Quantifying neurodegeneration of the cervical cord and brain in degenerative cervical myelopathy: A multicentre study using quantitative <scp>magnetic resonance imaging</scp>
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Simultaneous assessment of neurodegeneration in both the cervical cord and brain across multiple centres can enhance the effectiveness of clinical trials. Thus, this study aims to simultaneously assess microstructural changes in the cervical cord and brain above the stenosis in degenerative cervical myelopathy (DCM) using quantitative magnetic resonance imaging (MRI) in a multicentre study. METHODS: We applied voxelwise analysis with a probabilistic brain/spinal cord template embedded in statistical parametric mappin (SPM-BSC) to process multi parametric mapping (MPM) including effective transverse relaxation rate (R2*), longitudinal relaxation rate (R1), and magnetization transfer (MT), which are indirectly sensitive to iron and myelin content. Regression analysis was conducted to establish associations between neurodegeneration and clinical impairment. Thirty-eight DCM patients (mean age ± SD = 58.45 ± 11.47 years) and 38 healthy controls (mean age ± SD = 41.18 ± 12.75 years) were recruited at University Hospital Balgrist, Switzerland and Toronto Western Hospital, Canada. RESULTS: Remote atrophy was observed in the cervical cord (p = 0.002) and in the left thalamus (0.026) of the DCM group. R1 was decreased in the periaqueductal grey matter (p = 0.014), thalamus (p = 0.001), corpus callosum (p = 0.0001), and cranial corticospinal tract (p = 0.03). R2* was increased in the primary somatosensory cortices (p = 0.008). Sensory impairments were associated with increased iron-sensitive R2* in the thalamus and periaqueductal grey matter in DCM. CONCLUSIONS: Simultaneous assessment of the spinal cord and brain revealed DCM-induced demyelination, iron deposition, and atrophy. The extent of remote neurodegeneration was associated with sensory impairment, highlighting the intricate and expansive nature of microstructural neurodegeneration in DCM, reaching beyond the stenosis level.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".