FDG-PET/CT Radiomics Models for The Early Prediction of Locoregional Recurrence in Head and Neck Cancer

被引:4
|
作者
Hu Cong [1 ,4 ]
Wang Peng [1 ]
Zhou Tian [2 ]
Vallieres, Martin [3 ]
Xu Chuanpei [1 ,4 ]
Zhu Aijun [1 ,4 ]
Zhang Benxin [1 ,4 ]
机构
[1] Guilin Univ Elect Technol, Sch Elect Engn & Automat, Guilin, Peoples R China
[2] Guilin Univ Aerosp Technol, Sch Elect Informat & Automat, Guilin, Peoples R China
[3] McGill Univ, Med Phys Unit, Montreal, PQ, Canada
[4] Guangxi Key Lab Automat Detecting Technol & Instr, Guilin, Peoples R China
基金
中国国家自然科学基金;
关键词
Local Recurrence; outcome prediction; radiomics; texture analysis; FDG-PET/CT fusion; head and neck cancer;
D O I
10.2174/1573405616666200712181135
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: Both CT and PET radiomics is considered as a potential prognostic biomarker in head and neck cancer. This study investigates the value of fused pre-treatment functional imaging (18F-FDG PET/CT) radiomics for modeling of local recurrence of head and neck cancers. Materials and Methods: Firstly, 298 patients have been divided into a training set (n = 192) and verification set (n = 106). Secondly, PETs and CTs are fused based on wavelet transform. Thirdly, radiomics features are extracted from the 3D tumor area from PETCT fusion. The training set is used to select the features reduction and predict local recurrence, and the random forest prediction models combining radiomics and clinical variables are constructed. Finally, the ROC curve and K-M analysis are used to evaluate the prediction efficiency of the model on the validation set. Results: Two PET/CT fusion radiomics features and three clinic parameters are extracted to construct the radiomics model. AUC value in the verification set 0.70 is better than no fused sets 0.69. The accuracy of 0.66 is not the highest value (0.67). Either consistency index CI 0.70 (from 0.67 to 0.70) or the p-value 0.025 (from 0.03 to 0.025) get the best result in all four models. Conclusion: The radiomics model based on the fusion of PETCT is better than the model based on PET or CT alone in predicting local recurrence, the inclusion of clinical parameters may result in more accurate predictions, which has certain guiding significance for the development of personalized, precise treatment scheme.
引用
收藏
页码:374 / 383
页数:10
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