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Fidock, Benjamin, Barker, Natasha, Balasubramanian, Nithin, Archer, Gareth, Fent, Graham, Al-Mohammad, Abdullah, Richardson, James, O'Toole, Laurence, Briffa, Norman, Rothman, Alexander, Van Der Geest, Rob, Hose, Rod, Wild, James M., Swift, Andrew J. and Garg, Pankaj 
ORCID: https://orcid.org/0000-0002-5483-169X
(2019)
A systematic review of 4D-flow MRI derived mitral regurgitation quantification methods.
Frontiers in Cardiovascular Medicine, 6.
ISSN 2297-055X
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Abstract
Background: Four-dimensional flow cardiac magnetic resonance (4D flow CMR) is an emerging non-invasive imaging technology that can be used to quantify mitral regurgitation (MR) volume. Current methods of quantification have demonstrated limitations in accurate analysis, particularly in difficult cases such as complex congenital heart disease. 4D flow CMR methods aim to circumvent these limitations and allow accurate quantification of MR volume even in complex cases. This systematic review aims to summarize the available literature on 4D flow CMR MR quantification methods and examine their ability to accurately classify MR severity. Methods: Structured searches were carried out on Medline and EMBASE in December 2018 to identify suitable research outcome studies. The titles and abstracts were screened for relevance, with a third adjudicator utilized when study suitability was uncertain. Results: Seven studies met the eligibility criteria and were included in the systematic review. The most widely used 4D flow MRI method was retrospective valve tracking (RVT) which was examined in five papers. The key finding of these papers was that RVT is a reliable and accurate method of regurgitant volume quantification. Conclusions: MR quantification through 4D flow MRI is both feasible and accurate. The evidence gathered suggests that for MR assessment, 4D flow MRI is potentially as accurate and reliable to echocardiography and may be complementary to this technique. Further work on MR quantification 4D flow image analysis is needed to determine the most accurate analysis technique and to demonstrate 4D flow MRI as a predictor of clinical outcome. PROSPERO Registration Number: CRD42019122837, http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42019122837
| Item Type: | Article |
|---|---|
| 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 04:52 |
| Last Modified: | 19 Oct 2023 03:09 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/82140 |
| DOI: | 10.3389/fcvm.2019.00103 |
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