Evidence map›Paper›PMID 29934611›Full record

ArticleScientific reports2018

Temporal window for detection of inflammatory disease using dynamic cell tracking with time-lapse MRI.

Max Masthoff, Sandra Gran, Xueli Zhang, Lydia Wachsmuth, Michael Bietenbeck, Anne Helfen, Walter Heindel, Lydia Sorokin, Johannes Roth, Michel Eisenblätter and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

9 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. ISMRM Clinical Focus Meeting 2023: "Imaging the Fire in the Brain".Journal of magnetic resonance imaging : JMRI · 2025
    Article
  3. Review
  4. Embracing complexity in sepsis.Critical care (London, England) · 2023
    Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. 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

12 authors at 4 institutions in 2 countries.

Max MasthoffTranslational Research Imaging Center, Department of Clinical Radiology, University Hospital Muenster, Albert-Schweitzer-Campus 1, 48149, Muenster, Germany.
Sandra GranInstitute for Immunology, University of Muenster, Roentgenstraße 21, 48149, Muenster, Germany.
Xueli ZhangInstitute for Physiological Chemistry and Pathobiochemistry, University of Muenster, Waldeyerstraße 15, 48149, Muenster, Germany.
Lydia WachsmuthTranslational Research Imaging Center, Department of Clinical Radiology, University Hospital Muenster, Albert-Schweitzer-Campus 1, 48149, Muenster, Germany.
Michael BietenbeckTranslational Research Imaging Center, Department of Clinical Radiology, University Hospital Muenster, Albert-Schweitzer-Campus 1, 48149, Muenster, Germany.
Anne HelfenTranslational Research Imaging Center, Department of Clinical Radiology, University Hospital Muenster, Albert-Schweitzer-Campus 1, 48149, Muenster, Germany.
Walter HeindelTranslational Research Imaging Center, Department of Clinical Radiology, University Hospital Muenster, Albert-Schweitzer-Campus 1, 48149, Muenster, Germany.
Lydia SorokinInstitute for Physiological Chemistry and Pathobiochemistry, University of Muenster, Waldeyerstraße 15, 48149, Muenster, Germany.
Johannes RothInstitute for Immunology, University of Muenster, Roentgenstraße 21, 48149, Muenster, Germany.
Michel EisenblätterTranslational Research Imaging Center, Department of Clinical Radiology, University Hospital Muenster, Albert-Schweitzer-Campus 1, 48149, Muenster, Germany.
Moritz WildgruberTranslational Research Imaging Center, Department of Clinical Radiology, University Hospital Muenster, Albert-Schweitzer-Campus 1, 48149, Muenster, Germany.
Cornelius FaberTranslational Research Imaging Center, Department of Clinical Radiology, University Hospital Muenster, Albert-Schweitzer-Campus 1, 48149, Muenster, Germany. faberc@uni-muenster.de.ORCID 0000-0001-7683-7710
University Hospital Münster · DEUniversity of Münster · DEAugenstern · DEKing's College London · GB

Funding

Deutsche Forschungsgemeinschaft (German Research Foundation) EXC1003Deutsche Forschungsgemeinschaft (German Research Foundation) SFB1009 B09Deutsche Forschungsgemeinschaft (German Research Foundation) SFB1009 rotational positionDeutsche Forschungsgemeinschaft (German Research Foundation) SFB1009 Z02
6 · The paper itself

Abstract

Time-lapse MRI was implemented for dynamic non-invasive cell tracking of individual slowly moving intravascular immune cells. Repetitive MRI acquisition enabled dynamic observation of iron oxide nanoparticle (ION) labelled cells. Simulations of MRI contrast indicated that only cells moving slower than 1 µm/s were detectable. Time-lapse MRI of the brain was performed after either IONs or ION-labelled monocytes were injected intravenously into naïve and experimental autoimmune encephalomyelitis (EAE) bearing mice at a presymptomatic or symptomatic stage. EAE mice showed a reduced number of slow moving, i.e. patrolling cells before and after onset of symptoms as compared to naïve controls. This observation is consistent with the notion of altered cell dynamics, i.e. higher velocities of immune cells rolling along the endothelium in the inflamed condition. Thus, time-lapse MRI enables for assessing immune cell dynamics non-invasively in deep tissue and may serve as a tool for detection or monitoring of an inflammatory response.

Indexed as

Cell TrackingMagnetic Resonance ImagingAnimalsAsymptomatic DiseasesEncephalomyelitis, Autoimmune, ExperimentalFemaleMiceMice, Inbred C57BLMonocytesTime Factors

Identifiers

PMID29934611
PMCPMC6015069
OpenAlexW2809174329

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.