Evidence map›Paper›PMID 33150707›Full record

ArticleNMR in biomedicine2021

Myocardial arterial spin labeling in systole and diastole using flow-sensitive alternating inversion recovery with parallel imaging and compressed sensing.

Markus Henningsson, Carl-Johan Carlhäll, Johan Kihlberg

Open access · hybridAbstract read
In one paragraph

Article in NMR in biomedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 29% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
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  3. Improved accuracy for myocardial blood flow mapping with deep learning-enabled CMR arterial spin labeling (DeepMASL): Validation by microsphere in vivo.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2025
    Article
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  5. Article
  6. 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

3 authors at 1 institution in 2 countries.

Markus HenningssonUnit for Cardiovascular Sciences, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.ORCID 0000-0001-6142-3005
Carl-Johan CarlhällUnit for Cardiovascular Sciences, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
Johan KihlbergCenter for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
Linköping University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative myocardial perfusion can be achieved without contrast agents using flow-sensitive alternating inversion recovery (FAIR) arterial spin labeling. However, FAIR has an intrinsically low sensitivity, which may be improved by mitigating the effects of physiological noise or by increasing the area of artifact-free myocardium. The aim of this study was to investigate if systolic FAIR may increase the amount of analyzable myocardium compared with diastolic FAIR and its effect on physiological noise. Furthermore, we compare parallel imaging acceleration with a factor of 2 with compressed sensing acceleration with a factor of 3 for systolic FAIR. Twelve healthy subjects were scanned during rest on a 3 T scanner using diastolic FAIR with parallel imaging factor 2 (FAIR-PI2

Indexed as

Signal Processing, Computer-AssistedAdultAngiographyCoronary VesselsData CompressionDiastoleFemaleHeart RateHemorheologyHumansImage Processing, Computer-AssistedMaleRestSpin LabelsSystoleSpin Labelsacquisition, cardiovascular MR, compressed sensing, myocardial perfusion, perfusion and permeability, perfusion spin labeling

Identifiers

PMID33150707
PMCPMC7816237
OpenAlexW3096237940

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.