Evidence map›Paper›PMID 35180211›Full record

ArticlePloS one2022

Avoiding data loss: Synthetic MRIs generated from diffusion imaging can replace corrupted structural acquisitions for freesurfer-seeded tractography.

Jeremy Beaumont, Giulio Gambarota, Marita Prior, Jurgen Fripp, Lee B Reid

Abstract read
In one paragraph

Article in PloS one, 2022. 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. Article
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

5 authors.

Jeremy BeaumontThe Australian e-Health Research Centre, CSIRO, Queensland, Australia.ORCID 0000-0003-1198-2217
Giulio GambarotaUniv Rennes, INSERM, LTSI-UMR1099, Rennes, France.
Marita PriorDepartment of Medical Imaging, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.
Jurgen FrippThe Australian e-Health Research Centre, CSIRO, Queensland, Australia.
Lee B ReidThe Australian e-Health Research Centre, CSIRO, Queensland, Australia.ORCID 0000-0002-3585-8141

Funding

Mapping the Human Connectome: Structure, Function, and HeritabilityU54MH091657 · NIMH · WASHINGTON UNIVERSITY · PI UGURBIL, KAMIL, VAN ESSEN, DAVID C · 2010 to 2014
$34.7M
NIMH NIH HHS U54 MH091657
6 · The paper itself

Abstract

Magnetic Resonance Imaging (MRI) motion artefacts frequently complicate structural and diffusion MRI analyses. While diffusion imaging is easily 'scrubbed' of motion affected volumes, the same is not true for T1w or T2w 'structural' images. Structural images are critical to most diffusion-imaging pipelines thus their corruption can lead to disproportionate data loss. To enable diffusion-image processing when structural images are missing or have been corrupted, we propose a means by which synthetic structural images can be generated from diffusion MRI. This technique combines multi-tissue constrained spherical deconvolution, which is central to many existing diffusion analyses, with the Bloch equations that allow simulation of MRI intensities for given scanner parameters and magnetic resonance (MR) tissue properties. We applied this technique to 32 scans, including those acquired on different scanners, with different protocols and with pathology present. The resulting synthetic T1w and T2w images were visually convincing and exhibited similar tissue contrast to acquired structural images. These were also of sufficient quality to drive a Freesurfer-based tractographic analysis. In this analysis, probabilistic tractography connecting the thalamus to the primary sensorimotor cortex was delineated with Freesurfer, using either real or synthetic structural images. Tractography for real and synthetic conditions was largely identical in terms of both voxels encountered (Dice 0.88-0.95) and mean fractional anisotropy (intrasubject absolute difference 0.00-0.02). We provide executables for the proposed technique in the hope that these may aid the community in analysing datasets where structural image corruption is common, such as studies of children or cognitively impaired persons.

Indexed as

AnisotropyArtifactsBrain NeoplasmsCase-Control StudiesCerebrospinal FluidComputer SimulationConnectomeDiffusion Tensor ImagingEpilepsyGliomaGray MatterHealthy VolunteersHumansImage Processing, Computer-AssistedWhite Matter

Identifiers

PMID35180211
PMCPMC8856573

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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.