摘要
Background Distinguishing inverted papilloma （IP） from malignant tumors in the nasal cavity is difficult in a substantial number of cases,thus hindering the administration of appropriate therapeutic strategies.This study aimed to evaluate whether magnetic resonance imaging （MRI）,including dynamic contrast enhanced MRI （DCE-MRI）,could improve differentiation between IP and malignant tumors,and to identify which MRI features were the best in discriminating IP from malignant tumors in the nasal cavity.Methods Non-enhanced,static,and dynamic contrast enhanced MRI was performed in 88 patients with an IP or a malignant tumor in the nasal cavity that had been confirmed by histological results.MRI features of IP and malignant tumors including side,margin,T1 signal intensity,T1 homogeneity,T2 signal intensity,T2 homogeneity,lobulation signs,convoluted cerebriform pattern,extra-sinonasal involvement,pattern of enhancement,Tpeak,Tmax,Clmax,and TIC type were evaluated and correlated with histological findings.Results There were significant differences between IP and malignant tumors in T2 homogeneity,Iobulation signs,convoluted cerebriform pattern,extra-sinonasal involvement,Tpeak,Tmax and TIC types.A convoluted cerebriform pattern had a higher sensitivity and specificity in diagnosis of IP while washout-type TIC had a higher sensitivity and specificity in diagnosis of malignant tumors in the nasal cavity.Non-enhanced combined with static and dynamic enhancement MRI was significantly superior to non-enhanced combined with static enhancement MRI in the differentiation of IP and malignant tumors in the nasal cavity.Multivariate logistic regression analysis identified that the best MRI features were a convoluted cerebriform pattern,extra-sinonasal involvement,and washout-type TIC for both observers （Wang XY and Zhang ZY）.Conclusion Non-enhanced and static combined with dynamic contrast-enhanced MRI improves differentiation of IP and malignant tumors in the nasal cavity.
Background Distinguishing inverted papilloma （IP） from malignant tumors in the nasal cavity is difficult in a substantial number of cases,thus hindering the administration of appropriate therapeutic strategies.This study aimed to evaluate whether magnetic resonance imaging （MRI）,including dynamic contrast enhanced MRI （DCE-MRI）,could improve differentiation between IP and malignant tumors,and to identify which MRI features were the best in discriminating IP from malignant tumors in the nasal cavity.Methods Non-enhanced,static,and dynamic contrast enhanced MRI was performed in 88 patients with an IP or a malignant tumor in the nasal cavity that had been confirmed by histological results.MRI features of IP and malignant tumors including side,margin,T1 signal intensity,T1 homogeneity,T2 signal intensity,T2 homogeneity,lobulation signs,convoluted cerebriform pattern,extra-sinonasal involvement,pattern of enhancement,Tpeak,Tmax,Clmax,and TIC type were evaluated and correlated with histological findings.Results There were significant differences between IP and malignant tumors in T2 homogeneity,Iobulation signs,convoluted cerebriform pattern,extra-sinonasal involvement,Tpeak,Tmax and TIC types.A convoluted cerebriform pattern had a higher sensitivity and specificity in diagnosis of IP while washout-type TIC had a higher sensitivity and specificity in diagnosis of malignant tumors in the nasal cavity.Non-enhanced combined with static and dynamic enhancement MRI was significantly superior to non-enhanced combined with static enhancement MRI in the differentiation of IP and malignant tumors in the nasal cavity.Multivariate logistic regression analysis identified that the best MRI features were a convoluted cerebriform pattern,extra-sinonasal involvement,and washout-type TIC for both observers （Wang XY and Zhang ZY）.Conclusion Non-enhanced and static combined with dynamic contrast-enhanced MRI improves differentiation of IP and malignant tumors in the nasal cavity.
基金
This work was supported by Beijing Excellent Talents Foundation （No. 2010D003034000033）, Beijing Municipal Natural Science Foundation （No. 7112030）, and High Levels of Health Technical Personnel in Beijing City （No. 2011-3-047）.
