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Mehmood Z, Assadi H, Grafton-Clarke C, Li R, Matthews G, Alabed S, Girling R, Underwood V, Kasmai B, Zhao X, Ricci F, Zhong L, Aung N, Petersen SE, Swift AJ, Vassiliou VS, Cavalcante J, Geest RJVD, Garg P. Validation of 2D flow MRI for helical and vortical flows. Open Heart 2024; 11:e002451. [PMID: 38458769 PMCID: PMC10928773 DOI: 10.1136/openhrt-2023-002451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 11/09/2023] [Indexed: 03/10/2024] Open
Abstract
PURPOSE The main objective of this study was to develop two-dimensional (2D) phase contrast (PC) methods to quantify the helicity and vorticity of blood flow in the aortic root. METHODS This proof-of-concept study used four-dimensional (4D) flow cardiovascular MR (4D flow CMR) data of five healthy controls, five patients with heart failure with preserved ejection fraction and five patients with aortic stenosis (AS). A PC through-plane generated by 4D flow data was treated as a 2D PC plane and compared with the original 4D flow. Visual assessment of flow vectors was used to assess helicity and vorticity. We quantified flow displacement (FD), systolic flow reversal ratio (sFRR) and rotational angle (RA) using 2D PC. RESULTS For visual vortex flow presence near the inner curvature of the ascending aortic root on 4D flow CMR, sFRR demonstrated an area under the curve (AUC) of 0.955, p<0.001. A threshold of >8% for sFRR had a sensitivity of 82% and specificity of 100% for visual vortex presence. In addition, the average late systolic FD, a marker of flow eccentricity, also demonstrated an AUC of 0.909, p<0.001 for visual vortex flow. Manual systolic rotational flow angle change (ΔsRA) demonstrated excellent association with semiautomated ΔsRA (r=0.99, 95% CI 0.9907 to 0.999, p<0.001). In reproducibility testing, average systolic FD (FDsavg) showed a minimal bias at 1.28% with a high intraclass correlation coefficient (ICC=0.92). Similarly, sFRR had a minimal bias of 1.14% with an ICC of 0.96. ΔsRA demonstrated an acceptable bias of 5.72°-and an ICC of 0.99. CONCLUSION 2D PC flow imaging can possibly quantify blood flow helicity (ΔRA) and vorticity (FRR). These imaging biomarkers of flow helicity and vorticity demonstrate high reproducibility for clinical adoption. TRIALS REGISTRATION NUMBER NCT05114785.
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Affiliation(s)
- Zia Mehmood
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Hosamadin Assadi
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
- Department of Cardiovascular and Metabolic Health, University of East Anglia Norwich Medical School, Norwich, UK
| | - Ciaran Grafton-Clarke
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
- Department of Cardiovascular and Metabolic Health, University of East Anglia, Norwich, UK
| | - Rui Li
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
- Department of Cardiovascular and Metabolic Health, University of East Anglia, Norwich, UK
| | - Gareth Matthews
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
- Department of Cardiovascular and Metabolic Health, University of East Anglia, Norwich, UK
| | - Samer Alabed
- Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Rebekah Girling
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Victoria Underwood
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Bahman Kasmai
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
- Department of Cardiovascular and Metabolic Health, University of East Anglia, Norwich, UK
| | | | - Fabrizio Ricci
- Neuroscience, Imaging and Clinical Sciences, Gabriele d'Annunzio University of Chieti and Pescara, Chieti Scalo, Italy
| | | | - Nay Aung
- Queen Mary University of London, London, UK
| | - Steffen Erhard Petersen
- Advanced Cardiovascular Imaging William Harvey Research Institute, The London Chest Hospital, London, UK
| | | | - Vassilios S Vassiliou
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
- Department of Cardiovascular and Metabolic Health, University of East Anglia, Norwich, UK
| | - João Cavalcante
- Cardiovascular, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | | | - Pankaj Garg
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
- Department of Cardiovascular and Metabolic Health, University of East Anglia, Norwich, UK
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Mehmood Z, Assadi H, Li R, Kasmai B, Matthews G, Grafton-Clarke C, Sanz-Cepero A, Zhao X, Zhong L, Aung N, Skinner K, Hadinnapola C, Swoboda P, Swift AJ, Vassiliou VS, Miller C, van der Geest RJ, Peterson S, Garg P. Aortic flow is abnormal in HFpEF. Wellcome Open Res 2024; 8:577. [PMID: 38495400 PMCID: PMC10940846 DOI: 10.12688/wellcomeopenres.20192.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/05/2024] [Indexed: 03/19/2024] Open
Abstract
