Association of brain morphology and phenotypic profile in patients with unruptured intracranial aneurysm
Bibliographic record
Abstract
Introduction Studies have found a varying degree of cognitive, psychosocial, and functional impairments in patients with unruptured intracranial aneurysms (UIAs), whereas the neural correlates underlying these impairments remain unknown. Methods To examine the brain morphological alterations and white matter lesions in patients with UIA, we performed a range of structural analyses to examine the brain morphological alterations in patients with UIA compared with healthy controls (HCs). Twenty-one patients with UIA and 23 HCs were prospectively enrolled into this study. Study assessment consisted of a brain magnetic resonance imaging (MRI) scan with high-resolution T1-weighted and T2-weighted imaging data, a Montreal Cognitive Assessment (MoCA), and laboratory tests including blood inflammatory markers and serum lipids. Brain MRI data were processed for cortical thickness, local gyrification index (LGI), volume and shape of subcortical nuclei, and white matter lesions. Results Compared to the HCs, patients with UIA showed no significant differences in cortical thickness but decreased LGI values in the right posterior cingulate cortex, retrosplenial cortex, cuneus, and lingual gyrus. In addition, decreased LGI values correlated with decreased MoCA score (r = 0.498, p = 0.021) and increased white matter lesion scores (r = −0.497, p = 0.022). The LGI values were correlated with laboratory values such as inflammatory markers and serum lipids. Patients with UIA also showed significant regional atrophy in bilateral thalami as compared to the HCs. Moreover, the LGI values were significantly correlated with thalamic volume in the HCs (r = 0.4728, p = 0.0227) but not in the patients with UIA (r = 0.11, p = 0.6350). Discussion The decreased cortical gyrification, increased white matter lesions, and regional thalamic atrophy in patients with UIA might be potential neural correlates of cognitive changes in UIA.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".