This study aimed to investigate the prevalence of brachydactyly type A3 (BDA3) and its associated epiphysial development abnormalities in Chinese children aged 3–17 years, and to explore differences based on gender, region and urban–rural demographics.

Cross-sectional study.

The study was conducted across 14 provinces (28 survey sites) in China, as part of a nationwide investigation on skeletal maturation. The population was selected using multistage stratified randomised cluster sampling.

A total of 17 850 children (8856 boys and 8994 girls) aged 3–17 years participated. The cohort was drawn from a large-scale survey conducted between 2019 and 2021. Selection criteria included children with no visible clinodactyly or hand function impairments.

Non-dominant hand-wrist radiographs were obtained using a portable X-ray device. A retrospective analysis of these radiographs was performed to identify BDA3 and epiphysial development abnormalities. Prevalence rates were calculated and compared across gender, regional and urban–rural groups.

The overall prevalence of BDA3 was 10.0%, with a higher prevalence in girls (12.9% vs 7.1%; p

This nationwide, multicentre study provides the first national epidemiologic data on BDA3 and associated epiphysial features in Chinese children and adolescents, establishing a prevalence of 10.0%. This baseline supports counselling that a straight, well-functioning short fifth finger is a common anatomic variant and may help reduce unnecessary concern.

The utility of brain MRI in dementia diagnosis offers critical insights into structural brain changes, such as hippocampal and thalamic atrophy, which are hallmark features of Alzheimer’s disease and Alzheimer’s disease-related dementias . However, its use, especially in low- and middle-income countries (LMICs), is affected by limited accessibility. This protocol outlines a systematic review and meta-analysis to assess the diagnostic utility, feasibility and challenges of integrating brain MRI for dementia diagnosis in LMICs.

The review follows Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols with a priori eligibility criteria and is registered in PROSPERO. Searches (from inception to September 2025) will be run in MEDLINE/PubMed, EMBASE, Web of Science and PsycINFO, with supplementary bibliography screening. Adults ≥50 years in LMIC settings undergoing brain MRI for dementia evaluation will be eligible. Data will be synthesised narratively and, where appropriate, via random-effects meta-analysis with planned subgroup analyses by MRI approach (qualitative vs quantitative), magnet strength, sequence availability and reference standard. Screening and data extraction are planned for 1 November to 30 December 2025.

Ethical approval was obtained from the Makerere University School of Medicine Research and Ethics Committee (Mak-SOMREC; Ref Mak-SOMREC-2022-337). For verification, contact the SOMREC Administrator at rresearch9@gmail.com. Departmental contact: Dr Geoffrey Erem, Head, Department of Radiology, Makerere University College of Health Sciences (dreremgeoffrey@gmail.com). Only published data will be used, with no new patient contact. Findings will be disseminated via peer-reviewed publication, conference presentations and policy briefs (and, where feasible, mainstream media) to inform clinical practice and training in LMICs.

CRD42024510241.

Overuse of CT scans is associated with multiple harms, such as an increased risk of cancer development, particularly in children. However, the rate of CT scan use is high and unwarranted worldwide.

This study aimed to identify the patterns and reported indications for head CT scans ordered for non-traumatic paediatric cases in Palestine.

This was a retrospective, cross-sectional study based on a desk review.

The study was carried out from June 2024 to September 2024 in five hospitals located in five major Palestinian governorates in the West Bank.

The study included records of children aged 14 or younger, presenting with non-traumatic complaints and having undergone head CT between January 2020 and September 2024. A total of 3715 patient records were explored, of which 2977 were included in the final analysis; 1764 (59.3%) males and 1213 (40.7%) females.

A pilot review of 100 records was conducted, and the data collection spreadsheet included demographic and clinical characteristics, presentations, reported reasons for CT requests, CT results, and information on lumbar puncture (LP) performance.

The mean age of patients was 4.3 years (SD±3.3), with 59.3% aged 3 to 11 years, and 47.7% presenting to hospitals in northern governorates. The most commonly reported presentation was fever and convulsion (8.2%), followed by convulsions (7.7%), and a combination of fever, headache and vomiting (6.5%). Only 12.9% of the CT scans yielded positive findings, including dilated ventricles (19.3%), sinusitis (18.8%), brain oedema (12.9%), and brain mass (11.1%). Most CT scans were requested to check for contraindications to LP, with only 4.1% having a positive CT finding indicating a contraindication. At the multivariate level, a positive CT result was associated with being a neonate, having a past medical condition, ordering CT to check for contraindication to LP and presenting with convulsions.

CT scans were found to be overused without justification, particularly for ruling out contraindications to LP. The development of clear and specific national guidelines is recommended. This process can be supported through training, decision support tools, alternative management pathways and specialist consultations to ensure compliance. Additionally, enhancing reporting quality and using health information systems are vital for monitoring and improving radiological safety.

