Evidence map›Paper›PMID 33035638›Full record

ArticleMagnetic resonance imaging2020

Validation of non-contrast multiple overlapping thin-slab 4D-flow cardiac magnetic resonance imaging.

Nina Rashedi, Luis Landeras, Victor Mor-Avi, Davide Genovese, Peng Lai, Haonan Wang, Kalie Kebed, Isla McClelland, Anja Brau, Martin Janich and 3 more

Abstract readValidation Study
In one paragraph

Article in Magnetic resonance imaging, 2020. 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. 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

13 authors.

Nina RashediDepartment of Medicine, University of Chicago Medicine, Chicago, IL, USA.
Luis LanderasDepartment of Medicine, University of Chicago Medicine, Chicago, IL, USA.
Victor Mor-AviDepartment of Medicine, University of Chicago Medicine, Chicago, IL, USA. Electronic address: vmoravi@bsd.uchicago.edu.
Davide GenoveseDepartment of Medicine, University of Chicago Medicine, Chicago, IL, USA; Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padua, Padua, Italy.
Peng LaiGeneral Electric Healthcare, Chicago, IL, USA.
Haonan WangGeneral Electric Healthcare, Chicago, IL, USA.
Kalie KebedDepartment of Medicine, University of Chicago Medicine, Chicago, IL, USA.
Isla McClellandDepartment of Medicine, University of Chicago Medicine, Chicago, IL, USA.
Anja BrauGeneral Electric Healthcare, Chicago, IL, USA.
Martin JanichGeneral Electric Healthcare, Chicago, IL, USA.
Karima AddetiaDepartment of Medicine, University of Chicago Medicine, Chicago, IL, USA.
Roberto M LangDepartment of Medicine, University of Chicago Medicine, Chicago, IL, USA.
Amit R PatelDepartment of Medicine, University of Chicago Medicine, Chicago, IL, USA.

Funding

MULTIDISCIPLINARY CARDIAC SCIENCEST32HL007381 · NHLBI · UNIVERSITY OF CHICAGO · PI JEANNE M DECARA, Yoav Gilad · 1985 to 2026
$12.5M
NHLBI NIH HHS T32 HL007381
6 · The paper itself

Abstract

backgroundCardiac magnetic resonance (CMR) flow quantification is typically performed using 2D phase-contrast (PC) imaging of a plane perpendicular to flow. 3D-PC imaging (4D-flow) allows offline quantification anywhere in a thick slab, but is often limited by suboptimal signal, potentially alleviated by contrast enhancement. We developed a non-contrast 4D-flow sequence, which acquires multiple overlapping thin slabs (MOTS) to minimize signal loss, and hypothesized that it could improve image quality, diagnostic accuracy, and aortic flow measurements compared to non-contrast single-slab approach.

methodsWe prospectively studied 20 patients referred for transesophageal echocardiography (TEE), who underwent CMR (GE, 3 T). 2D-PC images of the aortic valve and three 4D-flow datasets covering the heart were acquired, including single-slab, pre- and post-contrast, and non-contrast MOTS. Each 4D-flow dataset was interpreted blindly for ≥moderate valve disease and compared to TEE. Flow visualization through each valve was scored (0 to 4), and aortic-valve flow measured on each 4D-flow dataset and compared to 2D-PC reference.

resultsDiagnostic quality visualization was achieved with the pre- and post-contrast 4D-flow acquisitions in 25% and 100% valves, respectively (scores 0.9 ± 1.1 and 3.8 ± 0.5), and in 58% with the non-contrast MOTS (1.6 ± 1.1). Accuracy of detection of valve disease was 75%, 92% and 82%, respectively. Aortic flow measurements were possible in 53%, 95% and in 89% patients, respectively. The correlation between pre-contrast single-slab measurements and 2D-PC reference was weak (r = 0.21), but improved with both contrast enhancement (r = 0.71) and with MOTS (r = 0.67).

conclusionsAlthough non-contrast MOTS 4D-flow improves valve function visualization and diagnostic accuracy, a significant proportion of valves cannot be accurately assessed. However, aortic flow measurements using non-contrast MOTS is feasible and reaches similar accuracy to that of contrast-enhanced 4D-flow.

Indexed as

Magnetic Resonance ImagingAortaBlood Flow VelocityFemaleHeartHumansImaging, Three-DimensionalMaleMiddle AgedAortic flowContrast enhancementOffline analysisPhase contrast

Identifiers

PMID33035638
PMCPMC7931662

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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.