Evidence map›Paper›PMID 36336794›Full record

ArticleMagnetic resonance in medicine2023

MR Multitasking-based multi-dimensional assessment of cardiovascular system (MT-MACS) with extended spatial coverage and water-fat separation.

Zhehao Hu, Jiayu Xiao, Xianglun Mao, Yibin Xie, Alan C Kwan, Shlee S Song, Michael W Fong, Alison G Wilcox, Debiao Li, Anthony G Christodoulou and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Magnetic resonance in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. The future of cardiovascular magnetic resonance: All-in-one vs. real-time (Part 1).Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2024
    Review
  4. 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

11 authors.

Zhehao HuDepartment of Radiology, University of Southern California, Los Angeles, California, USA.ORCID 0000-0002-5813-2925
Jiayu XiaoDepartment of Radiology, University of Southern California, Los Angeles, California, USA.
Xianglun MaoBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.ORCID 0000-0002-2745-7444
Yibin XieBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Alan C KwanBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Shlee S SongDepartment of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Michael W FongDivision of Cardiovascular Medicine, University of Southern California, Los Angeles, California, USA.
Alison G WilcoxDepartment of Radiology, University of Southern California, Los Angeles, California, USA.
Debiao LiBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Anthony G ChristodoulouBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.ORCID 0000-0002-9334-8684
Zhaoyang FanDepartment of Radiology, University of Southern California, Los Angeles, California, USA.ORCID 0000-0002-2693-0260

Funding

Motion-Resolved, Comprehensive Quantitative Tissue Characterization Using MR MultitaskingR01EB028146 · NIBIB · CEDARS-SINAI MEDICAL CENTER · PI CHRISTODOULOU, ANTHONY G, LI, DEBIAO · 2019 to 2022
$2.5M
NIBIB NIH HHS R01 EB028146
6 · The paper itself

Abstract

purposeTo extend the MR MultiTasking-based Multidimensional Assessment of Cardiovascular System (MT-MACS) technique with larger spatial coverage and water-fat separation for comprehensive aortocardiac assessment.

methodsMT-MACS adopts a low-rank tensor image model for 7D imaging, with three spatial dimensions for volumetric imaging, one cardiac motion dimension for cine imaging, one respiratory motion dimension for free-breathing imaging, one T2-prepared inversion recovery time dimension for multi-contrast assessment, and one T2*-decay time dimension for water-fat separation. Nine healthy subjects were recruited for the 3T study. Overall image quality was scored on bright-blood (BB), dark-blood (DB), and gray-blood (GB) contrasts using a 4-point scale (0-poor to 3-excellent) by two independent readers, and their interreader agreement was evaluated. Myocardial wall thickness and left ventricular ejection fraction (LVEF) were quantified on DB and BB contrasts, respectively. The agreement in these metrics between MT-MACS and conventional breath-held, electrocardiography-triggered 2D sequences were evaluated.

resultsMT-MACS provides both water-only and fat-only images with excellent image quality (average score = 3.725/3.780/3.835/3.890 for BB/DB/GB/fat-only images) and moderate to high interreader agreement (weighted Cohen's kappa value = 0.727/0.668/1.000/1.000 for BB/DB/GB/fat-only images). There were good to excellent agreements in myocardial wall thickness measurements (intraclass correlation coefficients [ICC] = 0.781/0.929/0.680/0.878 for left atria/left ventricle/right atria/right ventricle) and LVEF quantification (ICC = 0.716) between MT-MACS and 2D references. All measurements were within the literature range of healthy subjects.

conclusionThe refined MT-MACS technique provides multi-contrast, phase-resolved, and water-fat imaging of the aortocardiac systems and allows evaluation of anatomy and function. Clinical validation is warranted.

Indexed as

Imaging, Three-DimensionalWaterHeart VentriclesHumansMagnetic Resonance ImagingReproducibility of ResultsStroke VolumeVentricular Function, LeftWaterMR Multitaskingmulti-contrast imagingmulti-dimensional imagingphase-resolved imagingwater-fat separationwhole-heart MR

Identifiers

PMID36336794
PMCPMC9892247

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.