Evidence map›Paper›PMID 38923094›Full record

ArticleMagnetic resonance in medicine2024

Amide proton transfer MRI at 9.4 T for differentiating tissue acidosis in a rodent model of ischemic stroke.

Tao Jin, Jicheng Wang, Julius Chung, T Kevin Hitchens, Dandan Sun, Joseph Mettenburg, Ping Wang

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2024. 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. 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.

Tao JinDepartment of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID 0000-0003-2912-3517
Jicheng WangDepartment of Urology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Julius ChungDepartment of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.ORCID 0000-0002-1513-5181
T Kevin HitchensDepartment of Neurobiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Dandan SunDepartment of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Joseph MettenburgDepartment of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Ping WangDepartment of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.

Funding

Magnetic Resonance Imaging of Glucose Analogs in StrokeR01NS100703 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI JIN, TAO · 2018 to 2022
$1.6M
National Institutes of Health of USA R01NS100703NINDS NIH HHS R01 NS100703
6 · The paper itself

Abstract

purposeDifferentiating ischemic brain damage is critical for decision making in acute stroke treatment for better outcomes. We examined the sensitivity of amide proton transfer (APT) MRI, a pH-weighted imaging technique, to achieve this differentiation.

methodsIn a rat stroke model, the ischemic core, oligemia, and the infarct-growth region (IGR) were identified by tracking the progression of the lesions. APT MRI signals were measured alongside ADC, T

resultsThe APT signal in the IGR decreased by about 10% shortly after stroke onset, and further decreased to 35% at 5 h, indicating a progression from mild to severe acidosis as the lesion evolved into infarction. Although ADC, T

conclusionThe sensitivity of APT MRI is high in detecting severe acidosis of the ischemic core but is much lower in detecting mild acidosis, which may affect the accuracy of differentiation between the IGR and oligemia.

Indexed as

AcidosisDisease Models, AnimalIschemic StrokeMagnetic Resonance ImagingProtonsAmidesAnimalsBrainBrain IschemiaMaleRatsRats, Sprague-DawleySensitivity and SpecificityStrokeAmidesProtonsAPThyperglycemiainfarct growtholigemiapenumbrapHstroke

Identifiers

PMID38923094
PMCPMC11433955

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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.