Magnetic resonance imaging based on radiomics for differentiating T1-category nasopharyngeal carcinoma from nasopharyngeal lymphoid hyperplasia: a multicenter study

被引:2
|
作者
Cheng, Jingfeng [1 ]
Su, Wenzhe [2 ]
Wang, Yuzhe [3 ]
Zhan, Yang [3 ]
Wang, Yin [1 ]
Yan, Shuyu [4 ]
Yuan, Yuan [4 ]
Chen, Lingxin [4 ]
Wei, Zixun [4 ]
Zhang, Shengjian [2 ]
Gao, Xin [5 ]
Tang, Zuohua [1 ]
机构
[1] Fudan Univ, Eye & ENT Hosp, Shanghai Med Sch, Dept Radiol, 83 Fenyang Rd, Shanghai 200031, Peoples R China
[2] Fudan Univ, Dept Radiol, Shanghai Canc Ctr, Shanghai 200032, Peoples R China
[3] Fudan Univ, Zhongshan Hosp, Dept Radiol, Shanghai 200032, Peoples R China
[4] Fudan Univ, Shanghai 200032, Peoples R China
[5] Shanghai Universal Med Imaging Diagnost Ctr, Shanghai 200233, Peoples R China
关键词
Radiomics; Magnetic resonance imaging; Nasopharyngeal carcinoma; Lymphoid hyperplasia; MRI; SYSTEM;
D O I
10.1007/s11604-024-01544-0
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose To investigate the role of magnetic resonance imaging (MRI) based on radiomics using T2-weighted imaging fat suppression (T2WI-FS) and contrast enhanced T1-weighted imaging (CE-T1WI) sequences in differentiating T1-category nasopharyngeal carcinoma (NPC) from nasopharyngeal lymphoid hyperplasia (NPH). Materials and methods This study enrolled 614 patients (training dataset: n = 390, internal validation dataset: n = 98, and external validation dataset: n = 126) of T1-category NPC and NPH. Three feature selection methods were used, including analysis of variance, recursive feature elimination, and relief. The logistic regression classifier was performed to construct the radiomics signatures of T2WI-FS, CE-T1WI, and T2WI-FS + CE-T1WI to differentiate T1-category NPC from NPH. The performance of the optimal radiomics signature (T2WI-FS + CE-T1WI) was compared with those of three radiologists in the internal and external validation datasets. Results Twelve, 15, and 15 radiomics features were selected from T2WI-FS, CE-T1WI, and T2WI-FS + CE-T1WI to develop the three radiomics signatures, respectively. The area under the curve (AUC) values for radiomics signatures of T2WI-FS + CE-T1WI and CE-T1WI were significantly higher than that of T2WI-FS (AUCs = 0.940, 0.935, and 0.905, respectively) for distinguishing T1-category NPC and NPH in the training dataset (Ps all < 0.05). In the internal and external validation datasets, the radiomics signatures based on T2WI-FS + CE-T1WI and CE-T1WI outperformed T2WI-FS with no significant difference (AUCs = 0.938, 0.925, and 0.874 for internal validation dataset and 0.932, 0.918, and 0.882 for external validation dataset; Ps > 0.05). The radiomics signature of T2WI-FS + CE-T1WI significantly performed better than three radiologists in the internal and external validation datasets. Conclusion The MRI-based radiomics signature is meaningful in differentiating T1-category NPC from NPH and potentially helps clinicians select suitable therapy strategies.
引用
收藏
页码:709 / 719
页数:11
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