Abstract
OBJECTIVES: To optimize cervical vertebral bone quality (C-VBQ) score and explore its effectiveness in predicting cage subsidence in Anterior Cervical Corpectomy and Fusion (ACCF) and identify a new method for evaluating subsidence without different equipment and image scale interference. METHODS: Collecting demographic, imaging, and surgical related information. Measuring Cage Subsidence with a new method. Multifactorial logistic regression was used to identify risk factors associated with subsidence. Pearson's correlation was used to determine the relationship between C-VBQ and computed tomography (CT) Hounsfield units (HU). The receiver operating characteristic (ROC) curve was used to assess C-VBQ predictive ability. Correlations between demographics and C-VBQ scores were analyzed using linear regression models. RESULTS: 92 patients were included in this study, 36 (39.1%) showed subsidence with a C-VBQ value of 2.05 ± 0.45, in the no-subsidence group C-VBQ Value was 3.25 ± 0.76. The multifactorial logistic regression showed that C-VBQ is an independent predictor of cage subsidence with a predictive accuracy of 93.4%. Pearson's correlation analysis showed a negative correlation between C-VBQ and HU values. Linear regression analysis showed a positive correlation between C-VBQ and cage subsidence. Univariate analyses showed that only age was associated with C-VBQ. CONCLUSIONS: The C-VBQ values obtained using the new measurements independently predicted postoperative cage subsidence after ACCF and showed a negative correlation with HU values. By adding the measurement of non-operated vertebral heights as a control standard, the results of cage subsidence measured by the ratio method are likely to be more robust, perhaps can exclude unavoidable errors caused by different equipment and proportional.