Evidence map›Paper›PMID 34969179›Full record

ArticleInternational journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience2022

Structural abnormalities in paediatric moyamoya disease revealed by clinical magnetic resonance imaging, regionally distributed relative signal intensities and volumes.

Prahar Ijner, Grace Tompkins, Tadashi Shiohama, Emi Takahashi, Jacob Levman

Open access · greenAbstract read
In one paragraph

Article in International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 72% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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 3 countries.

Prahar IjnerDepartment of Computer Science, St. Francis Xavier University, Antigonish, Nova Scotia, Canada.ORCID https://orcid.org/0000-0001-5447-9174
Grace TompkinsDepartment of Mathematics and Statistics, St. Francis Xavier University, Antigonish, Nova Scotia, Canada.ORCID https://orcid.org/0000-0003-4091-9970
Tadashi ShiohamaDepartment of Pediatrics, Graduate School of Medicine, Chiba University, Chiba, Japan.ORCID https://orcid.org/0000-0003-0076-5882
Emi TakahashiDivision of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts, USA.
Jacob LevmanDepartment of Computer Science, St. Francis Xavier University, Antigonish, Nova Scotia, Canada.ORCID https://orcid.org/0000-0002-9604-3157
St. Francis Xavier University · CABoston Children's Hospital · USChiba University · JP

Funding

Development of Brain Connectivity in Human Fetus, Newborn, and Toddler AgesR01HD078561 · NICHD · BOSTON CHILDREN'S HOSPITAL · PI TAKAHASHI (OKI), EMI · 2014 to 2018
$1.7M
MRI-based biomarkers for regional brain abnormalities in autism spectrum disorder: From newborns to young adultsR21MH118739 · NIMH · BOSTON CHILDREN'S HOSPITAL · PI TAKAHASHI (OKI), EMI · 2018 to 2019
$487k
Brain Development in Down Syndrome during Fetal, Newborn, and Infant StagesR21HD098606 · NICHD · MASSACHUSETTS GENERAL HOSPITAL · PI TAKAHASHI (OKI), EMI · 2019 to 2020
$484k
Aberrant Patterns of Human Brain Connectivity and Gyral StructuresR03NS091587 · NINDS · BOSTON CHILDREN'S HOSPITAL · PI TAKAHASHI (OKI), EMI · 2015 to 2016
$177k
Canada Foundation for Innovation and Nova Scotia Research and Innovation Trust Infrastructure Grant R0176004Canada Research Chair Grant 231266Natural Science and Engineering Research Council of Canada Discovery Grant R0192004NICHD NIH HHS R01 HD078561NICHD NIH HHS R21 HD098606NIH HHS HD098606NIH HHS R01HD078561NIH HHS R03NS091587NIH HHS R21MH118739NIMH NIH HHS R21 MH118739NINDS NIH HHS R03 NS091587St. Francis Xavier University Research Startup Grant R0168020
6 · The paper itself

Abstract

Moyamoya disease (MMD) is a rare, progressive cerebrovascular disorder, with an unknown aetiology and pathogenesis. It is characterized by steno-occlusive changes at the terminal portion of the internal carotid artery (ICA), which is accompanied by variable development of the basal collaterals called moyamoya vessels. In this study, we investigate the potential for structural T1 magnetic resonance imaging (MRI) to help characterize MMD clinically, with the help of regionally distributed relative signal intensities (RRSIs) and volumes (RRVs). These RRSIs and RRVs provide the ability to characterize aspects of regional brain development and represent an extension to existing automated biomarker extraction technologies. This study included 269 MRI examinations from MMD patients and 993 MRI examinations from neurotypical controls, with regional biomarkers compared between groups with the area under the receiver operating characteristic curve (AUC). Results demonstrate abnormal presentation of RRSIs and RRVs in the insula (15- to 20-year old cohort, left AUC: 0.74, right AUC: 0.71) and the lateral orbitofrontal region (5- to 10-year old cohort, left AUC: 0.67; 15-20 year cohort, left AUC: 0.62, right AUC: 0.65). Results indicate that RRSIs and RRVs may help in characterizing brain development, assist in the assessment of the presentation of the brains of children with MMD and help overcome standardization challenges in multiprotocol clinical MRI. Further investigation of the potential for RRSIs and RRVs in clinical imaging is warranted and supported through the release of open-source software.

Indexed as

Moyamoya DiseaseAdolescentAdultBrainCerebral CortexChildChild, PreschoolHumansMagnetic Resonance ImagingROC CurveYoung Adultbiomarker extractionmagnetic resonance imagingmoyamoya

Identifiers

PMID34969179
PMCPMC8983520
OpenAlexW4205471534

What OpenQuestion holds

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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.