Evidence map›Paper›PMID 31395540›Full record

ArticleIEEE transactions on medical imaging2020

Automatic, Age Consistent Reconstruction of the Corpus Callosum Guided by Coherency From In Utero Diffusion-Weighted MRI.

David Hunt, Manjiri Dighe, Christopher Gatenby, Colin Studholme

Abstract read
In one paragraph

Article in IEEE transactions on medical imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

4 authors.

David Hunt
Manjiri Dighe
Christopher Gatenby
Colin Studholme

Funding

Mechanisms of Brain Dysmorphology in MN1 C-Terminal Truncation Syndrome, a Novel Intellectual Developmental Disability Disorder P50HD103524 · NICHD · UNIVERSITY OF WASHINGTON · PI Sandra E Juul · 2020 to 2026
$9.9M
Intellectual and Developmental Disabilities Research CenterU54HD083091 · NICHD · UNIVERSITY OF WASHINGTON · PI GURALNICK, MICHAEL J · 2014 to 2019
$7.9M
Motion Robust Mapping of Human Brain Microstructure and Macrostructure In-UteroR01NS055064 · NINDS · UNIVERSITY OF WASHINGTON · PI STUDHOLME, COLIN · 2006 to 2017
$4.1M
Motion Robust Mapping of Human Brain Functional Connectivity Changes in UteroR01EB017133 · NIBIB · UNIVERSITY OF WASHINGTON · PI STUDHOLME, COLIN · 2013 to 2016
$2.5M
NIBIB NIH HHS R01 EB017133NICHD NIH HHS P50 HD103524NICHD NIH HHS U54 HD083091NINDS NIH HHS R01 NS055064
6 · The paper itself

Abstract

Reconstruction of white matter connectivity in the fetal brain from in utero diffusion-weighted magnetic resonance imaging (MRI) faces many challenges, including subject motion, small anatomical scale, and limited image resolution and signal. These issues are compounded by the need to track significant changes in structural connectivity throughout development. We present an automated method for improved reliability and completeness of tract extraction across a wide range of gestational ages, based on the geometry of coherent patterns in streamline tractography, and apply it to the reconstruction of the corpus callosum. This method, focused specifically at addressing the challenges of fetal brain imaging, avoids depending on a tractography atlas, and handles variations in size, shape, and tissue properties of developing brains, both between subjects and across ages. Although tractography from in utero MRI generally suffers from a significant number of misleading and missing pathways, we demonstrate the feasibility of extracting the coherent bundle of the corpus callosum while avoiding inappropriate diversions into other tracts.

Indexed as

Corpus CallosumDatabases, FactualDiffusion Magnetic Resonance ImagingDiffusion Tensor ImagingFetusGestational AgeHumansWashington

Identifiers

PMID31395540
PMCPMC7189742

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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.