Using a combined classification of increased signal intensity on Magnetic Resonance Imaging (MRI) to predict surgical outcome in cervical spondylotic myelopathy

Abstract

Background: The aim of this study was to verify whether the combined classification of increased signal intensity (ISI) on magnetic resonance imaging is more closely related to surgical outcomes than signal quality changes or signal longitudinal extent changes alone and to evaluate whether the combined classification ISI method could be used to predict surgical outcomes in cervical spondylotic myelopathy. Material/Methods: Eighty-four patients (61 men and 23 women) who underwent surgery for cervical spondylotic myelopathy were included in this retrospective study. The patterns of ISI were classified into 3 categories based on (1) the quality of ISI into Grade 0: none, Grade 1: faint (fuzzy), and Grade 2: intense (sharp); (2) the longitudinal extent of ISI into none, focal, and multisegmental; and (3) the combined classification of the quality and longitudinal extent into Type 1 (none/none), Type 2 (focal/faint), Type 3 (focal/intense), Type 4 (multisegmental/faint), and Type 5 (multisegmental/intense). The multifactorial effects of variables were studied. A stepwise regression analysis was performed to verify whether this combined classification could predict outcome. Results: Of the 3 categories, the combined classification type of ISI was most closely related to recovery rate. Stepwise regression analysis confirmed the significance of combined classification of ISI as a predictor for surgical outcome. Conclusions: A combined classification of ISI is more closely related to surgical outcomes than either signal quality changes or signal longitudinal extent changes alone and it could be used as a meaningful indicator for predicting surgical outcomes. We recommend further studies to confirm this finding.