Microstructural and functional impairment of the basal ganglia in Wilson’s disease: a multimodal neuroimaging study
Bibliographic record
Abstract
Objectives: Magnetic susceptibility changes in brain MRI of Wilson's disease (WD) patients have been described in subcortical nuclei especially the basal ganglia. The objectives of this study were to investigate its relationship with other microstructural and functional alterations of the subcortical nuclei and the diagnostic utility of these MRI-related metrics. Methods: A total of 22 WD patients and 20 healthy controls (HCs) underwent 3.0T multimodal MRI scanning. Susceptibility, volume, diffusion microstructural indices and whole-brain functional connectivity of the putamen (PU), globus pallidus (GP), caudate nucleus (CN), and thalamus (TH) were analyzed. Receiver operating curve (ROC) was applied to evaluate the diagnostic value of the imaging data. Correlation analysis was performed to explore the connection between susceptibility change and microstructure and functional impairment of WD and screen for neuroimaging biomarkers of disease severity. Results: Wilson's disease patients demonstrated increased susceptibility in the PU, GP, and TH, and widespread atrophy and microstructural impairments in the PU, GP, CN, and TH. Functional connectivity decreased within the basal ganglia and increased between the PU and cortex. The ROC model showed higher diagnostic value of isotropic volume fraction (ISOVF, in the neurite orientation dispersion and density imaging model) compared with susceptibility. Severity of neurological symptoms was correlated with volume and ISOVF. Susceptibility was positively correlated with ISOVF in GP. Conclusion: Microstructural impairment of the basal ganglia is related to excessive metal accumulation in WD. Brain atrophy and microstructural impairments are useful neuroimaging biomarkers for the neurological impairment of WD.
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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".