Aims Turbulent aortic flow makes the cardiovascular system less effective. It remains unknown if patients with heart failure with preserved ejection fraction (HFpEF) have disturbed aortic flow. This study sought to investigate advanced markers of aortic flow disturbances in HFpEF. Methods This case-controlled observational study used four-dimensional flow cardiovascular magnetic resonance derived, two-dimensional phase-contrast reformatted plane data at an orthogonal plane just above the sino-tubular junction. We recruited 10 young healthy controls (HCs), 10 old HCs and 23 patients with HFpEF. We analysed average systolic aortic flow displacement (FDsavg), systolic flow reversal ratio (sFRR) and pulse wave velocity (PWV). In a sub-group analysis, we compared old HCs versus age-gender-matched HFpEF (N=10). Results Differences were significant in mean age (P<0.001) among young HCs (22.9±3.5 years), old HCs (60.5±10.2 years) and HFpEF patients (73.7±9.7 years). FDsavg, sFRR and PWV varied significantly (P<0.001) in young HCs (8±4%, 2±2%, 4±2m/s), old HCs (16±5%, 7±6%, 11±8m/s), and HFpEF patients (23±10%, 11±10%, 8±3). No significant PWV differences existed between old HCs and HFpEF.HFpEF had significantly higher FDsavg versus old HCs (23±10% vs 16±5%, P<0.001). A FDsavg > 17.7% achieved 74% sensitivity, 70% specificity for differentiating them. sFRR was notably higher in HFpEF (11±10% vs 7±6%, P<0.001). A sFRR > 7.3% yielded 78% sensitivity, 70% specificity in differentiating these groups. In sub-group analysis, FDsavg remained distinctly elevated in HFpEF (22.4±9.7% vs 16±4.9%, P=0.029). FDsavg of >16% showed 100% sensitivity and 70% specificity (P=0.01). Similarly, sFRR remained significantly higher in HFpEF (11.3±9.5% vs 6.6±6.4%, P=0.007). A sFRR of >7.2% showed 100% sensitivity and 60% specificity (P<0.001). Conclusion Aortic flow haemodynamics namely FDsavg and sFRR are significantly affected in ageing and HFpEF patients.
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Affiliation(s)
- Zia Mehmood
- Department of Cardiology, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, Norfolk, NR4 7UY, UK
| | - Hosamadin Assadi
- Department of Cardiology, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, Norfolk, NR4 7UY, UK
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, Norfolk, NR4 7TJ, UK
| | - Rui Li
- Department of Cardiology, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, Norfolk, NR4 7UY, UK
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, Norfolk, NR4 7TJ, UK
| | - Bahman Kasmai
- Department of Cardiology, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, Norfolk, NR4 7UY, UK
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, Norfolk, NR4 7TJ, UK
| | - Gareth Matthews
- Department of Cardiology, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, Norfolk, NR4 7UY, UK
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, Norfolk, NR4 7TJ, UK
| | - Ciaran Grafton-Clarke
- Department of Cardiology, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, Norfolk, NR4 7UY, UK
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, Norfolk, NR4 7TJ, UK
| | - Aureo Sanz-Cepero
- Department of Cardiology, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, Norfolk, NR4 7UY, UK
| | - Xiaodan Zhao
- National Heart Research Institute, National Heart Centre Singapore, Singapore, 169609, Singapore
| | - Liang Zhong
- National Heart Research Institute, National Heart Centre Singapore, Singapore, 169609, Singapore
- Cardiovascular Sciences Academic Clinical Program & Cardiovascular Metabolic Disorder Program, Duke National University of Singapore Medical School, Singapore, 169857, Singapore
- Department of Biomedical Engineering, National University of Singapore, Singapore, 117583, Singapore
| | - Nay Aung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, EC1A 7BS, UK
| | - Kristian Skinner
- Department of Cardiology, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, Norfolk, NR4 7UY, UK
| | - Charaka Hadinnapola
- Department of Cardiology, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, Norfolk, NR4 7UY, UK
| | - Peter Swoboda
- Division of Biomedical Imaging, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK
| | - Andrew J. Swift
- Department of Infection, Immunity & Cardiovascular Disease, The University of Sheffield, Sheffield, UK
| | - Vassilios S Vassiliou
- Department of Cardiology, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, Norfolk, NR4 7UY, UK
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, Norfolk, NR4 7TJ, UK
| | - Christopher Miller
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
| | - Rob J. van der Geest
- Department of Radiology, Division of Image Processing, Leiden University Medical Center, Leiden, 2300 RC, The Netherlands
| | - Steffen Peterson
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, EC1A 7BS, UK
| | - Pankaj Garg
- Department of Cardiology, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, Norfolk, NR4 7UY, UK
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, Norfolk, NR4 7TJ, UK
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Assadi H, Matthews G, Zhao X, Li R, Alabed S, Grafton-Clarke C, Mehmood Z, Kasmai B, Limbachia V, Gosling R, Yashoda GK, Halliday I, Swoboda P, Ripley DP, Zhong L, Vassiliou VS, Swift AJ, Geest RJVD, Garg P. Cardiac MR modelling of systolic and diastolic blood pressure. Open Heart 2023; 10:e002484. [PMID: 38114194 DOI: 10.1136/openhrt-2023-002484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 11/01/2023] [Indexed: 12/21/2023] Open
Abstract