The standard treatment for unresectable head and neck cancer typically involves radiotherapy (RT) alone or chemoradiotherapy (chemo-RT). Non-squamous cell carcinomas exhibit relatively low radiosensitivity, limiting the efficacy of conventional photon RT. Carbon-ion (C-ion) RT, characterised by high linear energy transfer (LET) and high relative biological effectiveness (RBE), has shown promising outcomes in treating radioresistant head and neck cancers. However, local recurrences still occur, and further improvements in treatment outcomes are needed. To enhance the local control rate, an increase in dose-averaged LET (LETd) to the tumour was considered.

Following a simulation study, a clinical trial was conducted to optimise LETd using only C-ion therapy, and its safety was confirmed. However, in this clinical trial, LETd could only be increased to approximately 70 keV/μm. To further escalate LETd, multi-ion therapy using ions heavier than carbon was developed. Simulation studies demonstrated that multi-ion therapy incorporating carbon, oxygen and neon ions could increase LETd up to 90 keV/μm, regardless of tumour size, while maintaining high-dose uniformity within the tumour. Based on these results, a clinical study was planned to evaluate the safety of escalating LETd from 70 keV/μm to 90 keV/μm using multi-ion therapy. The primary objective of this study is to evaluate the safety of escalating LETd to the tumour using multi-ion therapy for head and neck cancer, with the secondary goal of identifying the maximum tolerated LETd.

This is a non-randomised, open-label, phase 1 study focused on LETd escalation. A maximum of 18 patients with histologically confirmed inoperable head and neck malignancies will be enrolled. All patients will receive multi-ion therapy using helium, carbon, oxygen or neon ions, either alone or in combination, at an RBE-weighted dose ranging from 57.6 to 70.4 Gy, delivered in 16 fractions (4 fractions per week) over 4 weeks. The specific dose will be determined according to histology. LETd escalation will begin at 70 keV/μm and will increase by 10 keV/μm increments, reaching a maximum of 90 keV/μm. The safety of multi-ion therapy will be assessed based on the frequency and severity of dose-limiting toxicities, monitored up to 90 days after the initial irradiation. Patients will be followed up according to the protocol for 180 days after the initial multi-ion therapy irradiation.

The study protocol has been approved by the National Institutes for Quantum Science and Technology Certified Review Board (#L24-002). The results will be published in a peer-reviewed journal and presented at a scientific conference.

jRCTs032240451.

Progress at the intersection of artificial intelligence and paediatric neuroimaging necessitates large, heterogeneous datasets to generate robust and generalisable models. Retrospective analysis of clinical brain MRI scans offers a promising avenue to augment prospective research datasets, leveraging the extensive repositories of scans routinely acquired by hospital systems in the course of clinical care. Here, we present a systematic protocol for identifying ‘scans with limited imaging pathology’ through machine-assisted manual review of radiology reports.

The protocol employs a standardised grading scheme developed with expert neuroradiologists and implemented by non-clinician graders. Categorising scans based on the presence or absence of significant pathology and image quality concerns facilitates the repurposing of clinical brain MRI data for brain research. Such an approach has the potential to harness vast clinical imaging archives—exemplified by over 250 000 brain MRIs at the Children’s Hospital of Philadelphia—to address demographic biases in research participation, to increase sample size and to improve replicability in neurodevelopmental imaging research. Ultimately, this protocol aims to enable scalable, reliable identification of clinical control brain MRIs, supporting large-scale, generalisable neuroimaging studies of typical brain development and neurogenetic conditions.

Studies using datasets generated from this protocol will be disseminated in peer-reviewed journals and at academic conferences.

The increasing volume of radiological images and the associated workload of report generation necessitate efficient solutions, making artificial intelligence (AI) a crucial tool to streamline this process for radiologists. Recent years have seen a surge in research exploring AI-driven radiological report generation directly from images, particularly with the emergence of large vision language models. However, a comprehensive understanding of the current landscape, including specific limitations and the extent to which efforts move beyond abnormality detection to full textual report generation, remains unclear. This scoping review aims to systematically map the existing literature to provide an overview of the current state of AI in generating radiological reports from medical images, including the scope and limitations of existing research. To our knowledge, no prior scoping review has comprehensively mapped this landscape, especially considering recent advancements in foundation models in medicine and related AI architectures. Considering the explosive growth of related studies in recent years, a comprehensive scoping review will be significant in mapping the current research status and understanding relevant limitations.

This scoping review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews guidelines to map the literature on AI generating radiological reports from medical images. We will search PubMed, Scopus and Web of Science for peer-reviewed articles (January 2016 to March 2025) using keywords related to AI, radiological reports and medical images. Original research in English focusing on AI-driven report generation from images will be included and studies without report generation or not using medical images as input will be excluded. Two independent reviewers will perform a two-stage screening. Data extraction, guided by the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist and focusing on study characteristics, AI methods, image modalities, report features, limitations and key findings, will be analysed using narrative and descriptive synthesis, with results presented in tables, figures and a narrative summary.

This protocol describes a scoping literature review methodology that does not involve research on humans, animals or their data; therefore, no ethical approval is required. Following the review, the results will be considered for publication in a relevant peer-reviewed journal and may be shared with stakeholders through reports or summaries.