CT based intratumor and peritumoral radiomics for differentiating complete from incomplete capsular characteristics of parotid pleomorphic adenoma: a two-center study

作者全名："Li, Shuang; Su, Xiaorui; Ning, Youquan; Zhang, Simin; Shao, Hanbing; Wan, Xinyue; Tan, Qiaoyue; Yang, Xibiao; Peng, Juan; Gong, Qiyong; Yue, Qiang"

作者地址："[Li, Shuang; Su, Xiaorui; Zhang, Simin; Shao, Hanbing; Wan, Xinyue; Tan, Qiaoyue; Gong, Qiyong] Sichuan Univ, West China Hosp, Huaxi MR Res Ctr HMRRC, Dept Radiol, Chengdu 610041, Peoples R China; [Li, Shuang] Chinese Acad Med Sci, Res Unit Psychoradiol, Chengdu, Sichuan, Peoples R China; [Li, Shuang] Sichuan Univ, West China Hosp, Funct & Mol Imaging Key Lab Sichuan Prov, Chengdu, Sichuan, Peoples R China; [Ning, Youquan; Peng, Juan] Chongqing Med Univ, Affiliated Hosp 1, Dept Radiol, Chongqing, Peoples R China; [Tan, Qiaoyue] Sichuan Univ, West China Hosp, Div Radiat Phys, State Key Lab Biotherapy, Chengdu, Peoples R China; [Tan, Qiaoyue] Sichuan Univ, West China Hosp, Canc Ctr, Chengdu, Peoples R China; [Yang, Xibiao; Yue, Qiang] Sichuan Univ, West China Hosp, Dept Radiol, 37 GuoXue Xiang, Chengdu 610041, Sichuan, Peoples R China; [Gong, Qiyong] Sichuan Univ, West China Xiamen Hosp, Dept Radiol, Xiamen, Fujian, Peoples R China"

通信作者："Gong, QY (通讯作者)，Sichuan Univ, West China Hosp, Huaxi MR Res Ctr HMRRC, Dept Radiol, Chengdu 610041, Peoples R China.; Yue, Q (通讯作者)，Sichuan Univ, West China Hosp, Dept Radiol, 37 GuoXue Xiang, Chengdu 610041, Sichuan, Peoples R China.; Gong, QY (通讯作者)，Sichuan Univ, West China Xiamen Hosp, Dept Radiol, Xiamen, Fujian, Peoples R China."

来源：DISCOVER ONCOLOGY

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:000993834000001

JCR分区：Q2

影响因子：2.8

年份：2023

卷号：14

期号：1

开始页：　

结束页：　

文献类型：Article

关键词：Pleomorphic adenoma; Radiomics; Machine learning; Precise treatment

摘要："ObjectiveCapsular characteristics of pleomorphic adenoma (PA) has various forms. Patients without complete capsule has a higher risk of recurrence than patients with complete capsule. We aimed to develop and validate CT-based intratumoral and peritumoral radiomics models to make a differential diagnosis between parotid PA with and without complete capsule.MethodsData of 260 patients (166 patients with PA from institution 1 (training set) and 94 patients (test set) from institution 2) were retrospectively analyzed. Three Volume of interest (VOIs) were defined in the CT images of each patient: tumor volume of interest (VOItumor), VOIperitumor, and VOIintra-plus peritumor. Radiomics features were extracted from each VOI and used to train nine different machine learning algorithms. Model performance was evaluated using receiver operating characteristic (ROC) curves and the area under the curve (AUC).ResultsThe results showed that the radiomics models based on features from VOIintra-plus peritumor achieved higher AUCs compared to models based on features from VOItumor. The best performing model was Linear discriminant analysis, which achieved an AUC of 0.86 in the tenfold cross-validation and 0.869 in the test set. The model was based on 15 features, including shape-based features and texture features.ConclusionsWe demonstrated the feasibility of combining artificial intelligence with CT-based peritumoral radiomics features can be used to accurately predict capsular characteristics of parotid PA. This may assist in clinical decision-making by preoperative identification of capsular characteristics of parotid PA."

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