AIMS Blood pressure (BP) is a crucial factor in cardiovascular health and can affect cardiac imaging assessments. However, standard outpatient cardiovascular MR (CMR) imaging procedures do not typically include BP measurements prior to image acquisition. This study proposes that brachial systolic BP (SBP) and diastolic BP (DBP) can be modelled using patient characteristics and CMR data. METHODS In this multicentre study, 57 patients from the PREFER-CMR registry and 163 patients from other registries were used as the derivation cohort. All subjects had their brachial SBP and DBP measured using a sphygmomanometer. Multivariate linear regression analysis was applied to predict brachial BP. The model was subsequently validated in a cohort of 169 healthy individuals. RESULTS Age and left ventricular ejection fraction were associated with SBP. Aortic forward flow, body surface area and left ventricular mass index were associated with DBP. When applied to the validation cohort, the correlation coefficient between CMR-derived SBP and brachial SBP was (r=0.16, 95% CI 0.011 to 0.305, p=0.03), and CMR-derived DBP and brachial DBP was (r=0.27, 95% CI 0.122 to 0.403, p=0.0004). The area under the curve (AUC) for CMR-derived SBP to predict SBP>120 mmHg was 0.59, p=0.038. Moreover, CMR-derived DBP to predict DBP>80 mmHg had an AUC of 0.64, p=0.002. CONCLUSION CMR-derived SBP and DBP models can estimate brachial SBP and DBP. Such models may allow efficient prospective collection, as well as retrospective estimation of BP, which should be incorporated into assessments due to its critical effect on load-dependent parameters.
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Affiliation(s)
- Hosamadin Assadi
- Department of Cardiovascular and Metabolic Health, University of East Anglia, Norwich, UK
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Gareth Matthews
- Department of Cardiovascular and Metabolic Health, University of East Anglia, Norwich, UK
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Xiaodan Zhao
- National Heart Research Institute, National Heart Centre, Singapore
| | - Rui Li
- Department of Cardiovascular and Metabolic Health, University of East Anglia, Norwich, UK
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Samer Alabed
- Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Ciaran Grafton-Clarke
- Department of Cardiovascular and Metabolic Health, University of East Anglia, Norwich, UK
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Zia Mehmood
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Bahman Kasmai
- Department of Cardiovascular and Metabolic Health, University of East Anglia, Norwich, UK
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Vaishali Limbachia
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Rebecca Gosling
- Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | | | - Ian Halliday
- Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | | | - David Paul Ripley
- Department of Cardiology, Northumbria Specialist Emergency Care Hospital, Cramlington, UK
| | - Liang Zhong
- National Heart Research Institute, National Heart Centre, Singapore
- Cardiovascular Science Academic Program, Duke-NUS Medical School, Singapore
| | - Vassilios S Vassiliou
- Department of Cardiovascular and Metabolic Health, University of East Anglia, Norwich, UK
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | - Andrew J Swift
- Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Rob J van der Geest
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Pankaj Garg
- Department of Cardiovascular and Metabolic Health, University of East Anglia, Norwich, UK
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
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4
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Assadi H, Uthayachandran B, Li R, Wardley J, Nyi TH, Grafton-Clarke C, Swift AJ, Solana AB, Aben JP, Thampi K, Hewson D, Sawh C, Greenwood R, Hughes M, Kasmai B, Zhong L, Flather M, Vassiliou VS, Garg P. Kat-ARC accelerated 4D flow CMR: clinical validation for transvalvular flow and peak velocity assessment. Eur Radiol Exp 2022; 6:46. [PMID: 36131185 PMCID: PMC9492816 DOI: 10.1186/s41747-022-00299-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 07/24/2022] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND To validate the k-adaptive-t autocalibrating reconstruction for Cartesian sampling (kat-ARC), an exclusive sparse reconstruction technique for four-dimensional (4D) flow cardiac magnetic resonance (CMR) using conservation of mass principle applied to transvalvular flow. METHODS This observational retrospective study (2020/21-075) was approved by the local ethics committee at the University of East Anglia. Consent was waived. Thirty-five patients who had a clinical CMR scan were included. CMR protocol included cine and 4D flow using Kat-ARC acceleration factor 6. No respiratory navigation was applied. For validation, the agreement between mitral net flow (MNF) and the aortic net flow (ANF) was investigated. Additionally, we checked the agreement between peak aortic valve velocity derived by 4D flow and that derived by continuous-wave Doppler echocardiography in 20 patients. RESULTS The median age of our patient population was 63 years (interquartile range [IQR] 54-73), and 18/35 (51%) were male. Seventeen (49%) patients had mitral regurgitation, and seven (20%) patients had aortic regurgitation. Mean acquisition time was 8 ± 4 min. MNF and ANF were comparable: 60 mL (51-78) versus 63 mL (57-77), p = 0.310). There was an association between MNF and ANF (rho = 0.58, p < 0.001). Peak aortic valve velocity by Doppler and 4D flow were comparable (1.40 m/s, [1.30-1.75] versus 1.46 m/s [1.25-2.11], p = 0.602) and also correlated with each other (rho = 0.77, p < 0.001). CONCLUSIONS Kat-ARC accelerated 4D flow CMR quantified transvalvular flow in accordance with the conservation of mass principle and is primed for clinical translation.
