Predictive Value of Diffusion Magnetic Resonance Imaging for the Postoperative Outcome of Cervical Spondylotic Myelopathy

This study used multi-factorial linear quantile mixed-effects regression models to predict the outcome of cervical spondylotic myelopathy (CSM) patients one year after surgery based on MRI. Six models were constructed using the linear quantile mixed model and linear mixed-effects regression model based on the diffusion magnetic resonance imaging (dMRI) data, all the imaging data (dMRI & Conventional MRI), and all the registered data (dMRI & Conventional MRI & clinical data). We found that fractional anisotropy (FA) values quantified by preoperative dMRI could predict the surgical outcome of CSM and showed a significant positive correlation with the postoperative outcome.