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A diagnostic model for differentiating tuberculous spondylitis from pyogenic spondylitis on computed tomography images

  • Musculoskeletal
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To develop and evaluate a logistics regression diagnostic model based on computer tomography (CT) features to differentiate tuberculous spondylitis (TS) from pyogenic spondylitis (PS).

Methods

Demographic and clinical features were collected from the Electronic Medical Record System. Data of bony changes seen on CT images were compared between the PS (n = 61) and TS (n = 51) groups using the chi-squared test or t test. Based on features that were identified to be significant, a diagnostic model was developed from a derivation set (two thirds) and evaluated in a validation set (one third). The sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated.

Results

The width of bone formation around the vertebra and sequestrum was greater in the TS group. There were significant differences between the two groups in the horizontal and longitudinal location of erosion and the morphology of axial bone destruction and sagittal residual vertebra. Kyphotic deformity and overlapping vertebrae were more common in the TS group. A diagnostic model that included eight predictors was developed and simplified to include the following six predictors: width of the bone formation surrounding the vertebra, longitudinal location, axial-specific erosive morphology, specific morphology of the residual vertebra, kyphotic deformity, and overlapping vertebrae. The simplified model showed good sensitivity, specificity, and total accuracy (85.59%, 87.80%, and 86.50%, respectively); the AUC was 0.95, indicating good clinical predictive ability.

Conclusions

A diagnostic model based on bone destruction and formation seen on CT images can facilitate clinical differentiation of TS from PS.

Key Points

• We have developed and validated a simple diagnostic model based on bone destruction and formation observed on CT images that can differentiate tuberculous spondylitis from pyogenic spondylitis.

• The model includes six predictors: width of the bone formation surrounding the vertebra, longitudinal location, axial-specific erosive morphology, specific morphology of the residual vertebra, kyphotic deformity, and overlapping vertebrae.

• The simplified model has good sensitivity, specificity, and total accuracy with a high AUC, indicating excellent predictive ability.

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Abbreviations

AUC:

Area under the receiver operating characteristic curve

CT:

Computed tomography

NPV:

Negative predictive value

PPV:

Positive predictive value

PS:

Pyogenic spondylitis

TS:

Tuberculous spondylitis

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Acknowledgements

We sincerely express our gratitude to Meng Gao for data acquisition.

Funding

The authors state that this work has not received any funding.

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Authors and Affiliations

  1. Department of Spine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, No. 9677 in Jingshi Road, Jinan City, China

    Xiaoyang Liu, Jianmin Sun & Xingang Cui

  2. Department of Neurology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China

    Meimei Zheng

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  1. Xiaoyang Liu
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  2. Meimei Zheng
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  3. Jianmin Sun
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  4. Xingang Cui
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Correspondence to Xingang Cui.

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Guarantor

The scientific guarantor of this publication is Xingang Cui.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Informed consent was obtained from all participants

Ethical approval

Institutional Review Board approval was obtained.

Study subjects or cohorts overlap

Some subjects or cohorts have been previously reported in journal articles (Eur Spine J; 29: 1490-1498; Spine (Phila Pa 1976); 42: 113-121).

Methodology

• retrospective

• diagnostic or prognostic study

• performed at one institution

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Liu, X., Zheng, M., Sun, J. et al. A diagnostic model for differentiating tuberculous spondylitis from pyogenic spondylitis on computed tomography images. Eur Radiol 31, 7626–7636 (2021). https://doi.org/10.1007/s00330-021-07812-1

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  • DOI: https://doi.org/10.1007/s00330-021-07812-1

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