Comparison of spinal magnetic resonance imaging and classical clinical factors in predicting motor capacity in amyotrophic lateral sclerosis
- PMID: 37103756
- DOI: 10.1007/s00415-023-11727-w
Comparison of spinal magnetic resonance imaging and classical clinical factors in predicting motor capacity in amyotrophic lateral sclerosis
Abstract
Background: Motor capacity is crucial in amyotrophic lateral sclerosis (ALS) clinical trial design and patient care. However, few studies have explored the potential of multimodal MRI to predict motor capacity in ALS. This study aims to evaluate the predictive value of cervical spinal cord MRI parameters for motor capacity in ALS compared to clinical prognostic factors.
Methods: Spinal multimodal MRI was performed shortly after diagnosis in 41 ALS patients and 12 healthy participants as part of a prospective multicenter cohort study, the PULSE study (NCT00002013-A00969-36). Motor capacity was assessed using ALSFRS-R scores. Multiple stepwise linear regression models were constructed to predict motor capacity at 3 and 6 months from diagnosis, based on clinical variables, structural MRI measurements, including spinal cord cross-sectional area (CSA), anterior-posterior, and left-to-right cross-section diameters at vertebral levels from C1 to T4, and diffusion parameters in the lateral corticospinal tracts (LCSTs) and dorsal columns.
Results: Structural MRI measurements were significantly correlated with the ALSFRS-R score and its sub-scores. And as early as 3 months from diagnosis, structural MRI measurements fit the best multiple linear regression model to predict the total ALSFRS-R (R2 = 0.70, p value = 0.0001) and arm sub-score (R2 = 0.69, p value = 0.0002), and combined with DTI metric in the LCST and clinical factors fit the best multiple linear regression model to predict leg sub-score (R2 = 0.73, p value = 0.0002).
Conclusions: Spinal multimodal MRI could be promising as a tool to enhance prognostic accuracy and serve as a motor function proxy in ALS.
Keywords: Amyotrophic lateral sclerosis; Biomarkers; Disease progression rate; Motor neuron disorder; Spinal cord MRI.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.
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