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Affiliation(s)
- Hosamadin Assadi
- grid.8273.e0000 0001 1092 7967University of East Anglia, Norwich Medical School, Norfolk, UK ,grid.240367.40000 0004 0445 7876Norfolk and Norwich University Hospitals NHS Foundation Trust, Norfolk, UK
| | - Bhalraam Uthayachandran
- grid.8241.f0000 0004 0397 2876Division of Molecular and Clinical Medicine, University of Dundee, Dundee, UK
| | - Rui Li
- grid.8273.e0000 0001 1092 7967University of East Anglia, Norwich Medical School, Norfolk, UK ,grid.240367.40000 0004 0445 7876Norfolk and Norwich University Hospitals NHS Foundation Trust, Norfolk, UK
| | - James Wardley
- grid.8273.e0000 0001 1092 7967University of East Anglia, Norwich Medical School, Norfolk, UK ,grid.240367.40000 0004 0445 7876Norfolk and Norwich University Hospitals NHS Foundation Trust, Norfolk, UK
| | - Tha H. Nyi
- grid.240367.40000 0004 0445 7876Norfolk and Norwich University Hospitals NHS Foundation Trust, Norfolk, UK
| | - Ciaran Grafton-Clarke
- grid.240367.40000 0004 0445 7876Norfolk and Norwich University Hospitals NHS Foundation Trust, Norfolk, UK
| | - Andrew J. Swift
- grid.31410.370000 0000 9422 8284Department of Infection, Immunity and Cardiovascular disease, University of Sheffield Medical School and Sheffield Teaching Hospitals NHS Trust, Sheffield, UK
| | | | | | - Kurian Thampi
- grid.240367.40000 0004 0445 7876Norfolk and Norwich University Hospitals NHS Foundation Trust, Norfolk, UK
| | - David Hewson
- grid.240367.40000 0004 0445 7876Norfolk and Norwich University Hospitals NHS Foundation Trust, Norfolk, UK
| | - Chris Sawh
- grid.240367.40000 0004 0445 7876Norfolk and Norwich University Hospitals NHS Foundation Trust, Norfolk, UK
| | - Richard Greenwood
- grid.240367.40000 0004 0445 7876Norfolk and Norwich University Hospitals NHS Foundation Trust, Norfolk, UK
| | - Marina Hughes
- grid.240367.40000 0004 0445 7876Norfolk and Norwich University Hospitals NHS Foundation Trust, Norfolk, UK
| | - Bahman Kasmai
- grid.8273.e0000 0001 1092 7967University of East Anglia, Norwich Medical School, Norfolk, UK ,grid.240367.40000 0004 0445 7876Norfolk and Norwich University Hospitals NHS Foundation Trust, Norfolk, UK
| | - Liang Zhong
- grid.419385.20000 0004 0620 9905National Heart Centre Singapore, 5 Hospital Drive, Singapore, Singapore ,grid.428397.30000 0004 0385 0924Duke-NUS Medical School, 8 College Road, Singapore, Singapore
| | - Marcus Flather
- grid.8273.e0000 0001 1092 7967University of East Anglia, Norwich Medical School, Norfolk, UK ,grid.240367.40000 0004 0445 7876Norfolk and Norwich University Hospitals NHS Foundation Trust, Norfolk, UK
| | - Vassilios S. Vassiliou
- grid.8273.e0000 0001 1092 7967University of East Anglia, Norwich Medical School, Norfolk, UK ,grid.240367.40000 0004 0445 7876Norfolk and Norwich University Hospitals NHS Foundation Trust, Norfolk, UK
| | - Pankaj Garg
- grid.8273.e0000 0001 1092 7967University of East Anglia, Norwich Medical School, Norfolk, UK ,grid.240367.40000 0004 0445 7876Norfolk and Norwich University Hospitals NHS Foundation Trust, Norfolk, UK ,grid.31410.370000 0000 9422 8284Department of Infection, Immunity and Cardiovascular disease, University of Sheffield Medical School and Sheffield Teaching Hospitals NHS Trust, Sheffield, UK
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