The Relationship between Preoperative Clinical Presentation and Quantitative MRI Features in Patients with Degenerative Cervical Myelopathy
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».