A Combined Scoring Method Based on ¹⁸F-FDG PET/CT for Distinguishing Spinal Infection From Malignancy

Abstract

Study Design. 

Retrospective study.

Objective. 

This study aimed to explore the additional value of fluorine-18 fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) for the detection of early-stage and atypical spinal infections and to find the best combination of indicators from laboratory and imaging systems for higher diagnostic efficiency.

Summary of Background Data. 

Diagnosis of early-stage and atypical spinal infections may be challenging for clinicians. It is particularly important to distinguish spinal infection from malignancy to develop a timely treatment strategy and avoid unnecessary biopsy or surgery.

Materials and Methods. 

All patients with a discharge diagnosis of spinal infection or malignancy who underwent ¹⁸F-FDG PET/CT scans before spinal biopsy between January 1, 2014, and July 30, 2021, were included. Laboratory and imaging data were assessed. A receiver operating characteristic (ROC) curve was created, and the best cut-off point and cumulated area under the curve (AUC) were obtained to distinguish between spinal infection and malignancy. Kappa values were used to assess the agreement between the ¹⁸F-FDG PET/CT and MRI findings. Binary logistic regression was used to screen for statistically significant indicators and imaging findings.

Results. 

A total of 71 patients with confirmed spinal infections (n=30) or malignancies (n=41) were included in this study. Elevated ESR and significantly elevated tumor biomarkers or positive FLCs assay were significantly different between the two groups. In addition to the total lesion glycolysis of the involved vertebral bodies derived from ¹⁸F-FDG PET/CT, four imaging findings (consecutive multilevel vertebral lesions, intervertebral disc, vertebral arch, and extraspinal involvement) also showed significant differences between the two groups (P≤0.010). A combined scoring method based on the above seven indicators was designed with an overall classification accuracy of 95.2%, and it identified all patients with spinal infections (100%, 28/28). In addition, moderate-to-excellent agreement could be reached for the involvement of intervertebral discs, paravertebral soft tissues, and vertebral arches derived from MRI and¹⁸F-FDG PET/CT.

Conclusions. 

The combined scoring method based on ¹⁸F-FDG PET/CT provided excellent overall accuracy in distinguishing spinal infections from malignancies. This approach may prove useful for patients with MRI contraindications or with equivocal results following laboratory tests or traditional imaging when there is high suspicion for spinal infections or malignancy.