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Value of T2-weighted-based radiomics model in distinguishing Warthin tumor from pleomorphic adenoma of the parotid.
Hu, Zhenbin; Guo, Junjie; Feng, Jiajun; Huang, Yuqian; Xu, Honggang; Zhou, Quan.
Afiliação
  • Hu Z; Department of Medical Imaging, The Third Affiliated Hospital of Southern Medical University, No.183, Zhongshan Avenue West, Tianhe District, Guangzhou, 510630, Guangdong, China. hu_zhenbin1127@163.com.
  • Guo J; Department of Medical Imaging, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, No.1 Panfu Road, Yuexiu District, Guangzhou, 510030, Guangdong, China.
  • Feng J; Department of Medical Imaging, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, No.1 Panfu Road, Yuexiu District, Guangzhou, 510030, Guangdong, China.
  • Huang Y; Department of Medical Imaging, The Third Affiliated Hospital of Southern Medical University, No.183, Zhongshan Avenue West, Tianhe District, Guangzhou, 510630, Guangdong, China.
  • Xu H; Department of Medical Imaging, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, No.1 Panfu Road, Yuexiu District, Guangzhou, 510030, Guangdong, China. eyxuhonggang@scut.edu.cn.
  • Zhou Q; Department of Medical Imaging, The Third Affiliated Hospital of Southern Medical University, No.183, Zhongshan Avenue West, Tianhe District, Guangzhou, 510630, Guangdong, China. zhouquan3777@smu.edu.cn.
Eur Radiol ; 33(6): 4453-4463, 2023 Jun.
Article em En | MEDLINE | ID: mdl-36502461
ABSTRACT

OBJECTIVES:

The differentiation of Warthin tumor and pleomorphic adenoma before treatment is crucial for clinical strategies. The aim of this study was to develop and test a T2-weighted-based radiomics model for differentiating pleomorphic adenoma from Warthin tumor of the parotid gland.

METHODS:

A total of 117 patients, including 61 cases of Warthin tumor and 56 cases of pleomorphic adenoma, were retrospectively enrolled from two centers between January 2010 and June 2022. The training set included 82 cases, and the validation set included 35 cases. From T2-weighted images, 971 radiomics features were extracted. Seven radiomics features remained after a two-step selection process. We used the seven radiomics features and clinical factors through multivariable logistic regression to build radiomics and clinical models, respectively. A radiomics-clinical model was also built that combined the independent clinical predictors with the radiomics features. Through ROC curves, the three models were evaluated and compared.

RESULTS:

In the radiomics model, AUCs were 0.826 and 0.796 in training and validation sets, respectively. In the clinical model, the AUCs were 0.923 and 0.926 in the training and validation sets, respectively. Decision curve analysis revealed that the radiomics-clinical model had the best diagnostic performance for distinguishing Warthin tumor from pleomorphic adenoma of the parotid gland (AUC = 0.962 and 0.934 for the training and validation sets, respectively).

CONCLUSION:

The radiomics-clinical model performed well in differentiating pleomorphic adenoma from Warthin tumor of the parotid gland. KEY POINTS • The clinical model outperformed the radiomics model in distinguishing pleomorphic adenoma from Warthin tumor of the parotid gland. • The radiomics features extracted from T2-weighted images could help differentiate pleomorphic adenoma from Warthin tumor of the parotid gland. • The radiomics-clinical model was superior to the radiomics and the clinical models for differentiating pleomorphic adenoma from Warthin tumor of the parotid gland.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Parotídeas / Adenolinfoma / Adenoma Pleomorfo Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Parotídeas / Adenolinfoma / Adenoma Pleomorfo Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article