Correlation Between Fractional Anisotropy and Motor Outcomes in One-Year-Old Infants With Periventricular Brain Injury
Bibliographic record
Abstract
Purpose To determine whether motor outcomes of an exercise intervention beginning at 2 months corrected age (CA) in children with periventricular brain injury (PBI) are correlated with fractional anisotropy (FA) measures derived from diffusion tensor imaging (DTI) at 12 months CA. Materials and Methods DTI was performed in eight infants with PBI who were randomly assigned to kicking and treadmill stepping exercise or a no-training condition. Development was assessed using the Alberta Infant Motor Scale (AIMS) and the Gross Motor Function Classification System (GMFCS). FA values were derived from regions of interest (ROIs) in the middle third of the posterior limb of the internal capsule (PLIC) and the posterior thalamic radiation (PTR). Results Significant correlations were observed between motor development and FA measures. For PLIC, the correlation coefficients were 0.82 between FA and AIMS, and −0.92 between FA and GMFCS, while for PTR the corresponding correlation coefficients were 0.73 and −0.80, respectively. Conclusion Results of this study suggest that quantitative evaluation of white matter tracts using DTI at 12 months CA may be useful for assessment of brain plasticity in children. J. Magn. Reson. Imaging 2014;39:949–957. © 2013 Wiley Periodicals, Inc.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".