Quantitative Assessment of Deep Gray Matter Susceptibility and Correlation With Cognition in Patients With Liver Cirrhosis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Accumulation of metals quantified by quantitative susceptibility mapping (QSM) in deep gray matter (DGM) and their impact on cognition have not been studied in patients with liver cirrhosis. This study aims to use QSM to investigate the association between DGM susceptibility and cognition in cirrhotic patients. METHODS: Thirty cirrhotic patients and 30 age-, gender-, and education-matched controls were imaged using a multiecho gradient-echo sequence for QSM analysis in a 3T scanner. The susceptibility values were determined for the caudate nucleus (CN), putamen (PU), globus pallidus (GP), thalamus (TH), red nucleus (RN), substantia nigra (SN), and dentate nucleus (DN). All subjects underwent number connection test A (NCT-A), digit substitution test (DST), and Montreal Cognitive Assessment (MoCA). Comparisons between the two groups and the correlation between the susceptibility values and neuropsychological scores were analyzed. RESULTS: The susceptibility values of bilateral CN, TH, and RN were significantly lower in cirrhotic patients. Cirrhotic patients exhibited significantly prolonged NCT-A time and decreased DST and MoCA scores. The NCT-A, DST, MoCA, and sub-domain scores were correlated with susceptibility values of RN, DN, SN, and CN, respectively. The susceptibility value of the left RN was a predictor variable for the DST, MoCA, and visuospatial-executive scores; those of the right CN and left RN were predictor variables for the naming score, and that of the left SN was an independent predictor variable for the language score. CONCLUSIONS: Altered susceptibility values of DGM measured by QSM are potential quantitative indicators of cognitive impairment in cirrhotic patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".