Evidence map›Paper›PMID 26714794›Full record

ArticleMagnetic resonance in medicine2016

Diffusion in realistic biophysical systems can lead to aliasing effects in diffusion spectrum imaging.

Luis M Lacerda, Jonathan I Sperl, Marion I Menzel, Tim Sprenger, Gareth J Barker, Flavio Dell'Acqua

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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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Comparison of q-Space Reconstruction Methods for Undersampled Diffusion Spectrum Imaging Data.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2020
    Article
  4. Review
  5. Article
  6. Article
4 · The record

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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

6 authors.

Luis M LacerdaNATBRAINLAB, Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom.
Jonathan I SperlGE Global Research, Munich, BY, Germany.
Marion I MenzelGE Global Research, Munich, BY, Germany.
Tim SprengerGE Global Research, Munich, BY, Germany.
Gareth J BarkerDepartment of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom.
Flavio Dell'AcquaNATBRAINLAB, Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom.

Funding

Wellcome Trust
6 · The paper itself

Abstract

purposeDiffusion spectrum imaging (DSI) is an imaging technique that has been successfully applied to resolve white matter crossings in the human brain. However, its accuracy in complex microstructure environments has not been well characterized. THEORY AND

methodsHere we have simulated different tissue configurations, sampling schemes, and processing steps to evaluate DSI performances' under realistic biophysical conditions. A novel approach to compute the orientation distribution function (ODF) has also been developed to include biophysical constraints, namely integration ranges compatible with axial fiber diffusivities.

resultsPerformed simulations identified several DSI configurations that consistently show aliasing artifacts caused by fast diffusion components for both isotropic diffusion and fiber configurations. The proposed method for ODF computation showed some improvement in reducing such artifacts and improving the ability to resolve crossings, while keeping the quantitative nature of the ODF.

conclusionIn this study, we identified an important limitation of current DSI implementations, specifically the presence of aliasing due to fast diffusion components like those from pathological tissues, which are not well characterized, and can lead to artifactual fiber reconstructions. To minimize this issue, a new way of computing the ODF was introduced, which removes most of these artifacts and offers improved angular resolution. Magn Reson Med 76:1837-1847, 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

AlgorithmsArtifactsBrainDiffusionDiffusion Tensor ImagingHumansImage EnhancementImage Interpretation, Computer-AssistedReproducibility of ResultsSensitivity and SpecificityWhite MatteraliasingdiffusionDSIODFpropagatorresolution

Identifiers

PMID26714794
PMCPMC5111756

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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.