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 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 articleKhan S, Albers J, Vorobyev A, et al., 2026,
Critical point drying of brain tissue for X-ray phase-contrast imaging.
, J Synchrotron RadiatX-ray phase-contrast tomography can efficiently image brain tissue at subcellular resolution. However, current sample preparation methods are not optimized to exploit the full potential of X-ray contrast mechanisms. Here we propose to replace interstitial material by air to enhance X-ray phase contrast of the ultrastructural features. Critical point drying (CPD) of heavy-metal-stained mouse brain tissue produced samples with preserved ultrastructure, a nanofoam-like material that remains compatible with follow-up conventional resin embedding. Using two synchrotron-based setups, namely, a high-throughput microtomography beamline and a nanoscale holographic tomography beamline, we found that CPD samples consistently showed 2-4× stronger phase-shift signal than samples embedded in resin. CPD offers a versatile route for preparing tissue for subcellular and ultrastructural-resolution X-ray imaging. It retains structural detail while improving signal, and is compatible with follow-up protocols involving femtosecond laser milling or electron microscopy, paving the path for biological tissue imaging beyond the mm3 scale.
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Journal articleZhou Y, Xu C, Awad Z, et al., 2026,
CRAC-DM: class relation-aware categorical diffusion model for surgical scene segmentation.
, Int J Comput Assist Radiol SurgPURPOSE: Accurate multi-class segmentation of surgical scenes remains challenging due to ambiguous anatomical boundaries and imaging artifacts. While diffusion-based segmentation methods have achieved good results, they rely on computationally heavy continuous diffusion processes. Recent discrete diffusion variants reduce computation but their performance is limited due to uniform noise, ignoring inter-class relationships that are crucial for generating semantically relevant training signals. To address this gap, we propose the class relation-aware categorical diffusion model (CRAC-DM). METHODS: CRAC-DM consists of three key components. In the forward process, we embed semantic class relationships for the first time when adding categorical noise via a class relation-aware transition matrix, biasing noise toward semantically similar categories to generate class-aware supervision signals. In the reverse process, we introduce a step-skipping categorical denoiser (S2D) tailored for discrete diffusion segmentation, enabling fast inference. To further boost inference, we propose a novel confidence-adaptive test time augmentation (TTA) that selectively refines regions of interest with low prediction confidence using entropy-weighted aggregation. RESULTS: The proposed CRAC-DM was evaluated on the publicly available CholecSeg8k and EndoVis18 datasets. It consistently outperformed state-of-the-art U-Net-, transformer-, and diffusion-based baselines, particularly on tissue segmentation, even for small and under-represented classes while significantly reducing inference time compared to diffusion baselines. CONCLUSION: By enhancing the forward process with inter-class similarity and improving the reverse process with a deterministic S2D and targeted TTA, CRAC-DM achieves superior segmentation accuracy, efficiency, and reliability, paving the way for practical deployment in computer-assisted surgery.
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Journal articleBackeljauw P, Tomlinson G, Smart LR, et al., 2026,
Growth and puberty in African children with sickle cell anemia treated with hydroxyurea.
, Blood AdvChildren with sickle cell anemia (SCA) have poor growth and pubertal development. REACH (Realizing Effectiveness Across Continents with Hydroxyurea, NCT01966731) is a prospective trial evaluating the feasibility, safety, and benefits of hydroxyurea at maximum tolerated dose (MTD) for children with SCA in sub-Saharan Africa. Children 1-10 years old at 4 sites received open-label hydroxyurea with longitudinal follow-up. Height, weight, and pubertal (Tanner) staging were collected at enrollment and sequentially over 7 years of treatment. Biomarkers included insulin-like growth factor-I (IGF-I), insulin-like growth factor binding protein-3 (IGFBP-3), luteinizing hormone (LH), follicle stimulating hormone (FSH), and anti-Mullerian hormone (AMH). Hydroxyurea commenced at an average (mean±1SD) age of 5.9±2.4 years (range 1.6-10.2) for girls (n=296) and 5.4±2.4 years (range 1.3-10.1) for boys (n=310). Using natural history SCA-specific reference curves, the mean weight-for-age Z-score improved from 0.47±0.90 at enrollment to 0.69±1.00 on hydroxyurea treatment. Height increased from 0.26±0.90 to 0.42±1.00 on treatment, and BMI from 0.46±1.00 to 0.85±1.20. IGF-I remained low in many participants: mean IGF-I was -1.5 SD at baseline and -1.4 SD at follow-up in girls, and -2.3 at baseline and -2.2 at follow-up in boys. Pubertal onset was delayed in 25-30% of children, with gradual progress on treatment. AMH was low (<2.5th percentile) in 4% of girls, while 52% of boys had low AMH at baseline and 28% at follow-up. Long-term hydroxyurea treatment at MTD is associated with beneficial effects on growth with improved weight and height, and does not negatively impact pubertal development in children with SCA in sub-Saharan Africa.
