Magnetic resonance imaging assessment of degenerative cervical myelopathy: a review of structural changes and measurement techniques
Bibliographic record
Abstract
Degenerative cervical myelopathy encompasses a spectrum of age-related structural changes of the cervical spine that result in static and dynamic injury to the spinal cord and collectively represent the most common cause of myelopathy in adults. Although cervical myelopathy is determined clinically, the diagnosis requires confirmation via imaging, and MRI is the preferred modality. Because of the heterogeneity of the condition and evolution of MRI technology, multiple techniques have been developed over the years in an attempt to quantify the degree of baseline severity and potential for neurological recovery. In this review, these techniques are categorized anatomically into those that focus on bone, ligaments, discs, and the spinal cord. In addition, measurements for the cervical spine canal size and sagittal alignment are also described briefly. These tools have resulted collectively in the identification of numerous useful parameters. However, the development of multiple techniques for assessing the same feature, such as cord compression, has also resulted in a number of challenges, including introducing ambiguity in terms of which methods to use and hindering effective comparisons of analysis in the literature. In addition, newer techniques that use advanced MRI are emerging and providing exciting new tools for assessing the spinal cord in patients with degenerative cervical myelopathy.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".