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Updated: Oct 28, 2025
Diffusion Tensor Magnetic Resonance Imaging in Chronic Spinal Cord Compression
Published on: May 7, 2019
Can Morphometric Analysis of Cervical Spondylotic Myelopathy Be a Tool for Surgical Outcome Prediction?
Sofia Tavares1, Gonçalo Guerreiro Costa1, Orlando Galego2
1Centro Hospitalar e Universitário de Coimbra, Neurosurgery Department, Coimbra, Portugal.
Background:
Cervical spondylotic myelopathy (CSM) is one of the leading causes of degenerative cervical myelopathy and the most common cause of spinal cord dysfunction in the elderly worldwide. Although there is emerging evidence that most patients improve after surgery, the key clinical and imaging factors predicting outcome remain uncertain. Our purpose is to evaluate preoperative and postoperative morphometric parameters on magnetic resonance imaging and their relation with neurological outcome at discharge and at 12-month follow-up.
Methods:
Morphometric features (volume, area, and antero-posterior diameter of the major stenotic section) were acquired by manual segmentation of the spinal canal using OsiriX open-source software and confronted with neurological outcome (at discharge and 12 months after surgery) using Nurick's scale.
Results:
Fifty-five patients (21 females and 34 males) with a mean age of 64.89 ± 11.95 years were analyzed. Recovery ratio was 2.44% ± 2.40% at discharge and 11.74% ± 2.50% at follow-up. Statistical analysis revealed a significant difference (P < .001) between Nurick's scale at admission versus discharge, at discharge versus follow-up at 1 year, and between admission and follow-up at 1 year. Morphometric changes (difference and ratio) between preoperative and postoperative measurements were also statistically significant (P < .001, paired samples t test). When linear regression was applied, volume difference was shown to have an influence on clinical improvement (P < .05; R = 0.519). Linear regression was also applied using recovery ratio at discharge and follow-up as dependent variables, with the same conclusion: volume difference between preoperative and postoperative measurements correlates with outcome improvement at 1 year after surgery.
Conclusions:
Acquisition of morphometric features might be useful in predicting surgical outcome in patients with CSM. This information can be used to inform patients of their long-term postoperative prognosis in the future with more accurate and standardized measurements.
