Logistic regression analysis of non-enhanced MR imaging,static and dynamic enhanced MR imaging in prediction of malignancy of vertebral compression fractures
- VernacularTitle:非增强MRI、静态和动态对比增强MRI预测脊柱压缩性骨折良、恶性的Logistic回归分析
- Author:
Yunfei ZHA
- Publication Type:Journal Article
- Keywords:
Spine;
Fracture;
Regression analysis;
Magnetic resonance;
Contrast enhancement
- From:
Journal of Chongqing Medical University
2007;0(10):-
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To evaluate non-enhanced MR imaging,static and dynamic enhanced MR imaging in differentiation of be-nign from malignant vertebral compression fractures and to evaluate which MR imaging parameters are most predictive of malignancy.Methods:Non-enhanced MR imaging,static and dynamic gadolinium-enhanced MR imaging were performed on 43 patients with acute osteoporotic compression fracture and 49 patients with malignant compression fracture proved by clinical follow-up and/or histologic findings.Binary multivariate logistic regression analysis was used to identify the best combination of MR imaging parameters that might be predictive of malignancy.Subjective overall performance of diagnostic models for sensitivi-ty,specificity and accuracy was evaluated with receiver operating characteristic curve(ROC).Results:Univariate analysis showed that the frequency distribution of MR imaging parameters including T1 weighted imaging homogeneity of vertebrae,convex pos-terior of vertebrae,retropulsion of the posterosuperior angle of vertebrae,pedicle involvement,epidural soft tissue mass,paraverte-bral soft tissue lesions,pattern of enhancement of vertebrae,pattern of enhancement of paravertebral soft tissue lesions,start of dynamic enhancement and pattern of time-intensity curve(TIC) were different between benign and malignant compression frac-ture(P0.05).ROC analysis showed that combined non-enhanced,static and dynamic enhanced MR imaging parameters(model 3) were superior to non-enhanced MR imaging pa-rameter(smodel 1)iction of malignancy.The sensitivity,specificity and accuracy of model 3 were 81.6%,90.7% and 85.9%,respec-tively.Multivariate logistic regression analysis revealed the most discriminating parameters were pedicle involvement,pattern of enhancement of vertebrae and pattern of TIC(OR value were 3.558,4.666 and 0.007,respectively,P
