Research publications
Browse through all publications from the Institute of Global Health Innovation, which our Patient Safety Research Collaboration is part of. This feed includes reports and research papers from our Centre.
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Journal articleLasala A, Fiorentino MC, Bandini A, et al., 2026,
Two-step latent diffusion modelling for morphology-guided synthesis of glioma intraoperative ultrasound images
, Biomedical Signal Processing and Control, Vol: 120, ISSN: 1746-8094Intraoperative ultrasound (iUS) is increasingly used in neurosurgery to monitor tumour margins during resection. The adoption of iUS is still limited by low image quality, noise, and heterogeneous echogenicity, which makes surgeons’ interpretation of surgical margins challenging. While deep learning can aid automatic margin delineation, the lack of annotated datasets limits the development of robust methods. To address this challenge, we propose a two-step generative framework based on latent diffusion models that consist of (i) an unconditional tumour-mask generator that learns geometric features of real tumours, and (ii) a conditional iUS image generator that synthesizes realistic iUS images by using the generated tumour masks as a prior. Morphological fidelity is assessed through tailored quantitative and qualitative metrics. The performance of automatic tumour margin segmentation algorithms is evaluated through data augmentation experiments to determine whether the inclusion of synthetic data can improve segmentation performance. Compared to state-of-the-art conditional generative models, including diffusion-based approaches (ControlNet) and generative adversarial networks (Pix2Pix), the proposed framework achieves superior qualitative and quantitative performance in representing tumoural and non-tumoural tissue. Performance evaluated using a 5-fold cross-validation protocol yields statistically significant improvements in morphological fidelity (Dice Similarity Coefficient: 0.851; Hausdorff Distance: 16.21). The analysis shows that introducing synthetic data significantly improves boundary delineation performance using nn-UNet, reducing the average Hausdorff Distance from 33.97 to 30.72 in the test set. These results indicate that the proposed framework helps mitigate the scarcity of annotated iUS data by providing realistic samples to support training in neurosurgical image segmentation.
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Journal articleBatcup C, Almukhtar A, Menon A, et al., 2026,
Exploring the overuse of non-sterile gloves in operating theatres: a cross-sectional survey and interview study
, BMJ Open, ISSN: 2044-6055Objectives: To identify factors influencing unnecessary non-sterile glove use in operating theatres, and to estimate how common these factors are across the UK.Design: Mixed-methods study using interviews and a cross-sectional survey.Setting: Imperial College Healthcare Trust for interviews, and nationally across the UK for the survey. Participants: 19 interviewees and 329 survey respondents, all clinical staff working in UK operating theatres.Outcome measures: Barriers and facilitators to unnecessary non-sterile glove use in operating theatres.Results: The findings highlight a combination of key drivers leading to the unnecessary use of non-sterile gloves: (1) lack of prioritisation of sustainability, (2) fears around negative patient outcomes, (3) strong social influences such as norms to use gloves, (4) the absence of clear guidelines and limited training on glove use, (5) availability of alternatives and quality of gloves, and (6) beliefs about personal safety and habitual glove use. Respondents also suggested potential intervention strategies.Conclusions: 67% of participants reported using gloves unnecessarily. Our findings highlight the role of habitual behaviour, social influences and unclear guidelines in driving this practice. Interventions should address these factors, for example by clearly communicating when gloves should and should not be worn, encouraging changes to local social norms towards waste reduction, improving access to hand gel, and supporting habit change to reduce unnecessary glove use and associated environmental impact.
