P1‐397: LATERAL VENTRICLE ENLARGEMENT AND CORTICAL THINNING IN IDIOPATHIC NORMAL‐PRESSURE HYDROCEPHALUS PATIENTS
Bibliographic record
Abstract
We utilized three-dimensional surface-based morphometric approach to investigate lateral ventricle shape between 2 groups: (1) idiopathic normal-pressure hydrocephalus (INPH) patients who had a positive response to the cerebrospinal fluid tap test (CSFTT) and (2) healthy controls. The aims of the study were (1) to evaluate the location of INPH-related structural abnormalities of the lateral ventricles and (2) to investigate relationships between lateral ventricular enlargement and cortical thinning in INPH patients. We hypothesized that INPH patients might show a characteristic pattern of lateral ventricular enlargement, and there may be unique relationships between lateral ventricular enlargement and cortical thinning in INPH patients. Thirty-three INPH patients and 23 healthy controls were imaged with MRI, including 3-dimensional volumetric images for surface-based morphometric analysis of the lateral ventricles. We used sparse canonical correlation analysis to show correlated regions of ventricular surface expansion and cortical thinning. A significant surface expansion in the INPH group was observed mainly in clusters bilaterally located in the superior portion of the lateral ventricles, which are adjacent to the high convexity of the frontal and parietal regions. INPH patients showed a significant bilateral expansion of the medial aspects of the frontal horns of the lateral ventricles to the surrounding brain regions, including the medial frontal lobe. The temporal horns of the lateral ventricles, which are located near the medial temporal lobe structures, were also expanded in the INPH group relative to the control group. The ventricular surface expansion, particularly noticeable in the superior portion, was associated with cortical thinning in the bilateral orbitofrontal cortex and bilateral rostral anterior cingulate cortex. The ventricular surface expansion was also associated with cortical thinning in the left parahippocampal cortex, left temporal pole, right insula, right inferior temporal cortex, and right fusiform gyrus. These results suggest that patients with INPH have unique patterns of ventricular surface expansion. Further, the relationship between ventricular surface expansion and cortical thinning may be potentially related to the pathogenesis of INPH and other comorbid neurodegenerative pathologies.
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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 | 0.001 | 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".