Correlation of MRI Markers with Clinical Features in Multiple System Atrophy
Bibliographic record
Abstract
ABSTRACT BACKGROUND AND PURPOSE: Multiple system atrophy (MSA) is a progressive neurodegenerative disorder with two main subtypes: MSA with predominant cerebellar ataxia (MSA-C) and MSA with predominant parkinsonism (MSA-P). The latest diagnostic criteria emphasize the importance of neuroimaging markers from magnetic resonance imaging (MRI) alongside clinical symptomatology assessment. This study investigates the relationship between visual MRI markers and MSA subtypes, clinical features, and cerebral glucose metabolism and striatal dopaminergic degeneration. MATERIALS AND METHODS: 89 MSA patients (67 MSA-P, 22 MSA-C) underwent extensive clinical and neuropsychiatric evaluations, routine MRI scans to assess markers like the “hot cross bun” (HCB) sign, putaminal iron deposition, midbrain to pons (M/P) ratio, and cerebellar atrophy. Positron emission tomography (PET) imaging with 18F-fluorodeoxyglucose (18F-FDG) and 11C-2β-carbomethoxy-3β(4-fluorophenyl) tropane (11C-CFT) were conducted to evaluate brain metabolism and striatal dopaminergic uptake abnormalities. RESULTS: Canonical Correlation Analysis revealed significant associations between clinical symptoms and MRI markers, particularly HCB sign, M/P ratio, and putaminal iron deposition. The HCB sign and M/P ratio correlated with cerebellar dysfunction, while putaminal iron deposition correlated with parkinsonism severity, particularly in MSA-P. Cerebellar and putaminal metabolism negatively correlated with their respective structural changes. However, putaminal iron deposition showed no significant correlation with striatal dopaminergic uptake. CONCLUSIONS: Visual MRI markers are crucial for diagnosing MSA and delineating disease subtype and symptom severity. Supratentorial and infratentorial MRI markers reflect the severity of parkinsonism and cerebellar dysfunction, respectively. Putaminal iron deposition reflects the severity of parkinsonism, suggesting that iron deposition plays an important role in the pathophysiological mechanisms contributing to parkinsonism in MSA. ABBREVIATIONS: CCA = Canonical correlation analysis; 11C-CFT = 11C-2β-carbomethoxy-3β-(4-fluorophenyl) tropane; 18F-FDG = 18Ffluorodeoxyglucose; GCIs = glial cytoplasmic inclusions; HAMA = Hamilton anxiety scale; HAMD = Hamilton depression scale; HCB = hot cross bun; H-Y = Hoehn and Yahr; MCP = middle cerebellar peduncles; MMSE = mini-mental state examination; MoCA = Montreal cognitive assessment; M/P = midbrain to pons; MSA = multiple system atrophy
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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) | 0.003 | 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".