Evidence map›Paper›PMID 30847971›Full record

ArticleMagnetic resonance in medicine2019

Quantification of intracranial arterial blood flow using noncontrast enhanced 4D dynamic MR angiography.

Xingfeng Shao, Ziwei Zhao, Jonathan Russin, Arun Amar, Nerses Sanossian, Danny Jj Wang, Lirong Yan

Open access · greenAbstract 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 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

10 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Simultaneous perfusion, diffusion, TMagnetic resonance in medicine · 2024
    Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Intracranial 3D and 4D MR Angiography Using Arterial Spin Labeling: Technical Considerations.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2020
    Review
  10. Review
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 1 country.

Xingfeng ShaoLaboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California.
Ziwei ZhaoLaboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California.
Jonathan RussinCenter for Neurorestoration, Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, California.
Arun AmarCenter for Neurorestoration, Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, California.
Nerses SanossianDepartment of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, California.
Danny Jj WangLaboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California.
Lirong YanLaboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California.
University of Southern California · US

Funding

Non-contrast 4-D Dynamic MRA in Arteriovenous Malformation (AVM)R01EB014922 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI WANG, DANNY JJ · 2013 to 2016
$1.8M
Intracranial Vascular Compliance as an Early Imaging Marker of Alzheimer's DiseaseK25AG056594 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI YAN, LIRONG · 2017 to 2021
$753k
NIA NIH HHS K25 AG056594NIBIB NIH HHS R01 EB014922
6 · The paper itself

Abstract

purposeNoncontrast enhanced dynamic magnetic resonance angiography delineates the pattern of dynamic blood flow of the cerebral vasculature. A model-free solution was proposed to quantify arterial blood flow (aBF) by using the monotonic property of the residual function. THEORY AND

methodsAnalytical simulations and in-vivo studies were performed to evaluate the performance of the proposed method by comparing the aBF values generated from the proposed and conventional singular value decomposition methods. The aBF values were compared with blood flow velocity measured by 2D phase contrast MRI, and compared between balanced steady-state free precession-based radial and spoiled GRE-based Cartesian acquisitions. Hemodynamic parametric maps were generated in 1 patient with arteriovenous malformation.

resultsThe proposed method generates reliable aBF measurement at different signal-to-noise ratio levels, whereas overestimation/underestimation of aBF was observed when a high/low threshold was applied in the singular value decomposition method. Average aBF in large vascular branches was 214.4 and 214.5 mL/mL/min with radial and Cartesian acquisitions, respectively. Significant correlations were found between aBF and blood flow velocity measured by phase contrast MRI (P = 0.0008), and between Cartesian and radial acquisitions (P < 0.0001). Altered hemodynamics were observed at the lesion site of the arteriovenous malformation patient.

conclusionA robust analytical solution was proposed for quantifying aBF. This model-free method is robust to noise, and its clinical value in the diagnosis of cerebrovascular disorders awaits further evaluation.

Indexed as

AdultAlgorithmsBlood Flow VelocityBrainCerebrovascular CirculationFemaleHumansImaging, Three-DimensionalMagnetic Resonance AngiographyMaleSignal-To-Noise RatioSpin LabelsYoung AdultSpin Labelsarterial blood flow (aBF)arterial spin labeling (ASL)cerebrovascular hemodynamicsdynamic magnetic resonance angiography (dMRA)

Identifiers

PMID30847971
PMCPMC6491251
OpenAlexW2921353923

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.