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Journal articleAlian A, Avery J, Mylonas G, 2026,
Electrical Impedance Tomography and Neural Networks for Shape Sensing in Soft Continuum Endoscopic Robots
, IEEE Robotics and Automation Letters, Vol: 11, Pages: 6544-6551Soft robotics offer biocompatibility, dexterity, and safe tissue interaction in surgery, providing potential alternatives to conventional tools such as colonoscopes. However, their nonlinear behaviour demands closed-loop control with structure-compatible feedback. This work presents a scalable 3D shape-sensing method based on Electrical Impedance Tomography (EIT), unifying actuation and sensing of a hydraulically actuated soft robot within a neural network framework. A soft continuum manipulator (14.6 mm in diameter) with saline-pressurised chambers and embedded kirigami-inspired FPCs was evaluated in free motion and ex vivo porcine colon trials. A multilayer perceptron (MLP) predicted the full 3D shape, achieving tip RMSEs of 0.46, 0.20, and 0.40 mm (x, y, z) in free motion, and 1.96, 0.86, and 0.89 mm in ex vivo. This letter marks the first ex vivo validation of EIT-based shape sensing in soft endoscopy and demonstrating its potential for closed-loop surgical control.
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Journal articleReka H, van Kessel R, Mossialos E, et al., 2026,
Private health insurance in Gulf Cooperation Council countries: A scoping review.
, Health Policy Open, Vol: 10Private Health Insurance (PHI) in Gulf Cooperation Council (GCC) countries has experienced rapid growth over the past two decades, driven by demographic and economic changes. Although various analyses at the country level have been reported, no study has reviewed PHI systems in the GCC through a methodological approach. We provide a conceptual framework to review, describe and document the development of PHI in the GCC, based on literature from the scoping review. As of December 2023, all GCC countries have laws in place or have promulgated laws establishing mandatory PHI schemes. Most of these schemes are designed for expatriate populations residing in these countries, but there is a trend to extend them to nationals working in the private sector. The health system context plays a role in how PHI emerged and is designed in terms of role, eligibility, and coverage. PHI markets in the region are concentrated and dominated by local companies with performance levels that could be further improved. These markets are maturing and subject to more robust technical and prudential regulations as governments seek to enhance competition. Governments in the region must ensure the sustainable growth of these schemes and a more strategic alignment with health system objectives. Lessons learned from more mature markets are critical for future developments.
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Journal articleKostopoulou O, 2026,
Advice taking in medical decision making
, La Presse Médicale, Pages: 104360-104360, ISSN: 0755-4982 -
Journal articleDewa LH, Hafferty JD, Bates R, et al., 2026,
A response to “Surveillance is not safety: a response to Dewa and colleagues’ paper about passive remote monitoring technology (Oxevision)”
, BMC Psychiatry, Vol: 26, ISSN: 1471-244X -
Journal articleAnyaibe S, Anderson AK, Domfe CA, et al., 2026,
Eating architecture components and their associations with BMI in urban and rural Ghanaian mothers, fathers, children, and adolescents, assessed using a wearable camera: A cross-sectional study.
, Chronobiol Int, Pages: 1-14Eating architecture - timing, frequency, and size of meals and snacks - affects metabolism, but data from low-middle-income countries (LMICs) are scarce. We examined eating architecture (timing, frequency, and size of eating occasions) among Ghanaian households and its relationship with BMI. Thirty rural and 30 urban Ghanaian households participated. A wearable camera on eyeglasses captured dietary intake over 2 weekdays and 1 weekend day. Custom software was used for nutritional analysis and identifying eating episodes. Meals were distinguished from snacks by time, context, and items consumed. Eating frequencies were 2.4-2.7 x/d, and eating windows were 6.5-9.5 h/d. Children ate more frequently than other household members and had longer eating windows than fathers. Eating and energy intake peaked at 8:00 h and 12:00 h, respectively. Only 56% of urban and 72% of rural members snacked. Meal energy was similar across locations, but snack energy was higher among urban versus rural households, positively associated with BMI among urban mothers. Ghanaian eating architecture varied by location, household member, and differed from high-income countries. Only the size component of eating architecture, namely snack energy, was associated with BMI, and only in urban mothers. Our findings highlight the need to address nutritional disparities in Ghana and other LMICs.
