Development of a Diagnostic Model for Differentiating Tuberculous Spondylitis and Pyogenic Spondylitis with MRI: A Multicenter Retrospective Observational Study.

Abstract

Multicenter retrospective observational study. This study aimed to distinguish tuberculous spondylitis (TS) from pyogenic spondylitis (PS), using magnetic resonance imaging (MRI). Further, a novel diagnostic model for differential diagnosis was developed. TS and PS are the two most common spinal infections. Distinguishing between these types clinically is challenging. Delayed diagnosis can lead to deficits or kyphosis. Currently, there is a lack of radiology-based diagnostic models for TS and PS. We obtained radiological images from MRI imaging of patients with TS and PS and applied least absolute shrinkage and selection operator (LASSO) regression to select the optimal features for a predictive model. Predictive models were built using multiple logistic regression analysis. Clinical utility was determined using decision curve analysis (DCA) and internal validation was performed using bootstrap resampling. A total of 201 patients with TS (n=105) or PS (n=96) were enrolled. We identified significant differences in MRI features between both groups. We found that non-contiguous multi- and single-vertebral body involvement were common in TS and PS, respectively. Vertebral bone lesions were more severe in the TS group than in the PS group (Z=-4.553，P<0.001). The patients in the TS group were also more prone to vertebral intraosseous, epidural, and paraspinal abscesses (P<0.001). A total of 8 predictors were included in the diagnostic model. Analysis of the calibration curve and area under the receiver operating characteristic curve suggested that the model was well-calibrated with a high prediction accuracy. This is the largest study comparing MRI features in TS and PS and the first to develop an MRI-based nomogram which may help clinicians distinguish between TS and PS.