Evidence map›Paper›PMID 30237910›Full record

ArticleNature biomedical engineering2018

Magnetic resonance multitasking for motion-resolved quantitative cardiovascular imaging.

Anthony G Christodoulou, Jaime L Shaw, Christopher Nguyen, Qi Yang, Yibin Xie, Nan Wang, Debiao Li

Open access · greenAbstract read
In one paragraph

Article in Nature biomedical engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 184 papers.

0numbers the graph read from it
0cells of the map it votes in
184citing papers in PubMed
20.3field-weighted citation impact, top 1% 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

184 citing papers in PubMed, 314 citations in OpenAlex.

  1. Combined ADC and TMagnetic resonance in medicine · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Cardiac MR Fingerprinting at 0.55T Using a Deep Image Prior for Joint TJournal of magnetic resonance imaging : JMRI · 2026
    Article
  11. Article
  12. Motion Mitigation Techniques for Abdominal and Cardiac MR Imaging.Journal of magnetic resonance imaging : JMRI · 2026
    Review
  13. Deep learning in fetal, infant, and toddler neuroimaging research.Developmental cognitive neuroscience · 2026
    Review
  14. Article
  15. Article
  16. Abdominal simultaneous 3D water TMagnetic resonance in medicine · 2026
    Article
  17. Article
  18. Article
  19. Article
  20. Article

124 more citing papers are in PubMed but not listed here.

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

7 authors at 1 institution in 2 countries.

Anthony G ChristodoulouBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0002-9334-8684
Jaime L ShawBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0003-2730-5982
Christopher NguyenBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0003-1475-2329
Qi YangBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Yibin XieBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Nan WangBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0002-7616-8083
Debiao LiBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Debiao.Li@cshs.org.
Cedars-Sinai Medical Center · US

Funding

Training in Advanced Heart Disease ResearchT32HL116273 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI Joshua I Goldhaber, EDUARDO MARBAN · 2013 to 2026
$5.6M
Whole-Heart Myocardial Blood Flow Quantification Using MRIR01HL124649 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI LI, DEBIAO · 2015 to 2018
$3.3M
NHLBI NIH HHS R01 HL124649NHLBI NIH HHS T32 HL116273
6 · The paper itself

Abstract

Quantitative cardiovascular magnetic resonance (CMR) imaging can be used to characterize fibrosis, oedema, ischaemia, inflammation and other disease conditions. However, the need to reduce artefacts arising from body motion through a combination of electrocardiography (ECG) control, respiration control, and contrast-weighting selection makes CMR exams lengthy. Here, we show that physiological motions and other dynamic processes can be conceptualized as multiple time dimensions that can be resolved via low-rank tensor imaging, allowing for motion-resolved quantitative imaging with up to four time dimensions. This continuous-acquisition approach, which we name cardiovascular MR multitasking, captures - rather than avoids - motion, relaxation and other dynamics to efficiently perform quantitative CMR without the use of ECG triggering or breath holds. We demonstrate that CMR multitasking allows for

Identifiers

PMID30237910
PMCPMC6141200
OpenAlexW2797196654

What OpenQuestion holds

Textmetadata
LicenceTDM
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.