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Assessment of MRI parameters for studying brain development in newborns with congenital heart disease

2015· article· en· W95911159 on OpenAlexaff
Brahmdeep S. Saini, Prakash Muthusami, Sujana Madathil, Jessie Mei Lim, Christopher K. Macgowan, Steven P. Miller, Mike Seed

Bibliographic record

VenueJournal of Cardiovascular Magnetic Resonance · 2015
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineAngiologyCohortHeart diseaseWhite matterBrain developmentIncidence (geometry)CardiologyDiseasePediatricsMagnetic resonance imagingInternal medicineRadiologyNeurosciencePsychology

Abstract

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Microstructural evidence of white matter (WM) dysmaturation in the brains of newborns with congenital heart disease (CHD) using MRI has been previously shown [ 1 ]. Further, delayed WM development confers an increased risk of WM injury before and after neonatal cardiac surgery [ 2 ]. WM injury is associated with a high incidence of subsequent neurodevelopmental deficits and fetal interventions to improve brain development in the setting of CHD are currently being investigated. We wished to compare the utility of our previously described parameters in another cohort of CHD newborns, and assess the performance of a new parameter (WM T2 relaxation) for discerning differences in WM maturation. We studied the newborn brains of 30 normal and 21 CHD subjects between June 2013 and September 2014 as part of a hospital IRB approved study. MRI was performed without sedation at a mean age of 7 days (range 0-42 days) on a Siemens Avanto 1.5T system (Erlangen) with the following sequences: high resolution 3D T2W FSE, multivoxel proton magnetic resonance spectroscopy and diffusion tensor imaging. T2 mapping was performed in 6 normal and 6 CHD newborns. We calculated brain volume by segmenting the 3D T2W images using Mimics (Materialise, Leuven). The N-acetyl acetate to choline (NAA/Chol) ratio was calculated from the MRS of the centrum semiovale. Regions of interest for analysis of T2, fractional anisotropy (FA) and apparent diffusion coefficient (ADC) included inferior frontal, superior frontal and parietal WM. An unpaired t-test was used to determine the statistical significance of differences between the two groups. There was no significant difference between the corrected gestational ages of the two groups (p=0.88). Brain volume increased with age but was lower in CHD newborns than controls (Fig. 1A ). The ADC values decreased with age but were higher in CHD newborns than in controls (Fig. 1B ). FA and NAA/Chol ratios both increased with age but were not significantly different between the two groups. T2s decreased with age and the average WM T2s of CHD newborns were higher than controls. The T2 brain maps of CHD newborns showed visual differences in comparison to controls of similar age (Fig. 1C-D ). Table 1 summarizes all the results. Comparison of brain volumes (A.) and inferior frontal WM ADC (B.) versus corrected gestational age (GA) between CHD newborns and controls. Visual comparison of brain T2 maps at the same window level of inferior frontal WM in a control (C.) to a CHD newborn (D.). Both the normal and CHD newborn were of the same age, 39 weeks corrected GA. As expected, WM ADC values in CHD newborns were significantly higher than controls. We also found a reduction in brain volume in newborns with CHD, similar to the results of other groups [ 3 ]. In unmyelinated WM regions, FA and NAA/Chol ratios were not significantly different. Whereas, WM T2 was significantly higher in CHD newborns, despite the smaller number of studies that incorporated T2 mapping. WM T2 may be a sensitive marker of WM dysmaturation in the setting of CHD and a useful adjunct to more established parameters in the assessment of the impact of fetal interventions on brain development.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.290
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2015
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