic gastrointestinal diseases, indicating a particularly high psychosocial burden. These findings highlight the relevance of psychological aspects within integrated paediatric gastroenterology care.

Pediatric cholecystitis and cholelithiasis management is heterogeneous. We surveyed European centers to map current practices, training exposure, and outcomes of pediatric biliary cholecystectomy. A 24-item cross-sectional international survey was developed by the European Union of Medical Specialists (UEMS) Section of Paediatric Surgery and distributed to centers in 31 UEMS member states. Items covered institutional resources, indications and timing, surgical approach and adjuncts (ERCP, ICG), training exposure, and center-level outcomes; results are reported as n (%), median (IQR). Outcomes were reported at the center level and were self-reported by participating institutions. Thirty-two centers from 23/31 states responded (74.2%). Pediatric surgeons were primary operators in 84% (shared with adult surgeons in 16%); ERCP access was 66%. Trainee operator share was 22.5% (IQR 5-50) and simulator access 56%. ICG cholangiography was routine in 12.5% and selective in 31%. Acute calculous cholecystitis: 6% always index-admission and 59.4% interval (29-41 days) cholecystectomy; post-ERCP choledocholithiasis: 16% always index-admission cholecystectomy. In 2023, 185 cases were reported: 98.9% laparoscopic with 1.6% conversion; median age 14 years (IQR 12.25-15), operative time 90min (IQR 60-110), length of stay 2 days (IQR 1-2); 10 complications (5.4%). Substantial heterogeneity persists in both care pathways and training exposure; most centers lack formal pediatric-specific guidelines, and trainee-led operating remains limited, supporting the need for evidence-based protocols and structured training pathways.

The introduction of foundational models, specifically large language models, has promised a health care transformation. However, the field is rapidly evolving toward autonomous agent systems, defined as artificial intelligence (AI) entities that perceive and react to their environment to achieve specific goals-representing a paradigm shift from passive information retrieval to proactive, goal-oriented clinical assistance. Agentic AI systems transcend static knowledge limitations through core capabilities including persistent memory systems that maintain context across patient encounters, knowledge retrieval tools connecting to medical repositories through retrieval-augmented generation techniques, and computer use functionality enabling navigation of clinical software interfaces. Agentic workflows introduce sophisticated coordination mechanisms including hierarchical, collaborative, and sequential patterns demonstrating superior performance compared with single-agent approaches. Multiagent systems can autonomously coordinate entire clinical workflows across the entire radiology life cycle, from preacquisition protocol optimization through initial image analysis, specialized tool deployment, and preliminary report generation. However, successful clinical deployment requires systematic consideration of complexity thresholds, economic sustainability, cybersecurity frameworks, bias mitigation strategies, and appropriate governance structures. Critical challenges include managing the probabilistic nature of underlying models within deterministic clinical workflows, ensuring adequate human supervision, and preventing overcomplication of established processes. A structured four-phase implementation roadmap addresses these considerations through incremental progression from low-risk automation to comprehensive workflow orchestration while maintaining rigorous safety standards. As foundation models advance and interoperability standards mature, agentic AI will reshape radiology practice paradigms. Success depends on resolving stakeholder responsibility questions while orchestrating technological capabilities with clinical accountability, ensuring autonomous systems augment rather than replace professional judgment in pursuit of improved patient outcomes. Keywords: Informatics, Named Entity Recognition, Patient Scheduling/No-Show Prediction, Resource Allocation, Impact of AI on Education, Artificial Intelligence, Large Language Models, Agentic AI, Multi-Agent Systems, Radiology Workflow, Clinical Decision Support, Health Care Automation © RSNA, 2026.

We aimed to assess whether proteins which are involved in fetal lung development but also have an additional role in tissue or airway remodeling and oxidative stress response are associated with lung function and respiratory symptoms in infants. We performed hierarchical clustering to determine distinct profiles of nine cord blood proteins (growth factors, metalloproteinases, and autophagy markers) in 369 healthy infants born to non-asthmatic mothers from the Basel-Bern Infant Lung Development cohort (BILD). Using linear and negative binomial regression analysis, we examined the association of these profiles with lung function at 4-6 weeks and respiratory symptoms in the first year of life. Four protein profiles were identified, showing patterns of high growth factor, balanced protein (reference profile), low VEGF-A, and low growth factor, metalloproteinase, and autophagy marker levels. In comparison to the reference profile, the low VEGF-A levels profile was associated with reduced time to peak tidal expiratory flow to expiratory time (tPTEF/tE, -4.11, 95% confidence interval -8.04; -0.18, p=0.041, padj=0.123). No association was found between protein profiles and respiratory symptoms. In healthy infants, we found no clear association between the identified protein profiles and respiratory outcomes. However, we observed a trend for reduced tPTEF/tE in the low VEGF-A levels profile, which could indicate that some protein profiles may be associated with an increased risk of impaired lung function in infancy. This might be relevant in populations with additional risk factors such as prematurity or maternal asthma.

