Evidence map›Paper›PMID 40800391›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2024

Internally consistent and fully unbiased multimodal MRI brain template construction from UK Biobank: Oxford-MM.

Christoph Arthofer, Stephen M Smith, Gwenaëlle Douaud, Andreas Bartsch, Fidel Alfaro-Almagro, Jesper Andersson, Frederik J Lange

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.), 2024. 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. Article
  2. Article
  3. Article
  4. Article
  5. MMORF-FSL's MultiMOdal Registration Framework.Imaging neuroscience (Cambridge, Mass.) · 2024
    Article
  6. 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

7 authors.

Christoph ArthoferWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Stephen M SmithWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Gwenaëlle DouaudWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Andreas BartschDepartment of Neuroradiology, University of Heidelberg, Heidelberg, Germany.
Fidel Alfaro-AlmagroWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Jesper AnderssonWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Frederik J LangeWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.

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 MH091657Wellcome Trust
6 · The paper itself

Abstract

Anatomical magnetic resonance imaging (MRI) templates of the brain are essentialto group-level analyses and image processing pipelines, as they provide areference space for spatial normalisation. While it has become common forstudies to acquire multimodal MRI data, many templates are still limited to onetype of modality, usually either scalar or tensor based. Aligning each modalityin isolation does not take full advantage of the available complementaryinformation, such as strong contrast between tissue types in structural images,or axonal organisation in the white matter in diffusion tensor images. Mostexisting strategies for multimodal template construction either do not use allmodalities of interest to inform the template construction process, or do notuse them in a unified framework. Here, we present multimodal, cross-sectionaltemplates constructed from UK Biobank data: the Oxford-MultiModal-1 (OMM-1)template and age-dependent templates for each year of life between 45 and 81years. All templates are fully unbiased to represent the average shape of thepopulations they were constructed from, and internally consistent throughjointly informing the template construction process with T1-weighted (T1),T2-weighted fluid-attenuated inversion recovery (T2-FLAIR), and diffusion tensorimaging (DTI) data. The OMM-1 template was constructed with a multiresolution,iterative approach using 240 individuals in the 50-55-year age range. Theage-dependent templates were estimated using a Gaussian process, which describesthe change in average brain shape with age in 37,330 individuals. All templatesshow excellent contrast and alignment within and between modalities. The globalbrain shape and size are not preconditioned on existing templates, althoughmaximal possible compatibility with MNI-152 space was maintained through rigidalignment. We showed benefits in registration accuracy across two datasets (UKBiobank and HCP), when using the OMM-1 as the template compared withFSL's MNI-152 template, and found that the use of age-dependent templatesfurther improved accuracy to a small but detectable extent. All templates arepublicly available and can be used as a new reference space for uni- ormultimodal spatial alignment.

Indexed as

age-dependentmultimodalregistrationtemplateUK Biobank

Identifiers

PMID40800391
PMCPMC12315729

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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.