Wang S, Hu Y, Liu H, Yang K, Zhang X, Qu B, Yang H. Simplified S1 Vertebral Bone Quality Score in the Assessment of Patients with Vertebral Fragility Fractures.
World Neurosurg 2024;
185:e1004-e1012. [PMID:
38462067 DOI:
10.1016/j.wneu.2024.03.011]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 03/03/2024] [Accepted: 03/04/2024] [Indexed: 03/12/2024]
Abstract
OBJECTIVE
To evaluate the effectiveness of the S1 vertebral bone quality (VBQ) score in assessing bone quality among patients with vertebral fragility fractures (VFF). Additionally, whether the combination of S1 VBQ and Hounsfield unit (HU) values improves the predictive accuracy of VFF.
METHODS
Using lumbar noncontrast computed tomography and T1-weighted magnetic resonance imaging, we measured L1 HU values, S1 VBQ, and L1-L4 VBQ. To assess their predictive performance for VFF, we constructed receiver operating characteristic curves. We also compared the diagnostic efficacy of HU values with that of S1 VBQ and L1--L4 VBQ values for the joint diagnosis of VFF. The Delong test was used to compare the value of individual or combined predictions of VFF.
RESULTS
In comparison to the nonfracture group, all patients exhibited markedly elevated S1 VBQ and L1--L4 VBQ and notably reduced HU values (P < 0.001). Multivariate analysis revealed that elevated S1 VBQ, increased L1--L4 VBQ, and decreased HU values independently correlated with VFF development. The areas under the curve for VFF prediction were 0.806 for S1 VBQ, 0.799 for L1--L4 VBQ, and 0.820 for HU values. According to the Delong test, the combination of HU values with S1 VBQ/L1--L4 VBQ significantly improved the diagnostic accuracy.
CONCLUSIONS
The simplified S1 VBQ is a valuable tool for predicting the occurrence of VFF and can be used as an alternative to the L1--L4 VBQ. In addition, the combination of S1 VBQ and HU values can significantly improve the predictive value of VFF.
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