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Journal articleGursoy R, Yilmaz A, Kizilyaprak B, et al., 2026,
Artifact-aware fungal detection in dermatophytosis: a transformer-based approach for KOH microscopy
, Bioengineering, ISSN: 2306-5354Dermatophytosis is commonly assessed using potassium hydroxide (KOH) microscopy, yet accurate recognition of fungal hyphae is hindered by preparation-related artifacts, heterogeneous keratin clearance, and notable inter-observer variability. This study presents a transformer-based object detection framework using the RT-DETR architecture for precise, query-driven localization of fungal structures in high-resolution KOH images. A dataset of 2,540 routinely acquired microscopy images was manually annotated using a multi-class strategy that explicitly distinguishes fungalelements from confounding artifacts, enabling the model to actively suppress false detections arising from visuallysimilar mimics. To assess architectural trade-offs, RT-DETR was benchmarked against two CNN-based detectors (YOLOv11 and Faster R-CNN) under identical training and inference conditions. Five-fold stratified cross-validation was performed, and each fold-level model was evaluated on the same independent held-out test set (n=254). Across the five evaluations, RT-DETR achieved a mean AP@0.50 of 89.73±1.48%, a mean recall of 0.831±0.011, and a mean precision of 0.921±0.014. When aggregated for image-level classifications, the model achieved a mean sensitivity of 0.989±0.022 on the independent test set, with a mean of 0.2±0.4 missed positive cases across the five evaluations. These results demonstrate the technical feasibility of a transformer-based artificial intelligence (AI) system as a decision-support aid for fungal region detection in KOH microscopy, pending prospective multi-center validation to establish clinical generalizability.
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Journal articleEzzat A, Zhu Z, Roddan A, et al., 2026,
Label-free classification of breast cancer subtypes in ex vivo human tissues using Raman spectroscopy and machine learning
, Scientific Reports, ISSN: 2045-2322Breast conserving surgery (BCS) aims to excise breast tumors whilst preserving breast-related quality of life, but is complicated by the challenge of accurately identifying the margin between healthy and cancerous tissue. Raman spectroscopy (RS) has been shown to distinguish between normal breast tissue and breast cancer. Thus, this study aimed to further evaluate the diagnostic performance of RS in ex vivo breast tissue subtype classification via investigation of signals from healthy tissues and three breast cancer subtypes (invasive ductal carcinoma, IDC; invasive lobular carcinoma, ILC; and ductal carcinoma in situ, DCIS). A total of 80 tissue samples (46 normal and 34 cancerous) from 71 individuals were measured using a confocal Raman microscope. Spectral signatures wereinvestigated, and supervised classification was performed for both two-class (healthy vs. cancer) and four-class (healthy vs. IDC vs. ILC vs. DCIS) classification tasks. RS successfully differentiated cancerous from normal breast tissue (97.84% sensitivity, 97.18% specificity). For four-class classification, RS achieved in-class sensitivity ranging from 83-96% and specificity from 93-99%. These findings demonstrate that RS can accurately distinguish normal from cancerous tissue and capture clinically relevant differences among histological including invasive and pre-invasive disease, supporting its promise for intraoperative tissue characterization during BCS.
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Journal articleBower M, Filia K, Lawrance EL, et al., 2026,
Climate change and social health.
, Nat Hum BehavSocial health-our ability to access and maintain meaningful human relationships-is recognized as a critical determinant of population health and climate change resilience, yet it is poorly integrated into climate change policy and research. This narrative Review synthesizes interdisciplinary evidence of the bidirectional and nuanced relationship between climate change and social health: climate change disrupts key social conditions (including housing stability and community cohesion), while widespread social disconnection limits our collective capacity to address the climate crisis. We unpack how social health can function as both a climate vulnerability and a lever for climate action. We present a new conceptual framework, describing the pathways through which social health and climate outcomes interact. Finally, we highlight existing evidence gaps and opportunities for public policy development and call for climate and health governance to centre social health as a key pillar of resilience in a changing world.
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