Evidence map›Paper›PMID 40833175›Full record

Observational studyJournal of magnetic resonance imaging : JMRI2026

4D Flow MRI Velocity and Turbulence Mapping in Mild Valvular Heart Disease.

Tamara Bianchessi, Chiara Trenti, Carl-Johan Carlhäll, Tino Ebbers, Jan Engvall, Farkas Vanky, Federica Viola, Petter Dyverfeldt

Abstract readObservational Study
In one paragraph

Observational study in Journal of magnetic resonance imaging : JMRI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 4D Flow MRI Velocity and Turbulence Mapping in Mild Valvular Heart Disease.Journal of magnetic resonance imaging : JMRI · 2026
    Observational
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

8 authors.

Tamara BianchessiDivision of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.ORCID https://orcid.org/0000-0001-9709-803X
Chiara TrentiDivision of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
Carl-Johan CarlhällDivision of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
Tino EbbersDivision of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.ORCID https://orcid.org/0000-0003-1395-8296
Jan EngvallCenter for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.ORCID https://orcid.org/0000-0002-5716-5098
Farkas VankyDivision of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
Federica ViolaDivision of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.ORCID https://orcid.org/0000-0002-0354-7680
Petter DyverfeldtDivision of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.

Funding

ALF Grants (Region Östergötland)EU (FP7) Framework ProgramHjärt-LungfondenMedical Faculty at Linköping UniversityMedical Research Council of Southeast Sweden (FORSS)Strategic Research Area in Circulation and Metabolism at Linköping UniversityVetenskapsrådet
6 · The paper itself

Abstract

backgroundValvular heart disease (VHD) commonly leads to the development of turbulent blood flow. Turbulent kinetic energy (TKE), measured with 4D flow MRI, may be a complement to current metrics for early identification of VHD. PURPOSE: To investigate TKE as a marker of VHD in relation to flow velocity and cardiovascular geometry. STUDY TYPE: Retrospective observational cross-sectional. POPULATION: Twenty controls and 106 subjects with VHDs, including mitral regurgitation, aortic regurgitation, pulmonary regurgitation, tricuspid regurgitation, and aortic stenosis. FIELD STRENGTH/SEQUENCES: Four-dimensional flow MRI using a spoiled gradient-echo phase-contrast sequence with asymmetric 4-point motion encoding at 1.5 or 3 T. ASSESSMENT: Time-resolved segmentations of the left and right ventricles (LV, RV), atria (LA, RA), and aorta were performed. Total and maximum TKE, maximum and average velocity, and diameters were evaluated in each. Correlations between TKE, velocity, and diameter were assessed, along with group differences between VHD subjects and controls. STATISTICAL TESTS: Student's t-test, Wilcoxon rank-sum test, chi-squared test, Pearson's correlation, two-way analysis of covariance. A p value < 0.05 was considered significant.

resultsTotal and maximum TKE correlated significantly with maximum velocity (r = 0.45-0.76) and averaged velocity (r = 0.22-0.44) and less strongly with diameters for aorta, LV, LA, and RV (r = 0.18-0.37). Compared to controls, total and maximum aortic TKE were significantly higher in aortic stenosis (3.8 vs. 1.6 mJ; 291.7 vs. 133.7 J/m DATA

conclusionTKE is elevated in mild VHD. When evaluated alongside velocity as a marker for VHD, TKE may be more discriminative. Consequently, it has potential to be a hemodynamic marker of early VHD conveying complementary information to velocity. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 1.

Indexed as

Heart Valve DiseasesImaging, Three-DimensionalMagnetic Resonance ImagingAdultAgedBlood Flow VelocityCross-Sectional StudiesFemaleHeart VentriclesHumansMaleMiddle AgedRetrospective Studies4D flow MRIturbulent kinetic energyvalvular heart disease

Identifiers

PMID40833175
PMCPMC12706709

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.