Multimodal Imaging of Substantia Nigra in Parkinson's Disease with Levodopa‐Induced Dyskinesia
Bibliographic record
Abstract
BACKGROUND: Degeneration of the substantia nigra (SN) may contribute to levodopa-induced dyskinesia (LID) in Parkinson's disease (PD), but the exact characteristics of SN in LID remain unclear. OBJECTIVE: To further understand the pathogenesis of patients with PD with LID (PD-LID), we explored the structural and functional characteristics of SN in PD-LID using multimodal magnetic resonance imaging (MRI). METHODS: Twenty-nine patients with PD-LID, 37 patients with PD without LID (PD-nLID), and 28 healthy control subjects underwent T1-weighted MRI, quantitative susceptibility mapping, neuromelanin-sensitive MRI, multishell diffusion MRI, and resting-state functional MRI. Different measures characterizing the SN were obtained using a region of interest-based approach. RESULTS: Compared with patients with PD-nLID and healthy control subjects, the quantitative susceptibility mapping values of SN pars compacta (SNpc) were significantly higher (P = 0.049 and P = 0.00002), and the neuromelanin contrast-to-noise ratio values in SNpc were significantly lower (P = 0.012 and P = 0.000002) in PD-LID. The intracellular volume fraction of the posterior SN in PD-LID was significantly higher compared with PD-nLID (P = 0.037). Resting-state fMRI indicated that PD-LID in the medication off state showed higher functional connectivity between the SNpc and putamen compared with PD-nLID (P = 0.031), and the functional connectivity changes in PD-LID were positively correlated with Unified Dyskinesia Rating Scale total scores (R = 0.427, P = 0.042). CONCLUSIONS: Our multimodal imaging findings highlight greater neurodegeneration in SN and the altered nigrostriatal connectivity in PD-LID. These characteristics provide a new perspective into the role of SN in the pathophysiological mechanisms underlying PD-LID. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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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 | 0.001 |
| 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".