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• Journal article
  Zeyu T, Xing X, Wang G, Yang Get al., 2025,

  Enhancing super-resolution network efficacy in CT imaging: cost-effective simulation of training data

  , IEEE Open Journal of Engineering in Medicine and Biology, ISSN: 2644-1276

  Deep learning-based Generative Models have the potential to convert low-resolution CT images into high-resolution counterparts without long acquisition times and increased radiation exposure in thin-slice CT imaging. However, procuring appropriate training data for these Super-Resolution (SR) models is challenging. Previous SR research has simulated thick-slice CT images from thin-slice CT images to create training pairs. However, these methods either rely on simplistic interpolation techniques that lack realism or on sinogram reconstruction, which requires the release of raw data and complex reconstruction algorithms. Thus, we introduce a simple yet realistic method to generate thick CT images from thin-slice CT images, facilitating the creation of training pairs for SR algorithms. The training pairs produced by our method closely resemble real data distributions (PSNR=49.74 vs. 40.66, p<0.05). A multivariate Cox regression analysis involving thick slice CT images with lung fibrosis revealed that only the radiomics features extracted using our method demonstrated a significant correlation with mortality (HR=1.19 and HR=1.14, p<0.005). This paper represents the first to identify and address the challenge of generating appropriate paired training data for Deep Learning-based CT SR models, which enhances the efficacy and applicability of SR models in real-world scenarios.

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• Journal article
  Vano LJ, McCutcheon RA, Sedlacik J, Rutigliano G, Kaar SJ, Finelli V, Lobo MC, Berry A, Statton B, Fazlollahi A, Everall IP, Howes ODet al., 2025,

  The role of low subcortical iron, white matter myelin, and oligodendrocytes in schizophrenia: a quantitative susceptibility mapping and diffusion tensor imaging study

  , MOLECULAR PSYCHIATRY, ISSN: 1359-4184
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• Conference paper
  Patel KHK, Bajaj N, Statton BK, Bishop MJ, Stoks J, Li X, Sau A, Brezitski M, Ware JS, Purkayastha S, O'Regan D, Coronel R, Cluitmans M, Lambiase PD, Ng FSet al., 2025,

  WEIGHT LOSS REVERSES ADVERSE STRUCTURAL, ELECTROPHYSIOLOGICAL AND AUTONOMIC REMODELLING IN OBESITY

  , Publisher: OXFORD UNIV PRESS, Pages: i3-i3, ISSN: 0032-5473
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• Journal article
  Li S, Zhuang B, Cui C, He J, Ren Y, Wang H, Francone M, Yang G, Mohiaddin R, Lu M, Xu Let al., 2025,

  Prognostic significance of myocardial fibrosis in men with alcoholic cardiomyopathy: insights from cardiac MRI

  , EUROPEAN RADIOLOGY, Vol: 35, Pages: 5594-5603, ISSN: 0938-7994
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  • Citations: 1
• Journal article
  Vano LJ, McCutcheon RA, Sedlacik J, Kaar SJ, Rutigliano G, Nordio G, Finelli V, Townsend L, Berry A, Statton B, Fazlollahi A, Veronese M, Hopkins SC, Koblan KS, Everall IP, Howes ODet al., 2025,

  Reduced Brain Iron and Striatal Hyperdopaminergia in Schizophrenia: A Quantitative Susceptibility Mapping MRI and PET Study

  , AMERICAN JOURNAL OF PSYCHIATRY, Vol: 182, Pages: 830-839, ISSN: 0002-953X
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  • Citations: 3
• Journal article
  Ai R, Xiao X, Deng S, Yang N, Xing X, Watne LO, Wedatilake Y, Xie C, Selback G, Rubinsztein DC, Neerland BE, Palmer JE, Chen H, Niu Z, Yang G, Fang EFet al., 2025,

  Artificial intelligence in drug development for delirium and Alzheimer's disease

  , ACTA PHARMACEUTICA SINICA B, Vol: 15, Pages: 4386-4410, ISSN: 2211-3835
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• Journal article
  Teh I, Moulin K, Ferreira PF, Absil J, Afzali M, Agger P, Akbari B, Aletras AH, Aono S, Benton C, Bhattacharya S, Croisille P, De Bruecker Y, Dall'Armellina E, Ennis DB, Glessgen C, Glinska A, Haltmeier S, Hannum A, Hedström E, Hussein T, Jones S, Joy G, Kettless K, Kim WY, Kozerke S, Magat J, Muthupillai R, Nezafat R, Nielles-Vallespin S, Oshinski J, Ozenne V, Pennell DJ, Pettigrew R, Pierce I, Raman B, Sabisz A, Schneider JE, Sherman JH, Shetye A, Symons R, Thoma P, Treibel T, Tsuneta S, Vallee J-P, Vejlstrup N, Viallon M, Nguyen C, Scott AD, Stoeck CTet al., 2025,

  Multi-centre investigation of cardiac diffusion tensor imaging in healthy volunteers by SCMR Cardiac Diffusion Special Interest Group NETwork (SIGNET)

  , Journal of Cardiovascular Magnetic Resonance, ISSN: 1097-6647

  BACKGROUND: Cardiac diffusion tensor imaging (cDTI) is an emerging technique for microstructural characterization of the heart and has shown clinical potential in a range of cardiomyopathies. However, there is substantial variation reported for in vivo cDTI results across the literature, and sensitivity of cDTI to differences in imaging sites, scanners, acquisition protocols and post-processing methods remains incompletely understood. METHODS: SIGNET is a prospective multi-centre, observational study in travelling and non-travelling healthy volunteers. The study was initiated by the executive board of the SCMR Cardiac Diffusion Special Interest Group (SIG) as a follow up to a previous multi-centre study on phantom validation of cardiac DTI and a recently published SCMR consensus statement on cardiac diffusion MRI. The study has been developed by the Project Management Committee in consultation with the SCMR Cardiac Diffusion SIG, which includes international experts in cardiac diffusion MRI. To date, more than 20 international institutions have engaged with the study, including sites that are new to cardiac DTI, making this the largest collaborative effort in the field. DISCUSSION: SIGNET will provide important information about the key sources of variation in cardiac DTI. This will help rationalise strategies for addressing and minimising such variation. Harmonisation of protocols in this and future studies will underpin efforts to translate cardiac DTI for clinical application.

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• Journal article
  Toma T, Tekle K, Smith J, Quest R, Kelly R, Lord C, Alavi Aet al., 2025,

  Enhancing the detection of paediatric ankle fractures with zero echo time imaging: A case of an occult salter-harris III ankle fracture

  , EMERGENCY RADIOLOGY, ISSN: 1070-3004
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• Journal article
  Zhu J, Liao Y, Chen Y, Gao F, Li R, Yang G, Lai X, Chen Jet al., 2025,

  Multimodal MRI-Based Glioma Segmentation and MGMT Promoter Methylation Status Prediction Using Multitask Learning Architecture

  , INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, Vol: 35, ISSN: 0899-9457
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• Journal article
  Zahid U, Osugo M, Selvaggi P, Lythgoe DJ, Fortunato C, Diederen K, Kiemes A, Wall MB, Whitehurst T, Onwordi EC, Statton B, Berry A, Dimitrov M, Lau R, McCutcheon RA, Murray R, Marques TR, Mehta MA, Howes ODet al., 2025,

  The effects of dopamine receptor antagonist and partial agonist antipsychotics on the glutamatergic system: double-blind, randomised, placebo-controlled <SUP>1</SUP>H-MRS cross-over study in healthy volunteers

  , BRITISH JOURNAL OF PSYCHIATRY, ISSN: 0007-1250
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