■内翻性乳头状瘤(IP)和鼻息肉(NP),作为两个良性病变,在MRI成像和临床上很难区分,特别是在预测嗅神经是否受损时,这是治疗和预后的重要方面。我们计划建立一种新的生物标志物来区分IP和NP可能侵入嗅神经,并分析其诊断效能。
■共收集到74例IP和55例NP。129名患者中总共有80%用作训练集(59IP和44NP);其余用作测试集。作为多模态研究(两个MRI序列和临床指标),收集术前MR图像,包括T2加权磁共振成像(T2-WI)和对比增强T1加权磁共振成像(CE-T1WI).从MR图像中提取放射学特征。然后,使用最小绝对收缩和选择算子(LASSO)回归方法来减少高度冗余和不相关。随后,影像组学模型由rad评分公式构建。曲线下面积(AUC),准确度,灵敏度,特异性,阳性预测值(PPV),并计算了模型的负预测值(NPV)。最后,决策曲线分析(DCA)用于评价模型的临床实用性。
■年龄差异显著,鼻出血,和两个病变之间的低表达(p<0.05)。总的来说,从T2-WI和CE-T1WI图像中提取了1,906个放射学特征。选择功能后,使用12个关键特征来构建模型。AUC,灵敏度,特异性,最优模型的测试队列的准确性为,分别,0.9121、0.828、0.9091和0.899。最佳模型的测试队列的AUC为0.9121;此外,灵敏度,特异性,和准确性,分别,0.828、0.9091和0.899。
■一种结合了多模态MRI影像组学和临床指标的新生物标志物,可以有效区分可能侵入嗅神经的IP和NP,可为个体化治疗提供有价值的决策依据。
UNASSIGNED: Inverted papilloma (IP) and nasal polyp (NP), as two benign lesions, are difficult to distinguish on MRI imaging and clinically, especially in predicting whether the olfactory nerve is damaged, which is an important aspect of treatment and prognosis. We plan to establish a new biomarker to distinguish IP and NP that may invade the olfactory nerve, and to analyze its diagnostic efficacy.
UNASSIGNED: A total of 74 cases of IP and 55 cases of NP were collected. A total of 80% of 129 patients were used as the training set (59 IP and 44 NP); the remaining were used as the testing set. As a multimodal study (two MRI sequences and clinical indicators), preoperative MR images including T2-weighted magnetic resonance imaging (T2-WI) and contrast-enhanced T1-weighted magnetic resonance imaging (CE-T1WI) were collected. Radiomic features were extracted from MR images. Then, the least absolute shrinkage and selection operator (LASSO) regression method was used to decrease the high degree of redundancy and irrelevance. Subsequently, the radiomics model is constructed by the rad scoring formula. The area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the model have been calculated. Finally, the decision curve analysis (DCA) is used to evaluate the clinical practicability of the model.
UNASSIGNED: There were significant differences in age, nasal bleeding, and hyposmia between the two lesions (p < 0.05). In total, 1,906 radiomic features were extracted from T2-WI and CE-T1WI images. After feature selection, using 12 key features to bulid model. AUC, sensitivity, specificity, and accuracy on the testing cohort of the optimal model were, respectively, 0.9121, 0.828, 0.9091, and 0.899. AUC on the testing cohort of the optimal model was 0.9121; in addition, sensitivity, specificity, and accuracy were, respectively, 0.828, 0.9091, and 0.899.
UNASSIGNED: A new biomarker combining multimodal MRI radiomics and clinical indicators can effectively distinguish between IP and NP that may invade the olfactory nerve, which can provide a valuable decision basis for individualized treatment.