Department of Otolaryngology Head and Neck Surgery, Beijing TongRen Hospital, Capital Medical University, Beijing, PR China; Beijing Key Laboratory of nasal diseases, Beijing Institute of Otolaryngology, Beijing, PR China; Department of Otolaryngology Head and Neck Surgery, Beijing DiTan Hospital, Capital Medical University, Beijing, PR China.
Department of Otolaryngology Head and Neck Surgery, Beijing DiTan Hospital, Capital Medical University, Beijing, PR China.
Rhinology. 2020 Jun 1;58(3):248-256. doi: 10.4193/Rhin19.240.
Accurate preoperative prediction of the malignant transformation of sinonasal inverted papilloma (SNIP) is essential for radical resection of tumours and prevention of recurrence. We here explored the predictive value of preoperative computed tomography (CT) and magnetic resonance imaging (MRI).
The study was performed on 268 patients with SNIP with (n = 78) or without (n = 190) coexistent malignant transformation. We used univariate and multivariate logistic regression analysis method to screen for independent risk factors, and established a nomogram model. Finally, using receiver operating characteristic curves, we assessed the diagnostic value of the independent risk factors for malignant transformation of SNIP.
We identified bone erosion on CT, change in convoluted cerebriform pattern (CCP) on MRI, and washout-type time intensity curve (TIC) of dynamic contrast-enhanced (DCE)-MRI were independent predictors of malignant transformation of SNIP. The scores of these three independent risk factors from the nomogram model were 10, 7 and 8, respectively. The area under the receiver operating characteristic curve for predicting SNIP malignancy was 0.954 for the nomogram model, 0.826 for bone erosion, 0.776 for washout-type TIC, and 0.810 for CCP mutation.
Of the independent risk factors and related combination identified, the nomogram model based on bone destruction on CT, CCP mutation on MRI, and washout-type TIC of DCE-MRI had the best predictive value for malignant transformation of SNIP.
准确预测鼻窦内翻性乳头状瘤(SNIP)的恶性转化对于肿瘤的根治性切除和复发的预防至关重要。我们在此探讨了术前计算机断层扫描(CT)和磁共振成像(MRI)的预测价值。
本研究纳入了 268 例 SNIP 患者,其中伴(n=78)或不伴(n=190)伴发恶性转化。我们采用单因素和多因素逻辑回归分析方法筛选独立危险因素,并建立了列线图模型。最后,通过受试者工作特征曲线评估 SNIP 恶性转化的独立危险因素的诊断价值。
我们发现 CT 上的骨侵蚀、MRI 上的卷曲脑回样模式(CCP)改变和动态对比增强(DCE)-MRI 的洗脱型时间强度曲线(TIC)是 SNIP 恶性转化的独立预测因子。来自列线图模型的这三个独立危险因素的评分分别为 10、7 和 8。列线图模型预测 SNIP 恶性肿瘤的受试者工作特征曲线下面积为 0.954,骨侵蚀为 0.826,洗脱型 TIC 为 0.776,CCP 突变为 0.810。
在确定的独立危险因素及其相关组合中,基于 CT 上骨破坏、MRI 上 CCP 突变和 DCE-MRI 洗脱型 TIC 的列线图模型对 SNIP 恶性转化具有最佳的预测价值。