• Jin Wang, Zhaoxin Li, Xiansu Chi, Yungang Chen, Huaxin Wang, Xiaoying Wang, Kaiying Cui, Qing Wang, Tongxin Lu, Jianhu Zheng, Qiang Zhang, and Yanke Hao.
• Shandong University of Traditional Chinese Medicine, Jinan, China.
• Spine. 2024 Jan 1; 49 (1): 344534-45.

Study DesignMulticenter retrospective observational study.ObjectiveThis 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.Summary Of Background DataTS 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.MethodsWe obtained radiologic images from MRI imaging of patients with TS and PS and applied the least absolute shrinkage and selection operator 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, and internal validation was performed using bootstrap resampling.ResultsA 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 noncontiguous multivertebral 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 high prediction accuracy.ConclusionsThis 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.Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.

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