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Archer, Gareth T., Elhawaz, Alaa, Barker, Natasha, Fidock, Benjamin, Rothman, Alexander, van der Geest, R. J., Hose, Rod, Briffa, Norman, Hall, Ian R., Grech, Ever, Bissell, Malenka, Al-Mohammad, Abdallah, Treibel, Thomas A., Swift, Andrew J., Wild, James M. and Garg, Pankaj 
ORCID: https://orcid.org/0000-0002-5483-169X
(2020)
Validation of four-dimensional flow cardiovascular magnetic resonance for aortic stenosis assessment.
Scientific Reports, 10.
ISSN 2045-2322
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Abstract
The management of patients with aortic stenosis (AS) crucially depends on accurate diagnosis. The main aim of this study were to validate the four-dimensional flow (4D flow) cardiovascular magnetic resonance (CMR) methods for AS assessment. Eighteen patients with clinically severe AS were recruited. All patients had pre-valve intervention 6MWT, echocardiography and CMR with 4D flow. Of these, ten patients had a surgical valve replacement, and eight patients had successful transcatheter aortic valve implantation (TAVI). TAVI patients had invasive pressure gradient assessments. A repeat assessment was performed at 3–4 months to assess the remodelling response. The peak pressure gradient by 4D flow was comparable to an invasive pressure gradient (54 ± 26 mmHG vs 50 ± 34 mmHg, P = 0.67). However, Doppler yielded significantly higher pressure gradient compared to invasive assessment (61 ± 32 mmHG vs 50 ± 34 mmHg, P = 0.0002). 6MWT was associated with 4D flow CMR derived pressure gradient (r = −0.45, P = 0.01) and EOA (r = 0.54, P < 0.01) but only with Doppler EOA (r = 0.45, P = 0.01). Left ventricular mass regression was better associated with 4D flow derived pressure gradient change (r = 0.64, P = 0.04). 4D flow CMR offers an alternative method for non-invasive assessment of AS. In addition, 4D flow derived valve metrics have a superior association to prognostically relevant 6MWT and LV mass regression than echocardiography.
| Item Type: | Article |
|---|---|
| Additional Information: | Author acknowledgements: We thank the staff of the MRI unit at the University of Sheffield in facilitating all the CMR scans. In addition, we thank all the staff at the Cardiothoracic Department, Sheffield Teaching Hospitals NHS Foundation Trust for their support and help during this study. Funding Information: This work was supported in part by EurValve (European Union funding) (Personalised Decision Support for Heart Valve Disease), Project Number: H2020 PHC-30–2015, 689617. AR was supported by Clinical Research Career Development Fellowships from the Wellcome Trust (206632/Z/17/Z). AS was supported by the Wellcome Trust (205188/Z/16/Z). PG was supported by the Academy of Sciences Starter Grant (SGL018\1100). Imaging infrastructure was supported by MRC and BHF funding MR/M008894/1. |
| Faculty \ School: | Faculty of Medicine and Health Sciences > Norwich Medical School |
| UEA Research Groups: | Faculty of Medicine and Health Sciences > Research Centres > Metabolic Health |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 17 Nov 2021 04:51 |
| Last Modified: | 23 Oct 2024 23:57 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/82135 |
| DOI: | 10.1038/s41598-020-66659-6 |
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