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Journal articleCalo J, Lo B, 2026,
Proof of Reasoning for Privacy-Enhanced Federated Blockchain Learning at the Edge
, IEEE Internet of Things Journal, Vol: 13, Pages: 12716-12723Consensus mechanisms are the core of any blockchain system. However, the majority of these mechanisms do not target federated learning (FL) directly, nor do they aid in the aggregation step. This article introduces proof of reasoning (PoR), a novel consensus mechanism specifically designed for FL using blockchain, aimed at preserving data privacy, defending against malicious attacks, and enhancing the validation of participating networks. Unlike generic blockchain consensus mechanisms commonly found in the literature, PoR integrates three distinct processes tailored for FL. First, a masked autoencoder (MAE) is trained to generate an encoder that functions as a feature map and obfuscates input data, rendering it resistant to human reconstruction and model inversion attacks. Second, a downstream classifier is trained at the edge, receiving input from the trained encoder. The downstream network's weights, a single encoded datapoint, the network's output, and the ground truth are then added to a block for federated aggregation. Lastly, this data facilitates the aggregation of all participating networks, enabling more complex and verifiable aggregation methods than previously possible. This three-stage process results in more robust networks with significantly reduced computational complexity, maintaining high accuracy by training only the downstream classifier at the edge. PoR scales to large Internet of Things (IoT) networks with low latency and storage growth, and adapts to evolving data, regulations, and network conditions.
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Journal articleKwasnicki RM, de Galbert L, Poon K, et al., 2026,
Validating a digital recovery tool for autologous breast reconstruction.
, J Plast Reconstr Aesthet Surg, Vol: 115, Pages: 225-233BACKGROUND: Recent research aims to leverage technology to further understand surgical recovery by using continuous data. Traditional metrics of readmission, flap failure, and patient-reported outcome measures are limited by poor accuracy and subjectivity. We aimed to validate smartphone-derived physical activity data to objectively measure and analyze trends in recovery following deep inferior epigastric perforator (DIEP) flap breast reconstruction. METHODS: A single-center, retrospective study was conducted. Eligible participants who underwent DIEP reconstruction downloaded a bespoke smartphone application, which retrieved data from 1 month preoperatively to 12 months postoperatively. Physical activity was compared and validated against wearable activity monitor data from a previous study. Temporal trends were visualized using mean daily activity values over predefined intervals. Univariable linear regression assessed associations between clinical variables and short-term recovery. RESULTS: Forty-one patients were included in the study. Wearable activity monitor and smartphone datasets (n=10) showed a positive correlation (0.6379, p=0.0105) demonstrating concurrent validity. Analysis of recovery in DIEP patients (n=34) demonstrated a median return to baseline activity at 27 days (IQR 12 days). Physical activity decreased after DIEP, with mean daily activity dropping to 18% of baseline in the first 2 weeks (SD=11%, p<0.0001) before improving to 107% at 8-12 weeks (SD=78%, p=0.9999). Immediate postoperative reconstruction (p=0.046) and lack of postoperative complications (p=0.0063), were short-term predictors of physical activity. CONCLUSION: This study validates smartphone physical activity as an objective recovery metric in DIEP reconstruction. Future applications include developing recovery prediction models for shared decision-making, implementing perioperative interventions, and postoperative monitoring.
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Journal articleRayner C, Smith N, Milne R, et al., 2026,
'What Do People With Long Covid Want From Healthcare Services?' A Qualitative Exploration From Lived Experience.
, Health Expect, Vol: 29BACKGROUND: Long COVID (LC) is a chronic, multisystem condition affecting millions globally, with significant personal, social and economic consequences. Despite increasing recognition of its impact, healthcare services for LC remain inconsistent with patients frequently encountering fragmented services, scepticism and delays leading to patient-voiced frustration. Therefore, understanding patient priorities is crucial for optimising service provision. OBJECTIVES: To explore what individuals with LC want from healthcare services-drawing on their lived experience and collaborative insights with clinicians and researchers, to inform principles for improving care delivery, barriers to access, expectations for service improvement, and the role of multidisciplinary care in managing LC. METHODS: A qualitative study using thematic analysis was conducted, incorporating multiple data sources, including semi-structured interviews, workshops, and a patient-led audit. Key themes were identified, focusing on healthcare access, clinical assessments, treatment options, and service organisation. STUDY PARTICIPANTS: Twenty-seven LC sufferers from the LOCOMOTION Patient Advisory Group (PAG) and Patient Advisory Network (PAN), along with clinicians and researchers involved in LC service provision across the United Kingdom, participated in the study. RESULTS: Three major themes emerged: (1) Who the services are for: Equity of access for all those with LC. Barriers such as stigma, inequitable access and lack of clinician awareness need to be addressed. (2) What services should do: Consistent and standardised assessments and diagnostic clarity-particularly for modifiable conditions like autonomic dysfunction-and an emphasis on the need for early medical intervention, not just rehabilitation. (3) How services should operate: Care should be coordinated, proactive and adaptable to evolving evidence. Patients should not be discharged without ongoing review. Multidisciplinary collaboration sho
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Journal articleRanque B, Tshilolo L, Williams TN, 2026,
The Epidemiology of Sickle Cell Disease in Sub-Saharan Africa: Current Knowledge and Gaps to be Filled.
, Am J Hematol, Vol: 101 Suppl 1, Pages: 5-16Sickle Cell Disease (SCD) is highly prevalent in sub-Saharan Africa. Epidemiological data remain sparse, but regional screening and research initiatives are expanding. Due to genetic, environmental, and socioeconomic factors, the disease course differs markedly from that in high-income countries. Although mortality is improving and can be further lowered with simple interventions, it remains high, especially among undiagnosed children. Genetic factors, poor healthcare infrastructure, and poverty contribute to disease severity. While recent collaborative programs like SickleInAfrica offer hope, national policies that foster the training of healthcare workers, newborn screening, and access to treatment are crucial to reducing the burden of SCD across the region.
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