Evidence map›Paper›PMID 23008121›Full record

ArticleMagnetic resonance in medicine2013

Quantitative Bayesian model-based analysis of amide proton transfer MRI.

Michael A Chappell, Manus J Donahue, Yee Kai Tee, Alexandre A Khrapitchev, Nicola R Sibson, Peter Jezzard, Stephen J Payne

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

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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

7 authors.

Michael A ChappellInstitute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK. michael.chappell@eng.ox.ac.uk
Manus J Donahue
Yee Kai Tee
Alexandre A Khrapitchev
Nicola R Sibson
Peter Jezzard
Stephen J Payne

Funding

Cancer Research UK 16466Cancer Research UK 16945Cancer Research UK A12678Cancer Research UK C5255/A12678Wellcome Trust 088877Wellcome Trust WT088877/Z/09/Z
6 · The paper itself

Abstract

Amide Proton Transfer (APT) reports on contrast derived from the exchange of protons between amide groups and water. Commonly, APT contrast is quantified by asymmetry analysis, providing an ensemble contrast of both amide proton concentration and exchange rate. An alternative is to sample the off-resonant spectrum and fit an exchange model, permitting the APT effect to be quantified, correcting automatically for confounding effects of spillover, field inhomogeneity, and magnetization transfer. Additionally, it should permit amide concentration and exchange rate to be independently quantified. Here, a Bayesian method is applied to this problem allowing pertinent prior information to be specified. A three-pool model was used incorporating water protons, amide protons, and magnetization transfer effect. The method is demonstrated in simulations, creatine phantoms with varying pH and in vivo (n = 7). The Bayesian model-based approach was able to quantify the APT effect accurately (root-mean-square error < 2%) even when subject to confounding field variation and magnetization transfer effect, unlike traditional asymmetry analysis. The in vivo results gave approximate APT concentration (relative to water) and exchange rate values of 3 × 10(-3) and 15 s(-1) . A degree of correlation was observed between these parameter making the latter difficult to quantify with absolute accuracy, suggesting that more optimal sampling strategies might be required.

Indexed as

Models, NeurologicalAdultAmidesBayes TheoremBody WaterBrainComputer SimulationHumansImage EnhancementImage Interpretation, Computer-AssistedMagnetic Resonance ImagingMalePattern Recognition, AutomatedProtonsReproducibility of ResultsSensitivity and SpecificityAmidesProtonsamide proton transferchemical exchange saturation transfermagnetization transfer

Identifiers

PMID23008121
PMCPMC7334045

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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 OpenQuestion graph.