White matter myelin profiles linked to clinical subtypes of Parkinson's disease
Bibliographic record
Abstract
BACKGROUND: White matter (WM) microstructural integrity is important for effective brain functioning and alterations have been shown in many neurodegenerative diseases. PURPOSE: To investigate WM myelin profiles and their relation to clinical features of Parkinson's disease (PD). STUDY TYPE: Retrospective cross-sectional. POPULATION: In all, 29 PD subjects and 15 healthy controls. FIELD STRENGTH/SEQUENCE: Multiecho GRASE with 10 msec echo spacing and echo planar imaging (EPI) diffusion-weighted (b-value = 700 with 32 gradient directions) on a 3T scanner. ASSESSMENT: Myelin water fraction (MWF) and fractional anisotropy (FA) across 20 WM regions of interest (ROIs) were compared between groups. Partial least squares (PLS) was used to associate MWF and FA with clinical and behavioral measures. STATISTICAL TESTS: Group comparisons were done using two-sample t-tests. PLS was assessed with permutation tests. Bootstrapping was used to investigate the robustness of imaging features. RESULTS: No group differences in myelin content could be detected with univariate tests. A three-component PLS model linked MWF profiles to clinical phenotypes but no FA profiles. The three components appeared to follow along broad motor/nonmotor subtypes of "akinetic-rigid," "tremor-predominant," and "depression/apathy" subtypes, respectively. The first component showed associations between overall motor scores (r = -0.43, P = 0.0196) and cognitive performance (r = 0.44, P = 0.0171) with interhemispheric and long-range association fibers. A second component linked overall motor scores (r = -0.58, P = 0.0009) and tremor scores (r = -0.48, P = 0.0091) to predominantly projection fibers. The last component related depression (r = -0.60, P = 0.0006) and apathy scores (r = -0.66, P = 0.0001 and r = -49, P = 0.0072) to a mixture of association and projection fibers. DATA CONCLUSION: MWF was robustly linked to distinct clinical subtypes of PD and may serve as an additional tool to characterize the disease. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:164-174.
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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 | 0.002 |
| 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".