Combined Diffusion Tensor Imaging and Apparent Transverse Relaxation Rate Differentiate Parkinson Disease and Atypical Parkinsonism
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Both diffusion tensor imaging and the apparent transverse relaxation rate have shown promise in differentiating Parkinson disease from atypical parkinsonism (particularly multiple system atrophy and progressive supranuclear palsy). The objective of the study was to assess the ability of DTI, the apparent transverse relaxation rate, and their combination for differentiating Parkinson disease, multiple system atrophy, progressive supranuclear palsy, and controls. MATERIALS AND METHODS: A total of 106 subjects (36 controls, 35 patients with Parkinson disease, 16 with multiple system atrophy, and 19 with progressive supranuclear palsy) were included. DTI and the apparent transverse relaxation rate measures from the striatal, midbrain, limbic, and cerebellar regions were obtained and compared among groups. The discrimination performance of DTI and the apparent transverse relaxation rate among groups was assessed by using Elastic-Net machine learning and receiver operating characteristic curve analysis. RESULTS: Compared with controls, patients with Parkinson disease showed significant apparent transverse relaxation rate differences in the red nucleus. Compared to those with Parkinson disease, patients with both multiple system atrophy and progressive supranuclear palsy showed more widespread changes, extending from the midbrain to striatal and cerebellar structures. The pattern of changes, however, was different between the 2 groups. For instance, patients with multiple system atrophy showed decreased fractional anisotropy and an increased apparent transverse relaxation rate in the subthalamic nucleus, whereas patients with progressive supranuclear palsy showed an increased mean diffusivity in the hippocampus. Combined, DTI and the apparent transverse relaxation rate were significantly better than DTI or the apparent transverse relaxation rate alone in separating controls from those with Parkinson disease/multiple system atrophy/progressive supranuclear palsy; controls from those with Parkinson disease; those with Parkinson disease from those with multiple system atrophy/progressive supranuclear palsy; and those with Parkinson disease from those with multiple system atrophy; but not those with Parkinson disease from those with progressive supranuclear palsy, or those with multiple system atrophy from those with progressive supranuclear palsy. CONCLUSIONS: DTI and the apparent transverse relaxation rate provide different but complementary information for different parkinsonisms. Combined DTI and apparent transverse relaxation rate may be a superior marker for the differential diagnosis of parkinsonisms.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".