Evidence map›Paper›PMID 26507239›Full record

ArticleMagnetic resonance in medicine2016

Investigating lung responses with functional hyperpolarized xenon-129 MRI in an ex vivo rat model of asthma.

David M L Lilburn, Amanda L Tatler, Joseph S Six, Clémentine Lesbats, Anthony Habgood, Joanne Porte, Theodore Hughes-Riley, Dominick E Shaw, Gisli Jenkins, Thomas Meersmann

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Differential remodeling in small and large murine airways revealed by novel whole lung airway analysis.American journal of physiology. Lung cellular and molecular physiology · 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.

David M L LilburnSir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom.
Amanda L TatlerDivision of Respiratory Medicine, Nottingham University Hospitals, City Campus, University of Nottingham, Nottingham, United Kingdom.
Joseph S SixSir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom.
Clémentine LesbatsSir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom.
Anthony HabgoodDivision of Respiratory Medicine, Nottingham University Hospitals, City Campus, University of Nottingham, Nottingham, United Kingdom.
Joanne PorteDivision of Respiratory Medicine, Nottingham University Hospitals, City Campus, University of Nottingham, Nottingham, United Kingdom.
Theodore Hughes-RileySir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom.
Dominick E ShawDivision of Respiratory Medicine, Nottingham University Hospitals, City Campus, University of Nottingham, Nottingham, United Kingdom.
Gisli JenkinsDivision of Respiratory Medicine, Nottingham University Hospitals, City Campus, University of Nottingham, Nottingham, United Kingdom.
Thomas MeersmannSir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom. thomas.meersmann@Nottingham.ac.uk.

Funding

Medical Research Council G0900785National Centre for the Replacement, Refinement and Reduction of Animals in Research G1100564/1National Centre for the Replacement, Refinement and Reduction of Animals in Research NC/K500501/1
6 · The paper itself

Abstract

purposeAsthma is a disease of increasing worldwide importance that calls for new investigative methods. Ex vivo lung tissue is being increasingly used to study functional respiratory parameters independent of confounding systemic considerations but also to reduce animal numbers and associated research costs. In this work, a straightforward laboratory method is advanced to probe dynamic changes in gas inhalation patterns by using an ex vivo small animal ovalbumin (OVA) model of human asthma.

methodsHyperpolarized (hp) (129) Xe was actively inhaled by the excised lungs exposed to a constant pressure differential that mimicked negative pleural cavity pressure. The method enabled hp (129) Xe MRI of airway responsiveness to intravenous methacholine (MCh) and airway challenge reversal through salbutamol.

resultsSignificant differences were demonstrated between control and OVA challenged animals on global lung hp (129) Xe gas inhalation with P < 0.05 at MCh dosages above 460 μg. Spatial mapping of the regional hp gas distribution revealed an approximately three-fold increase in heterogeneity for the asthma model organs.

conclusionThe experimental results from this proof of concept work suggest that the ex vivo hp noble gas imaging arrangement and the applied image analysis methodology may be useful as an adjunct to current diagnostic techniques. Magn Reson Med 76:1224-1235, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Indexed as

Pulmonary Gas ExchangeAdministration, InhalationAnimalsAsthmaComputer SimulationImage EnhancementImage Interpretation, Computer-AssistedLungMagnetic Resonance ImagingMaleModels, BiologicalMolecular ImagingRadiopharmaceuticalsRatsReproducibility of ResultsSensitivity and SpecificityRadiopharmaceuticalsXenon Isotopesairway hyper-responsivenesshp 129Xehyperpolarized noble gas MRImethacholine challengesovalbumin (OVA) rat model of asthmapulmonary imaging

Identifiers

PMID26507239
PMCPMC5026173

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Registered trials

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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.