Volumetric brain analysis in neurosurgery: Part 2. Brain and CSF volumes discriminate neurocognitive outcomes in hydrocephalus
Bibliographic record
Abstract
OBJECT: The evaluation of hydrocephalus remains focused on ventricular size, yet the goal of treatment is to allow for healthy brain development. It is likely that brain volume is more related to cognitive development than is fluid volume in children with hydrocephalus. This study tests this hypothesis by comparing brain and fluid volumes with neurocognitive outcome in pediatric patients with hydrocephalus. METHODS: Warf and colleagues previously acquired CT scans for pediatric patients in Uganda with myelomeningocele, measured frontal-occipital horn ratio (FOHR), and administered the modified Bayley Scales of Infant Development, third edition (BSID-III) to measure neurocognitive outcome that did not correlate with FOHR. In this present study, brain and fluid volumes were measured in 33 of these patients, 26 of whom required surgical treatment for hydrocephalus. Linear discrimination analysis (LDA) was used to test whether age-normalized brain and fluid volumes can discriminate neurocognitive outcome. RESULTS: Hydrocephalic patients show normal to small brain volumes and substantially larger fluid volumes compared with normal values. FOHR correlates highly with fluid volume (r=0.84, p<0.001) and substantially less with brain volume (r=-0.37, p=0.03), while brain and fluid volumes do not correlate with each other (p=0.99). Brain and CSF volumes correlated best with fine motor (p=0.03, p=0.01), cognitive (p=0.05, p=0.09), and expressive communication (p=0.08, p=0.08) scores. A combination of these 3 scores was used as a multivariate measure of neurocognitive outcome. Brain volume alone, unlike fluid volume, could discriminate high from low cognitive outcome (by t-test and ANOVA). It was shown that a combination of age-normalized brain and fluid volumes can discriminate neurocognitive outcome by 2-way LDA (p<0.01) and 3-way LDA (p<0.01). The multivariate LDA demonstrated the contribution of large fluid volume to a decrement in cognition. CONCLUSIONS: Hydrocephalus is treated by normalizing CSF, but normal brain development depends on brain growth. A combination of brain and CSF volumes appears to be significantly more powerful at predicting good versus poor neurocognitive outcomes in patients with hydrocephalus than either volume alone.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".