Quantitative Susceptibility Mapping Changes Relate to Gait Issues in Parkinson’s Disease
Bibliographic record
Abstract
ABSTRACT: Background: Quantitative susceptibility mapping (QSM) demonstrates elevated iron content in Parkinson’s disease (PD) patients within the basal ganglia, though it has infrequently been studied in relation to gait difficulties including freezing of gait (FOG). Our purpose was to relate QSM of basal ganglia and extra-basal ganglia structures with qualitative and quantitative gait measures in PD. Methods: This case–control study included PD and cognitively unimpaired (CU) participants from the Comprehensive Assessment of Neurodegeneration and Dementia study. Whole brain QSM was acquired at 3T. Region of interests (ROIs) were drawn blinded manually in the caudate nucleus, putamen, globus pallidus, pulvinar nucleus of the thalamus, red nucleus, substantia nigra, and dentate nucleus. Susceptibilities of ROIs were compared between PD and CU. Items from the FOG questionnaire and quantitative gait measures from PD participants were compared to susceptibilities. Results: Twenty-nine participants with PD and 27 CU participants were included. There was no difference in susceptibility values in any ROI when comparing CU versus PD (p > 0.05 for all). PD participants with gait impairment (n = 23) had significantly higher susceptibility in the putamen (p = 0.008), red nucleus (p = 0.01), and caudate nucleus (p = 0.03) compared to those without gait impairment (n = 6). PD participants with FOG (n = 12) had significantly higher susceptibility in the globus pallidus (p = 0.03) compared to those without FOG (n = 17). Among quantitative gait measures, only stride time variability was significantly different between those with and without FOG (p = 0.04). Conclusion: Susceptibilities in basal ganglia and extra-basal ganglia structures are related to qualitative measures of gait impairment and FOG 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 | 0.001 | 0.003 |
| 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".