Neuroimaging Features in Children with Optic Nerve Hypoplasia and Septo-Optic-Pituitary Dysplasia
Bibliographic record
Abstract
ABSTRACT Background: Optic nerve hypoplasia (ONH) and septo-optic-pituitary dysplasia (SOD) are common causes of congenital visual impairment. Our primary aim was to investigate the prevalence of abnormal neuroimaging features in patients with these disorders in Manitoba, Canada, and compare them with published reports. Methods: A retrospective neuroimaging review was performed in patients resident in Manitoba with ONH/SOD. Results: There were 128 patients ( M = 70) with ONH/SOD who had neuroimaging. Their mean age (SD) at the end of the study was 13.2 (7.5) years. Males were significantly more likely to have bilateral ONH and a small optic chiasm size, while females were more likely to have a left ONH and a small left optic chiasm size on neuroimaging ( p = 0.049). ONH and small optic chiasm size were seen in most patients on neuroimaging. Absent septum pellucidum was noted in 40%, small pituitary gland size in 28%, neuronal migration disorders (NMD) in 20% (>1 type and bilateral in 13 cases), corpus callosum abnormalities were present in 9%, while olfactory bulbs-tracts and olfactory sulci were absent in 8.6% of cases. Unilateral ONH was not significantly associated with other structural brain abnormalities, while NMD were significantly associated with other midline brain abnormalities including a symmetrically small optic chiasm size. Conclusion: The prevalence of structural neuroimaging abnormalities in our cohort with ONH/SOD was generally in the same range reported in other studies with corpus callosum abnormalities being relatively less common in our study. Bilateral NMD were relatively common among patients with NMD. The association between sex and ONH laterality requires further study.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".