HighlightsWhat are the main findings?Cine phase contrast MRI for time-resolved assessment of leg muscle function during voluntary and electrically evoked motion was feasible in typically developing children.The success rates of cine phase contrast MRI during both voluntary and electrically evoked leg motion were reduced in pediatric patients with cerebral palsy.What is the implication of the main finding?Further optimization of the electrical muscle stimulation protocol, the voluntary motion task, and the MRI acquisition—particularly with regard to scan acceleration—is required.These improvements would enable cine phase-contrast MRI to serve as a feasible method for studying muscle dynamics and assessing treatment effects in pediatric patients with neuromuscular diseases.Background/Objectives: Magnetic resonance imaging (MRI) can be used to assess muscle function while performing a motion task within the scanner. Quantitative measures such as contraction velocity and strain can be derived from the images. Cine phase contrast (PC) MRI for time-resolved imaging of muscle function relies on the consistently repeated execution of the motion task for several minutes until data acquisition is complete. This may be difficult for patients with neuromuscular dysfunctions. To date, this approach has been applied only in adults, but not pediatric populations. The aim of this pilot study was to investigate the feasibility of PC MRI for assessing calf muscle function during electrically evoked and voluntary motion in children with cerebral palsy (CP) using open-source hardware and software. Methods: Cine PC MRI was performed at 3T in ambulatory pediatric patients with CP and typically developing children under electrical muscle stimulation (EMS) (n = 14/13) and during voluntary plantarflexion (n = 4/4) using a home-built pedal with a force sensor. A visual feedback software was developed to enable synchronized imaging of voluntary muscle contractions. Muscle contraction velocity and strain were calculated from the MRI data. Data quality was rated by two readers. Results: During EMS, the velocity data quality was rated as sufficient in 21% of scans in patients compared with 82% of scans in controls. During the voluntary task, all patients demonstrated increased compliance and greater generated force output than during EMS. Voluntary motion imaging was successful in all controls but none of the patients, as motion periodicity in patients was worse during voluntary than during stimulated contraction. Conclusions: Cine phase-contrast MRI combined with EMS or voluntary motion proved challenging in pediatric patients with CP, particularly in those with more severe baseline muscle dysfunction or reduced tolerance to stimulation. In contrast, the approach was successfully implemented in typically developing children. Although the scope of the patient-based findings is limited by data heterogeneity, the method demonstrates considerable potential as a tool for monitoring treatment-related changes in muscle function, particularly in less severely affected patients. Further refinement of the EMS and voluntary motion protocols, together with a reduction in MRI acquisition time, is required to improve motion periodicity, tolerability, and consequently the overall success rate in the intended pediatric patient cohort.

The increasing integration of artificial intelligence as medical devices (AIaMDs) within diagnostic imaging necessitates a robust understanding of associated regulatory frameworks among clinical practitioners. Despite the growing commercial availability and adoption of AIaMD, a significant awareness gap persists among radiologists regarding pertinent European Union regulations, including the Medical Device Regulation (MDR) and the novel EU AI Act, both of which lack explicit provisions tailored to AI components. This regulatory ambiguity underscores a critical need for clarified guidelines concerning “high-risk” AI classification and best practices for safe deployment within the radiological workflow. Legal responsibility for AIaMD Post-Market Surveillance (PMS) primarily rests with software providers, yet radiologists are expected to contribute to the ongoing monitoring of safety and performance. Recognizing the need to raise awareness and provide practical guidance, the European Society of Radiology (ESR) eHealth and Informatics Subcommittee, supported by the ESR AI Working Group, conducted a modified Delphi procedure involving 16 domain experts (of which 14 acted as panelists) to establish a set of shared recommendations. These aim to establish essential practices for AIaMD PMS and post-market clinical feedback (PMCF), as stipulated by the MDR and partially updated by the AI Act. This paper also provides an overview of relevant regulations to enhance awareness among all stakeholders, particularly deployers (e.g., radiologists) and providers (e.g., vendors). These recommendations represent a foundational step towards improving consistency in AIaMD deployment, providing a critical reference standard for physicians navigating the unique challenges posed by these novel technologies.Critical relevance statementRadiologists need to familiarize themselves with AIaMD EU regulations due to shared PMS responsibilities and current ambiguities. ESR recommendations aim to bridge this awareness gap, standardizing safe AI deployment and enhancing clinical feedback within medical imaging.Key PointsRadiologists need a clear understanding of EU regulations for AIaMDs, as current laws lack imaging-specific guidance.There is a shared responsibility for AIaMD safety, with radiologists contributing to PMS and clinical feedback systems.The ESR provides crucial recommendations to standardize AI deployment and improve clinical feedback in imaging.Graphical

