Neuroanatomical Changes in Parkinson’s Disease: Neuroimaging Evaluation of Pedunculopontine Nucleus (P2.002)
Bibliographic record
Abstract
Objective: Our objective was to determine whether changes in the non-dopaminergic pedunculopontine nucleus (PPN) region could be shown in Parkinson’s disease (PD) with MRI, a non-invasive measurement. We hypothesize that these changes may be associated with development of dopamine (DA) non-responsive features. Background: There’s increasing evidence that PD is more complex than a simple DA responsive motor disorder, particularly in advanced stages. Balance impairment and gait disturbances, such as freezing, are often unresponsive to DA replacement therapy. The PPN is involved in locomotion. Rostral PPN neurons are important in the initiation of programmed movements while other PPN neurons provide feedback to basal ganglia and thalamus. A significant loss of PPN neurons is evident in PD from autopsy study. PPN stimulation has been shown to improve gait difficulties. Design/Methods: Optimally treated PD patients with gait/balance changes from the Movement Disorders Program at University of Alberta were enrolled (n=21) in this study. Healthy age-matched controls (n=9) were also recruited. Diffusion tensor imaging was performed at 1.5T using 30 directions of diffusion gradient. Midbrain images at the level of superior cerebellar peduncle (SCP) decussation were analyzed by placing regions of interest (2.5-3mm diameter) between medial lemniscus and SCP. Similar regions were placed on corticospinal tract (CST) at the same level for comparison. Fractional anisotropy (FA) and mean diffusivity (MD) were calculated using ExploreDTI. Differences between the 2 groups were analyzed using Student’s t-test. Results: Patients with PD had decreased FA (p<0.05) in the PPN region compared to controls. There was no difference in MD, nor any difference in either measurement in CST between the 2 groups. Conclusion: These data support the presence of neuropathological changes in the PPN in PD. Future studies are required to elucidate changes in PPN connections with other structures and the relationship with balance/gait difficulties in PD.
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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 | 0.000 |
| 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) | 0.001 | 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".