The Relationship between Preoperative Clinical Presentation and Quantitative MRI Features in Patients with Degenerative Cervical Myelopathy
Bibliographic record
Abstract
Introduction Degenerative Cervical Myelopathy (DCM) encompasses a group of degenerative conditions of the cervical spine, including cervical spondylotic myelopathy (CSM) and ossification of the posterior longitudinal ligament (OPLL), that result in spinal cord pathology through static and dynamic injury mechanisms. While there are a constellation of degenerative findings that present in patients with DCM on MRI, large studies have shown that cervical cord compression and signal changes on MRI can present in asymptomatic or population based cohorts as well. It is therefore the objective of the present research to investigate the correlations between clinical and MRI findings and address this area of controversy. Material and Methods One hundred and fourteen patients enrolled in the prospective and multicenter AOSpine CSM North American study with complete MRI and clinical data were evaluated. Patients were enrolled if they had ≥1 clinical signs of myelopathy. Mid-sagittal MRIs were assessed for maximum spinal cord compression (MSCC) and maximum cord compromise (MCC). Additionally, the presence of T1 and T2 signal changes assessed, and the degree of T2 signal hyperintensity deviation was evaluated by computing a signal change ratio (SCR). MRI features were then statistically related with the presence of upper and lower limb neurological symptoms as well as generalized neurological dysfunction using t-tests. The relationship between duration of symptoms and quantitative MRI features was assessed using Spearman's rank correlation coefficient. Results The average T2 signal change ratio at the region of interest was 1.31, and the mean MCC and MSCC were ~49% and 34%, respectively. Numb hands ( p = 0.01) and Hoffmann's sign ( p = 0.003) were associated with greater MSCC; broad-based, unstable gait ( p = 0.042), impairment of gait ( p = 0.008) and Hoffmann's sign ( p = 0.013) were associated with greater MCC; Numb hands ( p = 0.037), Hoffmann's sign ( p = 0.017), Babinski sign ( p = 0.002), lower limb spasticity ( p = 0.011), L'Hermitte's phenomena ( p = 0.045), hyperreflexia ( p = 0.004), and presence of T1 hypointensity were associated with a greater deviation of signal intensity on T2 MRI. Patients with the presence of T2 signal hyperintensity also had greater MSCC ( p < 0.001) and MCC ( p < 0.001). Patients with L'Hermitte's phenomenon had a statistically significant lower SCR ( p = 0.045), indicating that they more commonly presented with diffuse and faint, or absence of T2 signal hyperintensities. Conclusion MSCC and MCC were predominately associated with upper limb and lower limb manifestations, respectively. SCR was associated with upper limb, lower limb and general neurological deficits. Hoffmann's sign was the only clinical parameter which occurred more commonly in patients with a greater MSCC, MCC and SCR, supporting its role as a sensitive diagnostic tool. L'Hermitte's phenomenon presented more commonly in patients with a lower SCR and thus may serve to indicate mild pathology and potential for reversibility. Going forward, it would be interesting to investigate these correlations over multiple preoperative time periods to evaluate the validity and evolution of these relationships. Ultimately, the culmination of such research may serve as a prelude to the construction of an evidence based prediction model that may help to differentiate between patients that remain stable and identify those who are likely to deteriorate without surgical intervention.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".