Parkinson’s disease in the spinal cord: An exploratory study to establish T2*w, MTR and diffusion-weighted imaging metric values
Bibliographic record
Abstract
Parkinson's disease (PD) is primarily defined by brain pathology, including dopamine neuron degeneration and α-synuclein aggregation. Emerging evidence suggests that the spinal cord is also affected, with ex-vivo studies reporting abnormal α-synuclein protein aggregation within the spinal cord of PD patients. While advanced imaging techniques, such as diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging (NODDI), T2*-weighted (T2*w) imaging, and the magnetization transfer ratio (MTR) have demonstrated potential for detecting PD-related changes in the brain, their application to uncover spinal cord alterations remains unexplored. This study is the first to investigate MRI-derived microstructural metrics in the spinal cord of PD patients, comparing them to healthy controls. Although this study found limited microstructural or structural differences in the spinal cord between PD patients and healthy controls, these findings are consistent with recent results from PD mouse models and complement an earlier functional MRI study using the same cohort, where significant findings were observed. Our lack of significant structural findings may suggest that functional spinal cord changes are more sensitive markers of Parkinson's disease progression-particularly in relation to clinical measures such as the Unified Parkinson's Disease Rating Scale (UPDRS). These results highlight the need for further research to better understand how PD-related alterations in the spinal cord compare to normal aging processes and relate to functional changes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".