Evidence map›Paper›PMID 38084378›Full record

ArticleMagnetic resonance in medicine2024

Quantitative

Xiao-Hong Zhu, Wei Chen

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Magnetic resonance in medicine, 2024. 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
0.2field-weighted citation impact, top 38% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  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

2 authors at 1 institution in 1 country.

Xiao-Hong ZhuCenter for Magnetic Resonance Research, Radiology Department, University of Minnesota, Minneapolis, Minnesota, USA.
Wei ChenCenter for Magnetic Resonance Research, Radiology Department, University of Minnesota, Minneapolis, Minnesota, USA.ORCID 0000-0002-9608-1444
University of Minnesota · US

Funding

TRD4 - Ultrahigh Field Engineering and SafetyP41EB027061 · NIBIB · UNIVERSITY OF MINNESOTA · PI Gregory John Metzger, KAMIL UGURBIL · 2019 to 2026
$11.7M
Integrated fMRI Methods to Study Neurophysiology and Circuit Dynamics at Laminar and Columnar LevelR01MH111413 · NIMH · UNIVERSITY OF MINNESOTA · PI CHEN, WEI · 2016 to 2020
$4.4M
Computer Aided Diagnostic System for Prostate Cancer Detection Using Quantitative Multiparametric MRIR01CA241159 · NCI · UNIVERSITY OF MINNESOTA · PI METZGER, GREGORY JOHN · 2021 to 2025
$3.0M
Establishing translational neuroimaging tools for quantitative assessment of energy metabolism and metabolic reprogramming in healthy and diseased human brain at 7TR01NS133006 · NINDS · UNIVERSITY OF MINNESOTA · PI Wei Chen, XIAO-HONG ZHU · 2023 to 2026
$2.5M
NCI NIH HHS R01 CA241159NIBIB NIH HHS P41 EB027061NIH HHS P41 EB027061NIH HHS R01 MH111413NIH HHS R01 NS133006NIMH NIH HHS R01 MH111413NINDS NIH HHS R01 NS133006
6 · The paper itself

Abstract

purposeThe heart is a highly aerobic organ consuming most of the oxygen the body in supporting heart function. Quantitative imaging of myocardial oxygen metabolism and perfusion is essential for studying cardiac physiopathology in vivo. Here, we report a new imaging method that can simultaneously assess myocardial oxygen metabolism and blood flow in the rat heart.

methodsThis novel method is based on the

resultsWe show that this

conclusionThe

Indexed as

OxygenWorkloadAnimalsCoronary CirculationHeartMyocardiumOxygen ConsumptionRatsOxygenhigh workloadin vivo oxygen-17 (17O) MRS imaging (MRSI)myocardial blood flowmyocardial energy metabolismmyocardial metabolic rate of oxygen consumptionoxygen extraction fraction

Identifiers

PMID38084378
PMCPMC11089813
OpenAlexW4389607506

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.