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Dynamic contrast-enhanced MRI can quantitatively identify malignant transformation of sinonasal inverted papilloma

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机构: [1]Capital Med Univ, Beijing Tongren Hosp, Dept Radiol, Beijing, Peoples R China [2]Capital Med Univ, Beijing Tongren Hosp, Dept Otolaryngol Head & Neck Surg, Beijing, Peoples R China
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Objective: To investigate the diagnostic performance of quantitative and semi-quantitative parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) in differentiating sinonasal inverted papilloma (SIP) from SIP with coexisting malignant transformation into squamous cell carcinoma (MT-SIP). Methods: This retrospective study included 122 patients with 88 SIP and 34 MT-SIP. Quantitative and semi-quantitative parameters derived from DCE-MRI were compared between SIP and MT-SIP. The multivariate logistic regression analysis was performed to identify independent indicators and construct regression model for distinguishing MT-SIP and SIP. Diagnostic performance of independent indicators and regression model were evaluated using receiver operating coefficient (ROC) analysis and compared using DeLong test. Results: There were significant differences in maximum slope of increase, contrast-enhancement ratio, bolus arrival time, volume of extravascular extracellular space (V-e), and rate constant (K-ep) between SIP and MT-SIP (p < 0.05). There were no significant differences in initial area under the gadolinium curve (p = 0.174) and volume transfer constant (p = 0.105) between two groups. Multivariate analysis results showed that V-e and K-ep were identified as the independent indicators for differentiating MT-SIP from SIP (p < 0.001). Areas under the ROC curves (AUCs) for predicting MT-SIP were 0.779 for V-e and 0.766 for K-ep, The AUC of the combination of V-e and K-ep was 0.831, yielding 83% specificity and 76.5% sensitivity. Conclusion: DCE-MRI can quantitatively differentiate between MT-SIP and SIP. The combination of V-e and K-ep yielded an optimal performance for discriminating SIP from its malignant mimics.

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出版当年[2021]版:
大类 | 3 区 医学
小类 | 4 区 核医学
最新[2023]版:
大类 | 4 区 医学
小类 | 4 区 核医学
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出版当年[2020]版:
Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
最新[2023]版:
Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

影响因子: 最新[2023版] 最新五年平均 出版当年[2020版] 出版当年五年平均 出版前一年[2019版] 出版后一年[2021版]

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第一作者机构: [1]Capital Med Univ, Beijing Tongren Hosp, Dept Radiol, Beijing, Peoples R China
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