Evidence map›Paper›PMID 35223925›Full record

ArticleFrontiers in medicine2022

Reduced Acquisition Time [

Artem Zatcepin, Steffanie Heindl, Ulrike Schillinger, Lena Kaiser, Simon Lindner, Peter Bartenstein, Anna Kopczak, Arthur Liesz, Matthias Brendel, Sibylle I Ziegler

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
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  3. [Biomolecules · 2023
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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

10 authors at 3 institutions in 1 country.

Artem ZatcepinDepartment of Nuclear Medicine, University Hospital of Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany.
Steffanie HeindlInstitute for Stroke and Dementia Research, University Hospital of Ludwig-Maximilians-Universität (LMU) Munich, Institute for Stroke and Dementia Research, Munich, Germany.
Ulrike SchillingerInstitute for Stroke and Dementia Research, University Hospital of Ludwig-Maximilians-Universität (LMU) Munich, Institute for Stroke and Dementia Research, Munich, Germany.
Lena KaiserDepartment of Nuclear Medicine, University Hospital of Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany.
Simon LindnerDepartment of Nuclear Medicine, University Hospital of Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany.
Peter BartensteinDepartment of Nuclear Medicine, University Hospital of Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany.
Anna KopczakInstitute for Stroke and Dementia Research, University Hospital of Ludwig-Maximilians-Universität (LMU) Munich, Institute for Stroke and Dementia Research, Munich, Germany.
Arthur LieszInstitute for Stroke and Dementia Research, University Hospital of Ludwig-Maximilians-Universität (LMU) Munich, Institute for Stroke and Dementia Research, Munich, Germany.
Matthias BrendelDepartment of Nuclear Medicine, University Hospital of Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany.
Sibylle I ZieglerDepartment of Nuclear Medicine, University Hospital of Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany.
Ludwig-Maximilians-Universität München · DEMunich Cluster for Systems Neurology · DEGerman Center for Neurodegenerative Diseases · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimUnderstanding neuroinflammation after acute ischemic stroke is a crucial step on the way to an individualized post-stroke treatment. Microglia activation, an essential part of neuroinflammation, can be assessed using [ MATERIALS AND

methodsSix mice after PT and six sham mice were included in the study. For a half of the mice, we acquired four serial 0-90 min scans per mouse (analysis cohort) and calculated standardized uptake value ratios (SUVRs; cerebellar reference) for the PT volume of interest (VOI) in five late 10 min time frames as well as distribution volume ratios (DVRs) for the same VOI. We compared late static 10 min SUVRs and the 60-90 min time frame of the analysis cohort to the corresponding DVRs by linear fitting. The other half of the animals received a static 60-90 min scan and was used as a validation cohort. We extrapolated DVRs by using the static 60-90 min p.i. time window, which were compared to the DVRs of the analysis cohort.

resultsWe found high linear correlations between SUVRs and DVRs in the analysis cohort for all studied 10 min time frames, while the fits of the 60-70, 70-80, and 80-90 min p.i. time frames were the ones closest to the line of identity. For the 60-90 min time window, we observed an excellent linear correlation between SUVR and DVR regardless of the phenotype (PT

conclusionSimplified quantification by a reference tissue ratio of the late 60-90 min p.i. [

Indexed as

GE-180 imagingimage-derived blood input function (IDIF)kinetic modelingmicroglianeuroinflammationpositron emission tomography (PET)stroketranslocator protein (TSPO) imaging

Identifiers

PMID35223925
PMCPMC8866959
OpenAlexW4211144874

What Socratic holds

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LicenceCC BY
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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 Socratic graph.