Potential use of diffusion tensor imaging in level diagnosis of multilevel cervical spondylotic myelopathy

Abstract

STUDY DESIGN.: A prospective study on a series of consecutive patients. OBJECTIVE.: To investigate the use of diffusion tensor imaging (DTI) and orientation entropy in level localization in patients diagnosed with multilevel cervical spondylotic myelopathy (CSM). SUMMARY OF BACKGROUND DATA.: Multilevel CSM presents complex neurological signs that make level localization difficult. DTI is recently found to be able to assess the microstructural changes of the white matter caused by cord compression. METHODS.: Sixteen patients with CSM with multilevel compression were recruited. The level(s) responsible for the clinical symptoms were determined by detailed neurological examination, T2-weighted (T2W) magnetic resonance imaging (MRI), and DTI. On T2W MRI, anterior-posterior compression ratio and increased signal intensities were used to determine the affected level(s). The level diagnosis results from T2W MRI, increased signal intensities, DTI, and combination method were correlated to that of neurological examination on a level-to-level basis, respectively. The accuracy, sensitivity, and specificity were calculated. RESULTS.: When correlated with the clinical level determination, the weighted orientation entropy-based DTI analysis was found to have higher accuracy (82.76% vs. 75.86%) and sensitivity (84.62% vs. 76.92%) than those of the anterior-posterior compression ratio. The increased signal intensities have the highest specificity (100.00%) but the lowest accuracy (58.62%) and sensitivity (53.85%). When combined with the level diagnosis result of wOE with that of anterior-posterior compression ratio, it demonstrated the highest accuracy and sensitivity that were 93.10% and 96.15%, respectively, and equal specificity (66.67%) with using them individually. CONCLUSION.: DTI can be a useful tool to determine the pathological spinal cord levels in multilevel CSM. This information from orientation entropy-based DTI analysis, in addition to conventional MRI and clinical neurological assessment, should help spine surgeons in deciding the optimal surgical strategy. Copyright © 2014 Lippincott Williams & Wilkins.