Evidence map›Paper›PMID 30393888›Full record

ArticleMagnetic resonance in medicine2019

Optimization of phase-contrast MRI for the estimation of global cerebral blood flow of mice at 11.7T.

Zhiliang Wei, Lin Chen, Zixuan Lin, Dengrong Jiang, Jiadi Xu, Peiying Liu, Peter C M van Zijl, Hanzhang Lu

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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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

8 authors.

Zhiliang WeiRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Lin ChenRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Zixuan LinDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Dengrong JiangDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Jiadi XuRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Peiying LiuRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Peter C M van ZijlRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Hanzhang LuRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.

Funding

TR&D 4: Algorithms for functional and anatomical brain analysisP41EB015909 · NIBIB · HUGO W. MOSER RES INST KENNEDY KRIEGER · PI VAN ZIJL, PETER CM · 2012 to 2020
$13.1M
Normalized functional MRI in human brain disordersR01MH084021 · NIMH · UT SOUTHWESTERN MEDICAL CENTER · PI LU, HANZHANG · 2008 to 2017
$3.6M
An integrated vascular MR imaging suite in brain diseasesR01NS106702 · NINDS · JOHNS HOPKINS UNIVERSITY · PI LU, HANZHANG · 2018 to 2022
$2.7M
MR fingerprinting (MRF) perfusion imaging in cerebral vascular diseaseR01NS106711 · NINDS · JOHNS HOPKINS UNIVERSITY · PI LU, HANZHANG · 2018 to 2022
$2.2M
BOLD and its discontents: age-differences in the neurophysiology of fMRI signalR01AG047972 · NIA · UT SOUTHWESTERN MEDICAL CENTER · PI LU, HANZHANG, RYPMA, BART · 2015 to 2019
$1.7M
Advanced MRI methods to image vascular physiology with respiratory manipulationsR21NS095342 · NINDS · JOHNS HOPKINS UNIVERSITY · PI LU, HANZHANG · 2016 to 2017
$476k
Brain oxygen consumption as an MRI biomarker of neurodegeneration in a model of Alzheimer?s diseaseR21AG058413 · NIA · JOHNS HOPKINS UNIVERSITY · PI LU, HANZHANG · 2018 to 2019
$465k
Quantification of brain metabolic rate in neonates using MRIR21NS085634 · NINDS · UT SOUTHWESTERN MEDICAL CENTER · PI LIU, PEIYING · 2014 to 2015
$441k
NIA NIH HHS R01 AG047972NIA NIH HHS R21 AG058413NIBIB NIH HHS P41 EB015909NIH HHS P41 EB015909NIH HHS R01 AG047972NIH HHS R01 MH084021NIH HHS R01 NS106702NIH HHS R01 NS106711NIH HHS R21 AG058413NIH HHS R21 NS085634NIH HHS R21 NS095342NIMH NIH HHS R01 MH084021NINDS NIH HHS R01 NS106702NINDS NIH HHS R01 NS106711NINDS NIH HHS R21 NS085634NINDS NIH HHS R21 NS095342
6 · The paper itself

Abstract

purposeTo optimize phase-contrast (PC) MRI for the measurement of global cerebral blood flow (CBF) in the mouse at 11.7T.

methodsWe determined proper velocity encoding (VENC) for internal carotid arteries (ICAs) and vertebral arteries (VAs). Next, we optimized spatial resolution of the sequence. To shorten scan time without compromising data quality, we further optimized repetition time and developed a reduced field-of-view (FOV) scheme for ICA and VA PC MRI. Whole-brain volume was determined with T

resultsPeak flow velocities were 13.8 ± 1.7, 14.4 ± 0.6, 6.5 ± 1.7, and 6.7 ± 1.3 cm/s for left ICA, right ICA, left VA, and right VA, respectively. Thus, VENC values of 20 and 10 cm/s were chosen for ICA and VA PC MRI, respectively. An in-plane spatial resolution of 50 × 50 μm

conclusionWe have optimized PC MRI for noninvasive quantification of blood flow in mice at 11.7T.

Indexed as

Cerebrovascular CirculationAnimalsBlood Flow VelocityBrainCarotid Artery, InternalContrast MediaHemodynamicsImaging, Three-DimensionalMagnetic Resonance ImagingMiceMice, Inbred BALB CMice, Inbred C57BLReproducibility of ResultsSignal-To-Noise RatioVertebral ArteryContrast Mediacerebral blood flowinternal carotid arterymaximum blood velocitypartial volume effectspatial foldingspatial resolutionvertebral artery

Identifiers

PMID30393888
PMCPMC6372341

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Registered trials

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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.