Evidence map›Paper›PMID 33633162›Full record

ArticleScientific reports2021

Flow velocity quantification by exploiting the principles of the Doppler effect and magnetic particle imaging.

Dennis Pantke, Florian Mueller, Sebastian Reinartz, Fabian Kiessling, Volkmar Schulz

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Dennis PantkeDepartment of Physics of Molecular Imaging, Institute for Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany. dennis.pantke@pmi.rwth-aachen.de.
Florian MuellerDepartment of Physics of Molecular Imaging, Institute for Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany.
Sebastian ReinartzDepartment of Diagnostic and Interventional Radiology, Uniklinik RWTH Aachen, Aachen, Germany.
Fabian KiesslingInstitute for Experimental Molecular Imaging, Medical Faculty, RWTH Aachen University, Aachen, Germany.
Volkmar SchulzDepartment of Physics of Molecular Imaging, Institute for Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany. volkmar.schulz@pmi.rwth-aachen.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Changes in blood flow velocity play a crucial role during pathogenesis and progression of cardiovascular diseases. Imaging techniques capable of assessing flow velocities are clinically applied but are often not accurate, quantitative, and reliable enough to assess fine changes indicating the early onset of diseases and their conversion into a symptomatic stage. Magnetic particle imaging (MPI) promises to overcome these limitations. Existing MPI-based techniques perform velocity estimation on the reconstructed images, which restricts the measurable velocity range. Therefore, we developed a novel velocity quantification method by adapting the Doppler principle to MPI. Our method exploits the velocity-dependent frequency shift caused by a tracer motion-induced modulation of the emitted signal. The fundamental theory of our method is deduced and validated by simulations and measurements of moving phantoms. Overall, our method enables robust velocity quantification within milliseconds, with high accuracy, no radiation risk, no depth-dependency, and extended range compared to existing MPI-based velocity quantification techniques, highlighting the potential of our method as future medical application.

Identifiers

PMID33633162
PMCPMC7907137

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.