Evidence map›Paper›PMID 34307496›Full record

ReviewFrontiers in cardiovascular medicine2021

Clinical Translation of Three-Dimensional Scar, Diffusion Tensor Imaging, Four-Dimensional Flow, and Quantitative Perfusion in Cardiac MRI: A Comprehensive Review.

Sophie Paddock, Vasiliki Tsampasian, Hosamadin Assadi, Bruno Calife Mota, Andrew J Swift, Amrit Chowdhary, Peter Swoboda, Eylem Levelt, Eva Sammut, Amardeep Dastidar and 10 more

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cardiovascular medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.1field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 19 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Atrial Cardiomyopathy: From Diagnosis to Treatment.Reviews in cardiovascular medicine · 2025
    Review
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Observational
  15. Review
  16. Diagnostic efficacy of serum ST2 in patients with ASC.Journal of clinical laboratory analysis · 2022
    Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors at 5 institutions in 1 country.

Sophie PaddockDepartment of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, United Kingdom.
Vasiliki TsampasianDepartment of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, United Kingdom.
Hosamadin AssadiDepartment of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom.
Bruno Calife MotaDepartment of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom.
Andrew J SwiftDepartment of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom.
Amrit ChowdharyMultidisciplinary Cardiovascular Research Centre & Division of Biomedical Imaging, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom.
Peter SwobodaMultidisciplinary Cardiovascular Research Centre & Division of Biomedical Imaging, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom.
Eylem LeveltMultidisciplinary Cardiovascular Research Centre & Division of Biomedical Imaging, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom.
Eva SammutBristol Heart Institute and Translational Biomedical Research Centre, Faculty of Health Science, University of Bristol, Bristol, United Kingdom.
Amardeep DastidarBristol Heart Institute and Translational Biomedical Research Centre, Faculty of Health Science, University of Bristol, Bristol, United Kingdom.
Jordi Broncano CabreroCardiothoracic Imaging Unit, Hospital San Juan De Dios, Ressalta, HT Medica, Córdoba, Spain.
Javier Royuela Del ValCardiothoracic Imaging Unit, Hospital San Juan De Dios, Ressalta, HT Medica, Córdoba, Spain.
Paul MalcolmDepartment of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, United Kingdom.
Julia SunDepartment of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom.
Alisdair RydingDepartment of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom.
Chris SawhDepartment of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom.
Richard GreenwoodDepartment of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom.
David HewsonDepartment of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom.
Vassilios VassiliouDepartment of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, United Kingdom.
Pankaj GargDepartment of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, United Kingdom.
Norfolk and Norwich University Hospital · GBUniversity of East Anglia · GBUniversity of Leeds · GBUniversity of Bristol · GBUniversity of Sheffield · GB

Funding

Wellcome Trust 205188/Z/16/Z
6 · The paper itself

Abstract

Cardiovascular magnetic resonance (CMR) imaging is a versatile tool that has established itself as the reference method for functional assessment and tissue characterisation. CMR helps to diagnose, monitor disease course and sub-phenotype disease states. Several emerging CMR methods have the potential to offer a personalised medicine approach to treatment. CMR tissue characterisation is used to assess myocardial oedema, inflammation or thrombus in various disease conditions. CMR derived scar maps have the potential to inform ablation therapy-both in atrial and ventricular arrhythmias. Quantitative CMR is pushing boundaries with motion corrections in tissue characterisation and first-pass perfusion. Advanced tissue characterisation by imaging the myocardial fibre orientation using diffusion tensor imaging (DTI), has also demonstrated novel insights in patients with cardiomyopathies. Enhanced flow assessment using four-dimensional flow (4D flow) CMR, where time is the fourth dimension, allows quantification of transvalvular flow to a high degree of accuracy for all four-valves within the same cardiac cycle. This review discusses these emerging methods and others in detail and gives the reader a foresight of how CMR will evolve into a powerful clinical tool in offering a precision medicine approach to treatment, diagnosis, and detection of disease.

Indexed as

cardiovascular magnetic resonancediffusion tensor imagingfour-dimensional flow imagingmyocardial fibrosistissue characterisation

Identifiers

PMID34307496
PMCPMC8292630
OpenAlexW3178092726

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.