BackgroundThe therapeutic potential of non-invasive transcranial electric stimulation (tES) is growing, but challenges in tailoring treatments to individual patients persist. We demonstrated that personalized montages, informed by biophysical modeling, can reduce dose variability and improve target engagement. However, traditional setups are prone to electrode placement errors, leading to inconsistent dosage, localization and potential off-target engagement.MethodsWe developed a pipeline for creating patient-specific 3D-printed caps based on individual MRI scans to allow custom placement of up to 34 electrodes. Hybrid brush electrodes were incorporated to facilitate the use on with-hair regions of the head. The patient-specific caps are integrated within a Neurostimulator/EEG device, enabling precise electrode placement for recording of neural activity and optimized, personalised tES therapies based on individual biophysical brain models.ResultsA proof-of-concept in-silico study highlighted the importance of positional accuracy in electrode placement, particularly in minimizing off-target stimulation in case of the personalized montage configuration. To mitigate positional displacement, we introduced the pipeline for generating patient-specific 3D-printed caps, ensuring precise anatomical fit. The flexible design of these caps supports high-density electrode arrays tailored to various therapeutic montages. Integrated brush electrodes function in both dry and wet modes and are powered by electronics embedded in a neckpiece, enabling multi-step tES and EEG recording with minimal setup for at-home use. Electrical and mechanical evaluations confirmed the system’s feasibility, and a clinical trial with eight healthy subjects showed improved comfort and increased willingness for home use.ConclusionThis customized cap-electrode system provides a practical solution for self-administered, repeatable personalized tES and EEG session at home.Trial registration: The study is registered on the Swiss National Clinical Trials Portal (SNCTP), (SNCTP000005598) and Clinicaltrials.gov (NCT05999916). The study was approved by the Independent Competent Ethics Committee (Ethikkommission Nordwest-und Zentralschweiz (EKNZ)) at the 14 August 2023 and the Competent Regulatory Authority Swissmedic at the 20 December 2023.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12984-025-01769-8.

Children's interstitial lung disease (chILD) encompasses alarge group of rare and heterogeneous pulmonary disorders associated with diagnostic challenges for all disciplines. Due to the substantial morbidity and mortality, atimely and accurate diagnosis is required for optimal patient care. Radiology plays acrucial role in the diagnosis of chILD; computed tomography (CT) represents the current gold standard imaging modality. To make an accurate diagnosis, asystematic approach in amultidisciplinary team is essential. CT confirms the presence of chILD and enables exclusion of more frequent disorders. In conjunction with patient history and clinical presentation, knowledge of imaging patterns in chILD may lead to aspecific diagnosis; otherwise unspecific changes can narrow differential diagnosis, guide further diagnostics, and prevent more invasive procedures.

Abstract The cement industry ranks among the most energy-intensive sectors worldwide, accounting for extensive consumption of non-renewable fuels and the release of substantial untapped waste heat. Traditional energy balance methods are inadequate for identifying system inefficiencies, whereas exergy analysis provides a more rigorous evaluation by assessing energy quality losses. Conventional exergy models relay on enthalpy- based formulations derived from thermodynamics principles, correlating exergy with enthalpy and temperature through either Carnot factor. However, enthalpy cannot be measured directly with standard plant instruments, limiting the practicality of such methods for real-time monitoring. This study proposes a novel methodology for real-time exergy analysis of cement rotary kiln based exclusively on plant-measured variables, including temperature, pressure, and mass flowrates, integrated with machine learning tools. Real-time operational plant data of rotary kiln is analyzed using Python-based artificial intelligence algorithms to develop model. Results indicated that 454.38 MJ of exergy entered the kiln, primarily through raw materials and fuel combustion, while 3.9 MJ exited, leading to a calculated loss of 450.48 MJ. Regression fitting confirmed the model’s ability to capture real-time exergy dynamics with high accuracy. The findings demonstrate that combining exergy analysis with machine learning enables practical, real-time assessments of process inefficiencies, offering valuable insights for industrial decision-making. The proposed framework provides a pathway for optimizing operating conditions, minimizing exergy losses, and advancing sustainable in one of the world’s most energy-demanding industries.

Switzerland's decentralised healthcare system delegates responsibility for paediatric hospital infrastructure to individual cantons. To date, official statistics on the number and types of paediatric hospital beds are lacking. This study sought to fill this gap by collecting and analysing data from all paediatric hospitals in Switzerland. A nationwide cross-sectional e-mail survey was conducted in January 2023. Data on both structurally available and operated beds were collected and descriptively analysed. The survey identified a total of 1751 beds in 29 paediatric hospitals or departments, of which 85% were operated. Of the total beds, 112 were paediatric intensive care unit beds (80% operated) and 339 were neonatology beds (86% operated). Significant regional disparities in bed availability were identified: the Lake Geneva region has the highest bed-to-child ratios, while Central Switzerland, Eastern Switzerland and Ticino show notably lower ratios. These findings highlight the current distribution of paediatric beds, the considerable proportion of non-operated beds, and the importance of continued, comprehensive data collection to inform healthcare planning.