Volumetric MRI Analysis of a Case of Severe Ventriculomegaly
Bibliographic record
Abstract
We present a case of a 60-year-old male referred to a tertiary psychiatric facility for diagnostic assessment due to low mood and behavioral changes. Neurological examination of the patient was unremarkable. Magnetic resonance imaging (MRI) indicated overt ventriculomegaly with gross dilatation of lateral and third ventricles. Manual segmentation of gray matter, white matter and cerebrospinal fluid demonstrated that the patient had a ventricular volume almost 46 times greater than that of healthy volunteers in the same age range. Despite his striking degree of ventriculomegaly and cortical thinning, he presented primarily with psychiatric and cognitive complaints. These represented a major neurocognitive disorder. His behavior improved with a structured environment and routine instituted by the treating team. This is a dramatic example of the brain's response to extreme structural remodeling. Elements of pluripotentiality may counteract degeneracy to preserve functions in cases of serious structural stress in the brain. Changes in the neural circuitry of emotional processing, and/or disruption in signaling pathways important for synaptogenesis may influence depression pathophysiology. How this circuitry is modified in cases of extreme structural stress such as long-standing overt ventriculomegaly, is unclear. This case demonstrates the ability of the brain to generate a normal phenotype despite structural changes that seem incompatible with advanced cognitive function, illustrating the substantial potential for adaptability and plasticity in the brain.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".