Evidence map›Paper›PMID 31132451›Full record

ArticleNeuroImage2019

TRActs constrained by UnderLying INfant anatomy (TRACULInA): An automated probabilistic tractography tool with anatomical priors for use in the newborn brain.

Lilla Zöllei, Camilo Jaimes, Elie Saliba, P Ellen Grant, Anastasia Yendiki

Open access · greenAbstract read
In one paragraph

Article in NeuroImage, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
3.8field-weighted citation impact, top 7% of its field
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

20 citing papers in PubMed, 33 citations in OpenAlex.

  1. Review
  2. Deep learning in fetal, infant, and toddler neuroimaging research.Developmental cognitive neuroscience · 2026
    Review
  3. Frontiers in behavioral neuroscience · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Diffusion MRI with Machine Learning.Imaging neuroscience (Cambridge, Mass.) · 2024
    Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Review
  14. Article
  15. Article
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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

5 authors at 3 institutions in 2 countries.

Lilla ZölleiMassachusetts General Hospital, Boston, United States. Electronic address: lzollei@nmr.mgh.harvard.edu.
Camilo JaimesBoston Children's Hospital, Boston, United States. Electronic address: camilo.jaimescobos@childrens.harvard.edu.
Elie SalibaUniversity of Tours, France. Electronic address: elie.saliba@univ-tours.fr.
P Ellen GrantBoston Children's Hospital, Boston, United States. Electronic address: ellen.grant@childrens.harvard.edu.
Anastasia YendikiMassachusetts General Hospital, Boston, United States. Electronic address: ayendiki@nmr.mgh.harvard.edu.
Boston Children's Museum · USMassachusetts General Hospital · USUniversité de Tours · FR

Funding

A Storage Area Network for Structural and Functional Image AnalysisS10RR023401 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 2009 to 2009
$2.0M
Multimodal mapping of the neurocircuitry of the human prefrontal cortexR01EB021265 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI YENDIKI, ANASTASIA · 2016 to 2019
$2.0M
SILICON GRAPHICS PRISM EXTREME 128P/1TBS10RR023043 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI SORENSEN, ALMA GREGORY · 2006 to 2006
$1.5M
Age-Dependent Analysis Techniques for Pediatric Structural and Diffusion MRI DataR00HD061485 · NICHD · MASSACHUSETTS GENERAL HOSPITAL · PI ZOLLEI, LILLA · 2012 to 2014
$706k
A 3.0 Tesla MRI System in a Neuroscience ICUS10RR019254 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI SORENSEN, ALMA GREGORY · 2004 to 2004
$500k
Computeserver Structural &Functional Image AnalysisS10RR019307 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 2004 to 2004
$496k
NCRR NIH HHS S10 RR019254NCRR NIH HHS S10 RR019307NCRR NIH HHS S10 RR023043NCRR NIH HHS S10 RR023401NIBIB NIH HHS R01 EB021265NICHD NIH HHS R00 HD061485
6 · The paper itself

Abstract

The ongoing myelination of white-matter fiber bundles plays a significant role in brain development. However, reliable and consistent identification of these bundles from infant brain MRIs is often challenging due to inherently low diffusion anisotropy, as well as motion and other artifacts. In this paper we introduce a new tool for automated probabilistic tractography specifically designed for newborn infants. Our tool incorporates prior information about the anatomical neighborhood of white-matter pathways from a training data set. In our experiments, we evaluate this tool on data from both full-term and prematurely born infants and demonstrate that it can reconstruct known white-matter tracts in both groups robustly, even in the presence of differences between the training set and study subjects. Additionally, we evaluate it on a publicly available large data set of healthy term infants (UNC Early Brain Development Program). This paves the way for performing a host of sophisticated analyses in newborns that we have previously implemented for the adult brain, such as pointwise analysis along tracts and longitudinal analysis, in both health and disease.

Indexed as

Diffusion Tensor ImagingFemaleHumansInfantInfant, NewbornInfant, PostmatureMaleNeural PathwaysNeuroimagingWhite MatterAnatomical priorInfant brain MRIPremature and full-term infantsPrior-guided annotationProbabilistic tractography

Identifiers

PMID31132451
PMCPMC6688923
OpenAlexW2945068253

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.