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基于T1加权和FST2加权的影像组学列线图在鉴别多形性腺瘤和沃辛瘤中的价值。

The value of T1- and FST2-Weighted-based radiomics nomogram in differentiating pleomorphic adenoma and Warthin tumor.

作者信息

Sun Hongbiao, Sun Zuoheng, Wang Wenwen, Cha Xudong, Jiang Qinling, Wang Xiang, Li Qingchu, Liu Shiyuan, Liu Huanhai, Chen Qi, Yuan Weimin, Xiao Yi

机构信息

Department of Radiology, Changzheng Hospital, Navy Medical University, Shanghai, China.

Department of Otolaryngology, Changzheng Hospital, Navy Medical University, Shanghai, China; Department of Otolaryngology, Naval Specialty Medical Center, Naval Medical University, Shanghai, China.

出版信息

Transl Oncol. 2024 Nov;49:102087. doi: 10.1016/j.tranon.2024.102087. Epub 2024 Aug 18.

Abstract

PURPOSE

To establish a radiomics nomogram based on MRI radiomics features combined with clinical characteristics for distinguishing pleomorphic adenoma (PA) from warthin tumor (WT).

METHODS

294 patients with PA (n = 159) and WT (n = 135) confirmed by histopathology were included in this study between July 2017 and June 2023. Clinical factors including clinical data and MRI features were analyzed to establish clinical model. 10 MRI radiomics features were extracted and selected from T1WI and FS-T2WI, used to establish radiomics model and calculate radiomics scores (Rad-scores). Clinical factors and Rad-scores were combined to serve as crucial parameters for combined model. Through Receiver operator characteristics (ROC) curve and decision curve analysis (DCA), the discriminative values of the three models were qualified and compared, the best-performing combined model was visualized in the form of a radiomics nomogram.

RESULTS

The combined model demonstrated excellent discriminative performance for PA and WT in the training set (AUC=0.998) and testing set (AUC=0.993) and performed better compared with the clinical model and radiomics model in the training set (AUC=0.996, 0.952) and testing model (AUC=0.954, 0.849). The DCA showed that the combined model provided more overall clinical usefulness in distinguishing parotid PA from WT than another two models.

CONCLUSION

An analytical radiomics nomogram based on MRI radiomics features, incorporating clinical factors, can effectively distinguish between PA and WT.

摘要

目的

建立一种基于MRI影像组学特征并结合临床特征的影像组学列线图,用于鉴别多形性腺瘤(PA)和沃辛瘤(WT)。

方法

本研究纳入了2017年7月至2023年6月期间经组织病理学确诊的294例PA患者(n = 159)和WT患者(n = 135)。分析包括临床数据和MRI特征在内的临床因素以建立临床模型。从T1WI和FS - T2WI中提取并选择10个MRI影像组学特征,用于建立影像组学模型并计算影像组学评分(Rad - scores)。将临床因素和Rad - scores作为联合模型的关键参数。通过受试者操作特征(ROC)曲线和决策曲线分析(DCA),对三种模型的鉴别价值进行评估和比较,以影像组学列线图的形式展示表现最佳的联合模型。

结果

联合模型在训练集(AUC = 0.998)和测试集(AUC = 0.993)中对PA和WT表现出优异的鉴别性能,并且在训练集(AUC = 0.996,0.952)和测试模型(AUC = 0.954,0.849)中比临床模型和影像组学模型表现更好。DCA显示,联合模型在区分腮腺PA和WT方面比另外两种模型具有更高的总体临床实用性。

结论

基于MRI影像组学特征并纳入临床因素的分析性影像组学列线图能够有效区分PA和WT。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7061/11380391/9af666f649a3/gr1.jpg

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